TARGETED DOCUMENT ASSIGNMENTS IN AN ELECTRONIC DISCOVERY SYSTEM
Embodiments of the invention relate to systems, methods, and computer program products for improved electronic discovery. More specifically, embodiments relate to computer program products for targeted document review assignments by determining concept-related data groupings within the overall corpus of data associated with a case and assembling the targeted document review assignments based on the concept-related data groupings. As such, document reviewers are presented with assignments that have highly conceptually-related documents, which results in further efficiency in the review process.
The present application claims priority to U.S. patent application Ser. No. 12/730,807, entitled, “Search Term Hit Counts In An Electronic Discovery System,” filed on Mar. 24, 2010 which claims priority to Provisional Application No. 61/164,276 entitled “Electronic Discovery System” filed Mar. 27, 2009, and assigned to the assignee hereof and both hereby expressly incorporated by reference herein.
FIELDIn general, embodiments of the invention relate to methods, systems, apparatus and computer program products for electronic discovery and, more particularly, for providing targeted document review assignments to electronic discovery document reviewers.
BACKGROUNDElectronic discovery, commonly referred to as e-discovery, refers to any process in which electronic data is sought, located, secured and searched with the intent of using it as evidence in a legal proceeding, an audit, a securities investigation, a forensics investigation or the like. E-discovery can be carried out offline on a particular computer or it can be accomplished in a network environment.
The nature of digital data makes it extremely well-suited for investigation. In particular, digital data can be electronically searched with ease, whereas paper documents must be scrutinized manually. Furthermore, digital data is difficult or impossible to completely destroy, particularly if the data is stored in a network environment. This is because the data appears on multiple hard drives, and because digital files, even if deleted, generally can be undeleted. In fact, the only reliable means of destroying digital data is to physically destroy any and all hard drives where it is stored.
In the process of electronic discovery, data of all types can serve as evidence. This can include text, image, calendar event data, databases, spreadsheets, audio files, multimedia files, web sites and computer programs. Electronic mail (i.e., e-mail) can be an especially valuable source of evidence in civil or criminal litigation, because people are often less careful in these exchanges than in hard copy correspondence such as written memos or postal letters.
E-discovery is an evolving field that goes far beyond mere technology. It gives rise to multiple issues, many of which have yet to be resolved. For example, identifying data required to satisfy a given discovery request, locating the appropriate set of data that has been identified, and retrieving the data once it has been identified and located all pose problems in and of themselves. This is especially evident if the data that is being identified, located and retrieved comes from an evolving or disparate enterprise, such as a corporation that has experienced mergers, acquisitions, downsizing and the like. Mergers and acquisitions mean that the technology infrastructure across the enterprise may vary, at least in the interim. However, e-discovery must be able locate and retrieve data from these disparate technology infrastructure in a timely fashion, sometimes within days of when the merger/acquisition occurs.
In addition to identifying, locating and retrieving digital data, the most critical part of any electronic discovery is the preservation of data, which involves maintaining an original source copy and storing it for preservation purposes or furthering processing. This too becomes a daunting task for the enterprise system that encompasses a myriad of different technology infrastructures and the like. Therefore, a need exists to improve the identification, location, retrieval and preservation processes, especially in instances in which the enterprise system includes disparate technology infrastructures and the like.
As previously noted, e-discovery, as opposed as conventional discovery of printed materials, provides for the ability to filter or search the data so as to reduce the volume of data to only that which is relevant to the request. Such searching is typically accomplished by determining a specific date range for the request, providing key words relevant to the case and the like. Improvements in the area of searching are greatly in need to further add efficiency to the overall e-discovery process.
Once data has been retrieved, preserved and, in some instances, searched the electronic data may be reviewed by the requesting entry, such as a law firm, securities commission or the like. While large requests are generally suited for online review, the manner in which the data is presented for review adds efficiency to the review process and ultimately drives the cost of the review process. Therefore, improvements in the manner in which data is presented for review are also desirable as a means of increasing efficiency and reducing costs.
Lastly, once the digital data has been reviewed, data identified as relevant may need to be produced in a tangible format for further analysis or legal evidentiary purposes. The produced documents must be properly identified and include necessary redactions and confidentiality markings.
Up until now, e-discovery management has been conducted on a case-by-case basis, meaning all tasking and workflow related to the e-discovery is based at the case level. Such management does not allow for finer granularity in the management of a case or for links to exist between different cases for the purpose of leveraging the e-discovery related to one case to another new or pre-existing case. Therefore, a need exists to improve the manner in which cases are managed and, in particular, how tasking and workflow are managed depending on case requirements and the like.
Specific problems associated with electronic discovery are related to the inefficiencies and the inaccuracies in the document review process. Document redundancy, in the form of identical documents or documents that are highly similar, leads to reviewers having to review and code the same or highly similar document numerous times. Such redundant reviewing and coding of documents unnecessarily increases review time. In addition, when the same or highly similar document is reviewed by more than one reviewer the likelihood exists that the different reviewers will code the document differently. Such differences in coding the same or highly similar document provide for inaccuracies that question the overall reliability of the review process.
In addition to problems associated with the redundant review of documents, another problem is perceived by document review assignments that are random in scope and, thus, require the reviewer to determine the context and/or applicability of each and every document in the assignment in order to gauge the relevancy of the document and properly code the document. Such randomness or lack of focus in the document review process not only frustrates the review but adds to the overall review time.
Therefore, a need exists to provide for efficiency and accuracy within the document review processing stage of an electronic discovery system. The desired methods, apparatus and systems should provide for limiting the amount of document redundancy in the data to be reviewed by lessening or eliminating the occurrence of identical documents or highly similar documents. By eliminating document redundancy not only is the overall review time reduced but review reliability is increased by not subjecting the same or highly similar documents to multiple review by various different reviewers. In addition, the desired method, apparatus and system should provide for targeted document review assignments that are limited in terms of concepts or search terms, thereby decreasing the time for review further because the documents in the assignment are conceptually related.
SUMMARYThe following presents a simplified summary of one or more embodiments in order to provide a basic understanding of such embodiments. This summary is not an extensive overview of all contemplated embodiments, and is intended to neither identify key or critical elements of all embodiments, nor delineate the scope of any or all embodiments. Its sole purpose is to present some concepts of one or more embodiments in a simplified form as a prelude to the more detailed description that is presented later.
Embodiments of the present invention relate to systems, apparatus, methods, and computer program products for electronic discovery and, in particular, provide for predictive, automated coding of identical or highly similar documents for the purpose of limiting the volume of documents requiring review. In addition, by coding identical or highly similar documents from the corpus of electronic data associated with a case, the present invention adds reliability to the review process by lessening the likelihood of multiple reviewers reviewing the same document and coding it differently.
Other embodiments of the present invention relate to systems, apparatus, methods and computer program products that provide for targeted document review assignments by determining concept-related data groupings within the overall corpus of data associated with a case and assembling the targeted document review assignments from the concept-related data groupings. As such reviewers are presented with document review assignments that have highly related documents in terms of the concept or concepts covered in the documents. The review of such targeted assignments is expedited due to the relational aspect of the documents.
A method for predictive coding of electronic discovery documents provides embodiments of the present invention. The method includes receiving, at a computing device, a document coding input that assigns a review code to a first document associated with a case within an electronic discovery system. The review code may include a mark or a mark and a tag. The method further includes determining, via a computing device processor, that one or more second documents associated with the case are at least similar to the first document and assigning, via a computing device processor, the review code to the one or more second documents based on the determination.
In specific embodiments the method further includes removing, via a computing device processor, the one or more second documents from a plurality of pending review documents based on the assignment of the review code. In such embodiments, the removing of the one or more second documents may occur in near real-time, or shortly thereafter, to receiving the document coding input.
In other specific embodiment of the method determining further includes determining via the computing device processor, that one or more second documents associated with the case are a same representation (e.g., nearly identical) of the first document. In such embodiments, determining that the one or more second documents are the same representation may include determining, via the computing device processor, that the one or more second documents have a same hash mark as the first document.
In still further embodiments of the method determining includes providing, via computing device processor, probability analysis to determine the one or more second documents associated with the case are at least similar to the first document. In such embodiments, providing probability analysis may further include providing, via the computing device processor, at least one of clustering technique analysis, machine learning or Bayesian technique analysis to determine the one or more second documents associated with the case are at least similar to the first document. In other related embodiments of the method, determining may include determining, via the computing device, that the one or more second documents include a predetermined threshold of words, phrases or concepts included in the first document.
In still further embodiments the method includes providing a confidence indicator for the one or more second documents based on the determination, wherein the confidence indicator indicates a level of similarity between the one or more second documents and the first document. For example, the confidence indicator may a numeric or alpha score. In such embodiments, assigning may further include assigning, via the computing device processor, the review code assigned to the first document to the one or more second documents based on the determination and the confidence indicator.
In specific embodiments of the method, the received input codes the documents as privileged. In such embodiments, determining may further include determining, via the computing device processor, that one or more third documents associated with other cases in the electronic discovery system are at least similar to the first document. In addition, assigning may further include assigning, via the computing device processor, a privileged code to the one or more third documents based on the determination.
An apparatus for predictive coding provides other embodiments of the invention. The apparatus includes a computing platform including at least one processor and a memory. The apparatus further includes a document coding application stored in the memory, executable by the processor and configured to receive a document coding input that assigns a review code to a first document associated with a case. The apparatus further includes a predictive document coding assignment application stored in the memory, executable by the processor and configured to determine that one or more second documents associated with the case are at least similar to the first document and assign the review code to the one or more second documents based on the determination.
In specific embodiments of the apparatus, the predictive document coding assignment application is further configured to remove the one or more second documents from a plurality of pending review documents based on the assignment of the review code. In such embodiments the removal of the one or more second documents may occur in near real-time, or shortly thereafter, to the document coding application receiving the document coding input.
In other specific embodiments of the apparatus, the predictive document coding assignment application is further configured to determine that one or more second documents associated with the case are a same representation (e.g., nearly identical) of the first document. In such embodiments, the predictive document coding assignment application may be further configured to determine that the one or more second documents have a same hash mark as the first document.
In still further embodiments of the apparatus, the predictive document coding assignment application is further configured to perform probability analysis to determine the one or more second documents associated with the case are at least similar to the first document. The probability analysis may include, but is not limited to, clustering technique analysis, machine learning or Bayesian technique analysis. In other related embodiments, the predictive document coding assignment application is further configured to determine that the one or more second documents include a predetermined threshold of words, phrases and/or concepts included in the first document.
In other specific embodiments of the apparatus the predictive document coding assignment application is further configured to determine a confidence indicator for the one or more second documents based on the determination, wherein the confidence indicator indicates a level of similarity between the one or more second documents and the first document. In such embodiments, the confidence level indicator may a numeric or alpha indicator score. In further such embodiments, the predictive document coding assignment application may be further configured to assign the review code to the first document to the one or more second documents based on the determination and the confidence indicator.
In certain specific embodiments of the apparatus in which the received input code is privileged, the predictive document coding assignment application may be further configured to determine that one or more third documents associated with other cases in the electronic discovery system are at least similar to the first document and assign a privileged code to the one or more third documents based on the determination.
A computer program product including a computer-readable medium defines yet other embodiments of the invention. The computer-readable medium includes a first set of codes for causing a computer to receive a document coding input that assigns a review code to a first document associated with a case within an electronic discovery system. The computer-readable medium additionally includes a second set of codes for causing a computer to determine that one or more second documents associated with the case are at least similar to the first document. In addition, the computer-readable medium includes a third set of codes for causing a computer to assign the review code assigned to the first document to the one or more second documents based on the determination.
A method for determining targeted document review assignments in an electronic discovery system defines yet further embodiments of the invention. The method includes receiving, at a computing device, a plurality of predetermined concepts included within a corpus of electronic data associated with a case in the electronic discovery system. In accordance with specific embodiments, the predetermined concepts may be defined as a final search term set. The method further includes determining, via a computing device processor, a plurality of data groupings for the corpus of electronic. Each of the data groupings is defined by inclusion of at least one of the predetermined concepts. The method further includes generating, via a computing device processor, a plurality of document review assignments based on the determined data groupings.
In specific embodiments of the method determining further includes implementing, via the computing device processor, conceptual clustering techniques to determine the plurality of data groupings for the corpus of electronic data.
In other specific embodiments of the method, each of the generated assignments include at least a portion of one of the plurality of data groupings or each of the assignments include one or more of the plurality of data groupings.
In further specific embodiments of the method, assigning is based on associated data groupings within the document review assignments. In further related embodiments, assigning occurs such that two or more document review assignments that include a portion of a same segment are assigned to a same document reviewer.
In other specific embodiments of the invention, generating further includes generating, at the computing device, the document review assignments wherein each assignment includes at least approximately 2,000 documents.
An apparatus for determining targeted document review assignments in an electronic discovery system provides for further embodiments of the invention. The apparatus includes a computing platform including a memory and a processor. The apparatus further includes a targeted document review assignment application stored in the memory, executable by the processor and configured to receive a plurality of predetermined concepts, such as a final search term set and determine a plurality of data groupings for a corpus of electronic data. Each of the data groupings is defined by inclusion of at least one of the predetermined concepts in the data grouping. The application is further configured to generate a plurality of document review assignments based on the determined data groupings.
In specific embodiments of the apparatus, the targeted document review assignment application is further configured to implement conceptual clustering techniques to determine the plurality of data groupings for the corpus of electronic data.
In other specific embodiments of the apparatus, the targeted document review assignment application is further configured to generate the plurality of document review assignments, wherein each of assignments includes at least a portion of one of the plurality of data groupings and/or each assignment is based on associated data groupings within the document review assignments.
In further embodiments of the apparatus, the targeted document review assignment application is further configured to assign one or more of the plurality of document review assignments to each of the plurality of document reviewers, such that two or more document review assignments that include a portion of a same segment are assigned to a same document reviewer.
In still further related embodiments of the apparatus, the targeted document review assignment application is further configured to generate the document review assignments wherein each assignment includes at least approximately 2,000 documents.
A computer program product including a computer-readable medium defines other specific embodiments of the invention. The computer-readable medium includes a first set of codes for causing a computer to receive a plurality of predetermined concepts included within a corpus of electronic data associated with a case in the electronic discovery system. The computer-readable medium additionally includes a second set of codes for causing a computer to determine a plurality of data groupings for the corpus of electronic data. Each of the data groupings is defined by inclusion of at least one of the predetermined concepts in the data grouping. Additionally, the computer-readable medium includes a third set of codes for causing a computer to generate a plurality of document review assignments based on the determined data groupings.
Thus, further details are provided below for systems, apparatus, methods and computer program products for predictive and automated coding of identical or highly similar documents for the purpose of limiting the volume of documents requiring review and thereby increasing the overall efficiency of the document review process. Additional details are provided below for systems, apparatus, methods and computer program products that provide for targeted document review assignments by determining concept-related data groupings within the overall corpus of data associated with a case and assembling the targeted document review assignments based on the concept-related data groupings. As such, reviewers are presented with document review assignments that have highly conceptually-related documents, which results in further efficiency in the review process.
To the accomplishment of the foregoing and related ends, the one or more embodiments comprise the features hereinafter fully described and particularly pointed out in the claims. The following description and the annexed drawings set forth in detail certain illustrative features of the one or more embodiments. These features are indicative, however, of but a few of the various ways in which the principles of various embodiments may be employed, and this description is intended to include all such embodiments and their equivalents.
Having thus described embodiments of the invention in general terms, reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, and wherein:
Embodiments of the present invention now may be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all, embodiments of the invention are shown. Indeed, the invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure may satisfy applicable legal requirements. Like numbers refer to like elements throughout.
As may be appreciated by one of skill in the art, the present invention may be embodied as a method, system, computer program product, or a combination of the foregoing. Accordingly, the present invention may take the form of an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may generally be referred to herein as a “system.” Furthermore, embodiments of the present invention may take the form of a computer program product on a computer-readable medium having computer-usable program code embodied in the medium.
Any suitable computer-readable medium may be utilized. The computer-readable medium may be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium. More specific examples of the computer readable medium include, but are not limited to, the following: an electrical connection having one or more wires; a tangible storage medium such as a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a compact disc read-only memory (CD-ROM), or other optical or magnetic storage device; or transmission media such as those supporting the Internet or an intranet. Note that the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted, or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.
Computer program code for carrying out operations of embodiments of the present invention may be written in an object oriented, scripted or unscripted programming language such as Java, Perl, Smalltalk, C++, or the like. However, the computer program code for carrying out operations of embodiments of the present invention may also be written in conventional procedural programming languages, such as the “C” programming language or similar programming languages.
Embodiments of the present invention are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products. It may be understood that each block of the flowchart illustrations and/or block diagrams, and/or combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create mechanisms for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instruction means which implement the function/act specified in the flowchart and/or block diagram block(s).
The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions/acts specified in the flowchart and/or block diagram block(s). Alternatively, computer program implemented steps or acts may be combined with operator or human implemented steps or acts in order to carry out an embodiment of the invention.
Thus, apparatus, systems, methods and computer program products are herein disclosed that provide for increased efficiency in the document review process of electronic discovery. Specific embodiment of the invention provide for predictive and automated coding of electronic discovery documents that are determined to be a same representation (i.e., nearly identical) or highly similar. Such predictive and automated coding of review documents limits the overall volume of documents requiring review, thereby increasing efficiency. In addition, by automatically coding documents that are the same representation and/or highly similar, the present invention adds reliability to the review process by lessening the likelihood of multiple reviewers reviewing the same document and coding it differently.
Other embodiments of the present invention relate to systems, apparatus, methods and computer program products that provide for targeted document review assignments. Targeted document review assignments result from determining concept-related data groupings within the overall corpus of data associated with a case and generating the targeted document review assignments based on the concept-related data groupings. As a result, document reviewers are presented with assignments that are highly concept-related, adding further efficiency to the review process.
The memory 16 of apparatus 10 stores document coding application 18, which is executable by processor 14 and configured to receive a document coding input 20 that assigns a review code 22 to a first document 24 associated with a case within an electronic discovery system. In specific embodiments of the invention, the review code 22 includes a mark. Examples of marks include, but are not limited to, relevant, not relevant, important, not important, privileged, hot, trash, technical issue and the like. In other specific embodiments, the review code 22 may include a mark and a tag, wherein the tag provides a subcategory classification of the corresponding mark.
The memory 16 of apparatus 10 additionally includes predictive document coding application 26, which is executable by processor 14 and includes document similarity evaluator 28 and code assignor 30. Document similarity evaluator 28 is configured to determine that one or more second documents 32 associated with the case are at least similar to the first document 24. In specific embodiments of the invention, the document similarity evaluator 28 is configured to determine same representations (i.e., identical or near identical) of documents by comparing hash marks or the like. In other embodiments of the invention, the document similarity evaluator is configured to determine highly similar documents by probability analysis, such as clustering technique analysis, machine learning and/or Bayesian technique analysis and/or the like. In such embodiments a predetermined threshold of words, phrases and/or concepts may be required to be present in the second document 32 in order for it to be deemed highly similar to the first document 24.
Code assignor 30 is configured to assign the same review code 22 assigned to the first document to the one or more second documents 32 based on the determination that the second documents 32 are the same representation and/or highly similar. In specific embodiments of the invention the code assignor 30 is configured to automatically assign the same review code 22 assigned to the first document to the one or more second documents 32 based on the determination.
In specific embodiments, the document coding application 18 may be implemented by an electronic discovery associate, such as a case analyst, prior to assigning document review assignments to reviewers. In such embodiments, the electronic discovery associate may review and code a small subset of the overall corpus of electronic data associated with the case. The predictive coding application 26 is subsequently executed on the overall corpus of electronic data to determine and pre-code documents that are the same representation (i.e., identical or nearly identical) and/or highly similar. In such instances, the documents that are determined to be the same representation and/or highly similar may be pre-coded with the same review code 22 as the reviewed document and removed from the overall corpus of data prior to forming document review assignments.
In other embodiments of the invention, the document coding application 18 may be implemented by the document reviewer during the document review process. In such embodiments, once a document coding input 20 is received for a first document being reviewed, the predictive coding application 26 is executed on the documents assigned to the reviewer to determine and code documents that are the same representation and/or highly similar. In such instances, the documents that are determined to be the same representation and/or highly similar may be coded with the same review code 22 as the first document coding input 20 and removed from the assigned documents.
In further such embodiments of the invention, once the document coding input 20 is received, the predictive coding application may be executed on documents currently assigned, and in some instance currently being reviewed by other reviewers, to determine identical or highly similar documents in their respective assignments, code the identical and/or highly similar documents accordingly and remove the coded documents from their assigned documents.
In still further embodiments of the invention, once the document coding input 20 is received, the predictive coding application may be executed on the yet unassigned remainder of the corpus of electronic data associated with the case to determine identical and/or highly similar documents in the remainder of the corpus of electronic data, code the identical and/or highly similar documents accordingly.
It should also be noted that the document coding application 18 may be executed by a primary document reviewer or a secondary document reviewer. In certain instances, the secondary document reviewer is employed, in addition to the primary document reviewer, to provide verification/confirmation of the initial coding of the document by the primary document reviewer. Thus, in certain embodiments of the invention, the predictive document coding application 26 is executed after the secondary document reviewer makes the document coding input 20, i.e., confirms the initial coding of the document by the initial reviewer. While in other embodiments of the invention, in which a secondary document reviewer is not employed, the predictive coding application 26 is executed after the primary document reviewer makes the document coding input 20. In such embodiments, the determination of identical or highly similar documents, the coding of the identical or highly similar documents with the same code as the reviewed document and/or the removal of the document from assigned documents and/or the corpus of electronic data may occur in near real-time in relation to receipt of the document coding input 20 by the document coding application 18. Near real-time is defined herein as the time required for data transmission and data processing to conduct the necessary functions needed to carry out the actions of determining the identical or highly similar documents and/or coding the identical or highly similar documents and/or removing the documents form the assigned documents and/or the corpus of electronic data.
Referring to
The memory 46 of apparatus 40 stores targeted document review assignment application 48 that includes concept-based data grouping mechanism 50 and document review assignment generator 52. Concept-based data grouping mechanism 50 is configured to receive a plurality of predetermined concepts 54, (e.g., search terms included a final or non-final search term set) and determine a plurality of data groupings 56 for a corpus of electronic data, such that, each of the data groupings are defined by inclusion of at least one of the predetermined concepts 54. A corpus of electronic data is herein defined as the entire collection of electronic data associated with a case or matter or a majority portion (i.e., greater than fifty percent) of the entire collection of electronic data associated with a case.
The document review assignment generator 52 is configured to generate a plurality of document review assignments 58 that are based on the determined data groupings 56. For example, in certain embodiments, in which a data grouping 56 is larger in terms of the number of documents or file size than the document review assignments 58, an assignment 58 may include a portion of a data grouping 56. In other words, for data groupings 56 that are larger in size than the assignments 58, the data grouping will be spread out across multiple document review assignments. In other embodiments, in which a data grouping 56 is smaller in terms of the number of documents or file size than the document review assignments 58, an assignment 58 may include multiple data groupings 56. In other words, for data groupings that are smaller in size than the assignments 58, the document review assignments 58 may include more than one data grouping 56. In addition, since document review assignments 58 may be configured such that each assignment 58 has a finite number of documents, for example 2,000 documents per assignment or the like, it is conceivable that a document review assignment 58 may, in order to account for the finite number of documents, include one or more data groupings 56 in their entirety and a portion of another data grouping 56.
Referring to
The apparatus 130 includes computing platform 22 that can receive and execute routines and applications. Computing platform 12 includes memory 16, which may comprise volatile and non-volatile memory, such as read-only and/or random-access memory (RAM and ROM), EPROM, EEPROM, flash cards, or any memory common to computer platforms. Further, memory 16 may include one or more flash memory cells, or may be any secondary or tertiary storage device, such as magnetic media, optical media, tape, or soft or hard disk.
Further, computing platform 12 also includes processor 14, which may be an application-specific integrated circuit (“ASIC”), or other chipset, processor, logic circuit, or other data processing device. Processor 14 or other processor such as ASIC may execute an application programming interface (“API”) 60 that interfaces with any resident programs, document coding application 18, predictive coding application 26 or the like stored in the memory 66 of the apparatus 110.
Processor 14 includes various processing subsystems 62 embodied in hardware, firmware, software, and combinations thereof, that enable the functionality of apparatus 130 and the operability of the apparatus on a network. For example, processing subsystems 62 allow for initiating and maintaining communications and exchanging data with other networked devices. For the disclosed aspects, processing subsystems 62 of processor 14 may include any subsystem used in conjunction with document coding application 18, predictive coding application 26 or subcomponents or sub-modules thereof.
Computer platform 12 additionally includes communications module 64 embodied in hardware, firmware, software, and combinations thereof, that enables communications among the various components of the apparatus 130, as well as between the other devices in the electronic discovery system. Thus, communication module 64 may include the requisite hardware, firmware, software and/or combinations thereof for establishing a network communication connection.
As previously noted, the memory 16 of computing platform 12 stores document coding application 18, which is executable by processor 14 and configured to receive a document coding input 20 that assigns a review code 22 to a first document 24 associated with a case within an electronic discovery system. In specific embodiments of the invention, the review code 22 includes a mark 66, while in other embodiments of the invention the review code 22 includes a mark 66 and a tag 68, wherein the tag 68 provides a subcategory classification of the corresponding mark 66.
The memory 16 of apparatus 130 additionally includes predictive document coding application 26, which is executable by processor 14 and includes document similarity evaluator 28, code assignor 30 and, optionally document remover 70.
Document similarity evaluator 28 is configured to determine that one or more second documents 32 associated with the case are at least similar to the first document 24. In specific embodiments of the invention, the document similarity evaluator 28 is configured to include hash mark checker 72 that is configured to check the hash mark, such as an MD5 (Message-Digest-algorithm 5) of first 24 and second documents 32 to determine same representations (i.e., identical or near identical) of documents. In other embodiments of the invention, the document similarity evaluator 28 includes similarity probability analyzer 74 that is configured to determine highly similar documents by probability analysis. Thus, similarity probability analyzer may include clustering technique analysis 76, machine learning 77 and/or Bayesian technique analysis 78 and/or a similar probability analysis, each of which may be implemented individually or in combination. In such embodiments, a predetermined threshold 80, such as a word/phrase threshold 82, a concept threshold 84 or the like may be required to be present in the second document 32 in order for it to be deemed highly similar to the first document 24.
In addition, in certain embodiments of the invention, a confidence indicator 86 may be determined for highly similar documents. In specific embodiments the confidence indicator may be a confidence score based on one or more probability analysis, such as clustering technique analysis, machine learning, Bayesian technique analysis or the like. In specific embodiments, the confidence indicator 86 may need to reach or exceed a predetermined confidence threshold in order for a second document 32 to be deemed highly similar to a first document 24 for the purpose of automatically marking the second document with the same review code 22 as the first document 24. In other embodiments, the confidence indicator may be presented to an electronic discovery associate who then makes a determination as to whether the second document(s) 32 reach a level of similarity with the first document 24 in order to provide for the same review code 22.
Code assignor 30 is configured to assign the same review code 22 assigned to the first document to the one or more second documents 32 based on the determination that the second documents 32 are the same representation and/or highly similar. In specific embodiments of the invention the code assignor 30 is configured to automatically assign the same review code 22 assigned to the first document to the one or more second documents 32 based on the determination.
The predictive document coding application 26 may additionally include document remover 70 that is configured to remove the second documents 32 from the pending review documents 88. As previously noted, the pending review documents may be the entire corpus of documents associated with a case, or a portion of the corpus of electronic data associated with a case, such as a document review assignment currently being reviewed by a reviewer or requiring review by an assigned reviewer.
In specific embodiments of the invention, in which the review code 22 associated with the first document 22 is a privileged mark, the predictive document coding application 26 may be applied across other pending cases in the electronic discovery system in which a corpus of collected electronic data exists or will exist. This is because documents that are marked as privileged in one case or matter are consistently privileged across all cases or matters in the electronic discovery system. Thus, once a document is marked as privileged, the predictive document coding application 26 can be executed across all cases or matters in the electronic discovery system to determine identical or highly similar documents in other cases/matters, assign the “privileged” mark as the review code 22 to all of the identical or highly similar documents in all the other cases/matter and remove the documents from the pending review documents file of the related case/matter.
Referring to
In further specific embodiments of the method, the document coding input may be received from an electronic discovery associate, such as a case analyst, prior to assigning document review assignments to reviewers. In such embodiments, the electronic discovery associate may review and code a small subset of the overall corpus of electronic data associated with the case and subsequently identical or highly similar documents are determined and pre-coded from the overall corpus of electronic data.
In other specific embodiments of the method, the document coding input may be received from a document reviewer during the document review process. In such embodiments, once a document coding input is received, identical or highly similar documents are determined and pre-coded from the documents assigned to the reviewer.
In still further embodiments of the method, the document coding input may be received by a primary document reviewer or a secondary document reviewer. In certain instances, the secondary document reviewer is employed, in addition to the primary document reviewer, to provide verification/confirmation of the initial coding of the document by the primary document reviewer. Thus, in certain embodiments of the method, the determination of identical and/or highly similar documents is made after the secondary document reviewer makes the document coding input. While in other embodiments of the method, in which a secondary document reviewer is not employed, the determination of identical and/or highly similar documents is made after the primary document reviewer makes the document coding input.
At Event 94, one or more second documents associated with the case are determined to be at least similar to the first document. In specific embodiments, the second documents are determined to be the same representation, (e.g., identical or near identical) as the first document. In such embodiments a comparison of hash values may be undertaken to determine the same representation. In other embodiments of the method, the second documents are determined to be highly similar by implementing probability analysis, such as clustering techniques, machine learning, Bayesian techniques or the like. In further such embodiments predetermined thresholds of words, phrases and or concepts may be required to be included in the second document in order for the second document to be deemed highly similar to the first document. Moreover, in other embodiments, determination of the one or more second documents may include determination of a confidence indicator, which may serve to sum the probability analysis of multiple probability analysis techniques or the like.
At Event 96, the review code assigned to the first document is assigned to the one or more second documents based on the determination that the second documents are similar to the first documents. In specific embodiments of the method, the assignment of the review code is automatic based on the determination. In still further embodiments the assignment of the review code to the second documents occurs in near real-time to the receipt of the document coding input. Additionally, the method may include removing the second documents from either the corpus of electronic data in which review is outstanding or the document review assignment from which includes the first document or both.
Referring to
At Event 95, a plurality of data groupings are determined from a corpus of case-related electronic data. Each of the data groupings are defined by inclusion of at least one of the predetermined concepts. In specific embodiments of the invention the data groupings are determined by implementing conceptual clustering techniques or some analytical technique that identifies data groupings based on predetermined concepts within a grouping.
At Event 97, a plurality of document review assignments are generated based on the determined data groupings. In certain embodiments of the invention, document review assignments include a finite number of documents, for example approximately 2,000 documents or the like. In specific instances, in which a data grouping is larger in terms of documents or file size than a document review assignment, one or more document review assignments will include a portion of a data grouping (i.e., multiple document review assignments will include the same data grouping. In other specific instances, in which a data grouping is smaller in terms of documents or file size than a document review assignment, document review assignments may include more than one data grouping. In addition, in instances in which the document review assignments include a consistent finite number of documents, a document review assignment may include one or more complete data groupings and a portion of another data grouping.
At optional Event 99, the plurality of document review assignments are assigned to a plurality of document reviewers, such that assigning of document review assignments is based on associated data groupings. In specific embodiments of the method two or more document review assignments that include a portion of the same grouping are assigned to a same document reviewer.
As a means of providing an overview of a composite, enterprise-wide electronic discovery system, which may be implemented in conjunction with the computer monitoring of network status described above,
As shown in the block diagram of
Referring again to
Regardless of the number of database servers employed, it is an object of embodiments of the present invention that data relating to custodians and cases be stored in the database server 120 independently. While custodian data in the Unified Directory 122 and case data in the case database 124 may be linked or correlated within the database server 120, for example, when custodians are assigned to particular cases, custodians may be managed separately from cases. Therefore, when a case is initialized and a custodian is assigned to the case, information for that custodian (such as data storage locations for that custodian) is accessed by the electronic discovery management server 110 in the Unified Directory 122 in the database server 120 and linked to the particular case, rather than manually input by the e-discovery manager into the case.
Furthermore, in addition to separating (but allowing linkage of) custodian management and case management processes, and as discussed further below, data management processes relating to the collection of data from custodian storage locations during electronic discovery are also separated from case management and custodian management processes. In this regard, the data collected from a particular custodian is stored separately from both the custodian information and any relevant case information (as discussed below, it is stored in long-term network storage network 190), but is linked to a custodian, which is in turn linked to one or more cases. This is advantageous because in the event a particular custodian is assigned to multiple cases, data collected from the custodian may be shared with the other case(s) to which the custodian is assigned. Therefore, the various processes and components of the electronic discovery system 100 may be categorized within one of case management, custodian management, or data management. And even though cases, custodians, and collected data may all be managed separately, there are necessarily links between the various datastores to allow management of the overall electronic discovery process.
Custodian
With regard to custodian management, according to some embodiments of the present invention, the Unified Directory/custodian database 122 houses information relating to all potential custodians within the enterprise and the locations where those custodians store data. The information stored in the Unified Directory 122 may include for a particular custodian, for example, the custodian's name, position, human resources identifier (a unique number for each employee of the enterprise), employment location, domain, email addresses, network user identification, personal computer(s) name, paths of network storage devices used by the custodian, including Shared Drives and HomeSpaces, work history, related persons (such as managers, team members or subordinates), and any other information that may be relevant to the discovery process. Since the human resources identifier is always unique for each custodian, in some embodiments, the Unified Directory 122 may be organized around the human resources identifier. All of the information relating to how the Unified Directory 122 is generated is a multi-step process that utilizes multiple applications and methods of identifying relevant information.
For example, the electronic discovery management server 110 or the database server 120 may interface with the computer databases of the human resources computer systems of the enterprise to copy the information from the human resources databases into the Unified Directory 122. In some embodiments, the electronic discovery management server 110 may also reach out to a network directory, such as Windows Active Directory, to identify network resources related to particular custodians and integrate this information into the custodian entries including the copied human resources information. Information for the Unified Directory 122 may also be obtained from the managers of the information technology network, i.e., those individuals responsible for setting up email accounts for custodians and managing the various file servers of the enterprise. Furthermore, in addition to retrieving information in the manners described above, in some embodiments, information in the Unified Directory 122 is generated through applications initialized and/or deployed by the electronic discovery management server 110. In particular, in some embodiments, as shown in
The profile scanning application 112 may be deployed by the electronic discovery management server 110 and is configured to crawl the communication network 102, scan each of the enterprise personal computers 140, and transmit to the database server 120 identifying information about each computer, such as computer name and IP address, and a list of all profiles, including demographics information, (or network user identification) associated with each computer. According to different embodiments, the profile scanning application 112 may be run on the electronic discovery management server 110, the collection server 130, or another server in the communication network 102. In some embodiments, the profile scanning application 112 is further configured to identify and transmit to the database server 120 the most recent date and time at which a particular profile was logged on to the machine. When information relating to a particular computer is received by the database server 120, the database server 120 uses the profile information, which may include several user identifications, to link the particular computer to the custodians in the Unified Directory 122 associated with those user identifications. The database server 120 may also record in each custodian's entry in the Unified Directory 122 the last time the computer was accessed by the custodian, according to the profile information transmitted by the profile scanning application 112. Thus, the profile scanning application 112 ultimately generates a list of personal computers used by each custodian, and this list may be presented to the e-discovery manager when a collection of a custodian's local machine(s) is initialized, as discussed in detail below.
In accordance with some embodiments of the invention, the mapping application 114 is configured to crawl the communication network 102 and examine the enterprise file servers 150 residing on the communication network 102 to locate and identify the path of any personal network storage area on each server. As used herein, a personal network storage area is a network storage area associated with a single user who reads data from or writes data to it. Personal network storage areas may be in the form of network storage devices or folders or other resources within a network storage device and may be referred to hereafter for clarity purposes as “HomeSpaces.” According to different embodiments, the mapping application 114 may be run on the electronic discovery management server 110, the collection server 130, or another server in the communication network 102. In some embodiments, the mapping application 114 is a Windows service that is scheduled to execute through use of Windows Scheduled Task. As the mapping application 114 crawls the communication network 102, it is configured to examine each file server and transmit to the database server 120 the path of any network storage area within the plurality of servers 134 that it positively identifies as a HomeSpace. In some embodiments, the mapping application 114 is configured to explore the enterprise file servers 150 by obtaining and reviewing the directories on each server and evaluating the paths of each network storage area therein, including folders and other storage devices and resources.
With regard to identifying a particular network storage area as a HomeSpace, according to some embodiments, the mapping application 114 is configured to utilize conventional naming techniques for paths in the communication network 102 to identify those paths of network storage areas within the enterprise file servers 150 that include an indicator, based on the conventional naming techniques, that the particular storage areas associated with those paths are accessed and used by only one user, and are therefore HomeSpaces. In accordance with some embodiments of the invention, each user of the communication network 102 is assigned to at least one user identification and those user identifications are the indicators that the mapping application 114 attempts to locate within paths when identifying HomeSpaces. In such embodiments, it is the convention that the paths of HomeSpaces on the communication network 102 include the user's user identification. On the other hand, paths of shared network storage areas do not include user identifications. Therefore, the mapping application 114 may explore the directories of each server within the plurality of servers, evaluate each path in turn, and make a determination as to whether or not the path includes a user identification.
If it is determined that the path includes the designated indicator, for example, a user identification, the mapping application 114 is configured to positively identify the particular network storage area identified by that path as a HomeSpace and transmit to the database server 120 the particular user identification and the path of the HomeSpace. When that information is received by the database server 120, the database server 120 uses the user identification to link the particular HomeSpace to the custodian in the Unified Directory 122 associated with that user identification. In some embodiments, the mapping application 114 is also configured to recognize and transmit, and the database server 120 is configured to house, an indication of the last time the HomeSpace was accessed by the particular user, for example, the last time any data was read from and/or written to the HomeSpace. Additionally, in some embodiments, the mapping application 114 is configured to recognize when multiple paths map to the same network storage area. The collection server 130 compares paths for the same user to determine if duplicative entries exist. This advantageously enables avoidance of multiple collections of the same data. Thus, the profile scanning application 112 ultimately generates a list of HomeSpaces used by each custodian, and this list may be presented to the e-discovery manager when a collection of a custodian's HomeSpaces is initialized, as discussed in detail below.
In addition to storing a list of personal computers and HomeSpaces used by a particular custodian, which lists were generated by the profile scanning application 112 and the mapping application 114 respectively, in accordance with some embodiments of the present invention, the database server 120 is also configured to store a list of any shared network storage areas used by the custodian. As used herein, a shared network storage area is a network storage area associated with multiple users who read data from and/or write data to it. Shared network storage areas may also be in the form of network storage devices or folders or other resources within network storage devices and may be referred to hereafter for clarity purposes as “Shared Drives.” The user interface 118 is configured to receive a path of a Shared Drive input by the e-discovery manager and store the path in the Unified Directory 122 in relation to one or more custodians' human resources identifier(s). More particularly, in some embodiments, once a particular user of the communication network 102 is chosen for the collection process, the e-discovery manager may undertake to identify the particular shared network resources that that individual is using, and eventually, the paths associated with those shared network resources. This may be accomplished through conversations with the particular individual, by utilizing data returned from the local collection application 132 executed on collection server 130 (shown in the block diagram of
According to some embodiments of the present invention, the file browsing application 116 is configured to be utilized by the e-discovery manager through the user interface 118. The file browsing application 116 gives the e-discovery manager elevated authority within the communication network 102 to access, in a limited manner, the enterprise file servers 150 within the communication network 102. While the file browsing application 116 may not allow access to the actual files stored on certain file servers, it allows the e-discovery manager to browse through the directories of the file servers 150, locate files that have been accessed by the custodian, and determine the size of the files. In accordance with some embodiments, the e-discovery manager may initially have a general idea of a particular file server within the enterprise file servers 150 that the custodian has used in the past. For example, the custodian may communicate to the e-discovery manager a particular folder name and/or drive name on which he/she has stored files. Additionally, in some embodiments, the e-discovery manager may have already undertaken a local collection process on the custodian's machine, wherein the local collection application 132 returned a list of the network resources that the user of that machine has used. In that event, the e-discovery manager may be aware of the particular drive referenced by the user. The e-discovery manager may then employ the file browsing application 116 to browse out to the particular drive mentioned, scan the folders for any folder having a name resembling that name given by the user, identify any particular files created by and/or accessed by the user, determine the size of such files, and retrieve the path of any folder (or Shared Drive) including data belonging to the user.
The retrieved paths of the Shared Drives may then be added, either manually or automatically, to the Unified Directory 122 in the database server 120. Thus, the Unified Directory 122 may store in connection with one custodian (and in particular in relation to the custodian's human resources identifier) a list of the personal computers, HomeSpaces, and Shared Drives associated with that custodian. Each of these locations is a potential source of data stored by the custodian, and once an investigation or collection of a custodian is initiated, the location information stored in the Unified Directory 122 may be accessed to determine the particular storage locations that need to be addressed during the investigation/collection. This is advantageous as it allows a completely automated investigation/collection process, rather than relying on the e-discovery manager to manually input the targeted machines and file servers at the time of collection.
It should be noted that the Unified Directory 122 may be regularly or continuously updated as new information is gathered using the applications described herein. More particularly, the electronic discovery management server 110 may be configured to automatically retrieve data from the human resources databases and Active Directory and any other relevant sources, such as information technology directories or lists, as well as deploy the profile scanning application 112 and the mapping application 114, at regularly scheduled intervals. Alternatively, rather than periodically retrieving data from the various data sources such as the human resources databases, the system 100 may be configured such that the database server 120 is continuously interfacing with the data sources such that the Unified Directory 122 is updated in real-time as the data within the data sources update. In either instance, each of the feeds of information into the Unified Directory 122 is regularly updated to ensure that the data in the Unified Directory 122 is current.
In some embodiments, the database server 120 is configured such that all historical data relating to a custodian is stored in relation to that custodian's human resources identifier in the Unified Directory 122. Thus, when the feeds of information into the Unified Directory 122 are updated, in the event data relating to the custodian has updated, the database server 120 is configured to store in the Unified Directory 122 the new data and any relevant metadata, including, for example, the time and date of the update, as well as maintain a record of the old data so that it is still a part of the custodian's profile in the Unified Directory 122. For example, in the event the profile scanning application 114 identifies a new personal computer associated with a custodian and one of the personal computers associated with the custodian previously is no longer identified, the database server 120 is configured to store in the Unified Directory 122 the information for each computer, as well as indications as to when the new computer was first identified and when the old computer was no longer identified. In this way, the custodian profile within the Unified Database 122 may include a history of the personal computers used by the custodian. Such information may be relevant at the time of investigation or collection of the custodian.
One feed of information into the Unified Directory 122 which is particularly relevant to electronic discovery is employment status. According to some embodiments, when the feed of information from the human resources databases to the Unified Directory 122 includes an update as to employment status of a particular custodian, the electronic discovery management server 110 is configured to recognize the update and possibly perform particular functions in response. More specifically, in the event it is recorded in the Unified Directory 122 that the employment status of a particular custodian updates from active to terminated, the electronic discovery management server 110 is configured to determine whether the custodian is assigned to any case or matter, and, if so, to transmit to the designated manager or contact for the case or matter an electronic communication notifying the manager of the terminated status and inquiring as to whether the manager would like the terminated custodian's data collected. In the event the manager responds in the affirmative, the electronic discovery management server 110 is configured to automatically initiate the various collection processes of the present invention. Therefore, the custodian's data may be advantageously collected prior to any destruction or unavailability that could be caused by the termination. Alternatively, in other embodiments, the electronic discovery management server 110 may not communicate with the manager and may automatically initiate collection upon recognizing an update in employment status.
Case
With regard to case management processes, according to some embodiments, a case may be initialized by the e-discovery manager utilizing the user interface 118. In this regard, the e-discovery manager may enter into the user interface 118 certain information about a particular matter or case, such as a case name and/or number, a short description of the matter/case, a legal identifier, the particular requester (i.e., who asked for the case to be opened), managers or contacts for the matter (i.e., individuals involved in the substance of the matter rather than the process, like the e-discovery manager), custodians, etc. The electronic discovery management server 110 is configured to store this information in the case database 124 in the database server 120. The case database 124 is configured to house this information such that all information relating to a particular matter or case is related within the case database 124 and a user can use the user interface 118 to view a profile of the matter or case including all the information.
Once the matter and/or case has been initialized, the e-discovery manager may add custodians to the matter or case. In some embodiments, the electronic discovery management server 110 is configured to add numerous custodians to a single matter or case at one time. In this regard, the e-discovery manager may use the user interface 118 to enter in identifying information about the custodians. The identifying information for each custodian does not have to be of the same type. For example, a name may be entered for one custodian, an email address for another, a network user identification for another, and a human resources identifier for another. The user interface 118 is configured to receive the identifying information in different input areas depending upon the type of identifying information being received. The electronic discovery management server 110 is configured to use the input information to search the Unified Directory 122 in the database server 120 to determine which custodians are associated with the input information. In the case of a human resources identifier being entered, only one custodian in the Unified Directory 122 may be a match. On the other hand, in the case of a name being entered, multiple custodians may be a match.
The electronic discovery management server 110, after searching the Unified Directory 122 with the input identifying information, is configured to present through the user interface 118 a list of all custodians matching the input identifying information. In the event only one match was returned for a particular set of input identifying information, the electronic discovery management server 110 is configured to automatically select the custodian to be added to the case or matter. On the other hand, in the event more than one match was located for a particular set of input identifying information, then the multiple matches may be presented together to the e-discovery manager through the user interface 118 and marked so that the e-discovery manager must review the multiple custodian profiles associated with the matches to determine the correct custodian that should be added to the case or matter. In doing so, the e-discovery manager may consider the other information in the profiles, such as corporate title, work location, associated custodians, etc. Such information can inform the e-discovery manager as to whether the located custodian is the one intended. The e-discovery manager may then select the correct custodian for addition to the case or matter and confirm that all custodians selected may be added to the case or matter. According to some embodiments, “adding” a custodian to a case or matter involves linking correlating the custodian profile in the Unified Directory 122 to the case or matter in the Case database 124.
According to some embodiments, upon adding custodians to a matter, the electronic discovery management server 110 is configured to initiate the transmission of preservation notices and surveys to the custodians. In this regard, preservation notices and surveys relevant to the particular case or matter are stored in or linked to the case profile in the case database 124. Transmission of the preservation notices and surveys to custodians added to the case may be automated, for example, there may be preset instructions within the case profile that cause the electronic discovery management server 110 to transmit a particular preservation notice and survey at a particular date or time or upon a particular initiating event, such as a custodian being added to the case, or the e-discovery manager may manually cause the preservation notices and surveys to be transmitted. In some embodiments, the electronic discovery management server 110 is configured to transmit the preservation notices and surveys via a standard email function. The surveys may be tied to the preservation notices such that they are transmitted to custodians together, and one survey may be tied to more than one preservation notice. When a custodian responds to a survey, the survey response is received by the electronic discovery management server 110 and stored in relation to the relevant custodian in the case profile in the case database 124. Furthermore, the electronic discovery management server 110 may be configured to store all or a portion of the data received in the survey response in the Unified Directory 122 in the custodian's profile.
According to some embodiments, each transmission of a preservation notice and survey to a custodian, and each corresponding response, is tracked in the relevant case profile in the case database 124. The electronic discovery management server 110 may also be configured to transmit reminder notices if responses to the surveys are not received within a predefined period of time. The electronic discovery management server 110 may also be configured to schedule reminder notices to be sent to custodians to periodically refresh the custodians' memory of their duty to preserve files/documents pertaining to the matter. In some embodiments, once a preservation notice has been sent to a custodian, the electronic discovery management server 110 may undertake to prevent any reimaging or refreshing of the custodian's personal computer(s) by transmitting an alert of the preservation notice to the enterprise's information technology management group. In addition, the survey responses received from custodians serve to inform the collection process. For example, one survey may inquire as to what network storage devices the custodian uses when storing data. The answer that the custodian gives to the survey may inform the addition of Shared Drives to the custodian profile in the Unified Database 122 that may be used later in collection.
According to some embodiments of the present invention, the e-discovery manager may utilize the user interface 118 to add attachments, notes, tasks, and search terms to a case or matter. In some embodiments, the contacts/managers for a case may also access the case profile in the case database 124 using a web browser and may add attachments, notes, tasks, and search terms to be stored therein. Thus, the e-discovery manager may not be the only entry with access to the case and case management applications of the electronic discovery management server 110. The subject matter of the attachments, notes and tasks could be anything relevant to the case or matter. In some embodiments, the tasks are tasks that particular custodians must complete and the electronic discovery management server 110 is configured to transmit a notice to the custodians that that the task needs to be completed, perhaps using standard email functions. With regard to attachments, the e-discovery manager, or the contact/manager of the case, may upload relevant files to be attached to the case profile.
With regard to the search terms, the e-discovery manager or the case contacts or managers may add certain terms to the case profile to be applied when searching the collected data to locate data responsive or relevant to the underlying issues in the case. Storing the search terms within the case profile is advantageous as it creates a record of the searching that is to be undertaken with respect to the data and aids in organization of the data, as discussed further below.
According to some embodiments of the present invention, when a decision is made that it is time to collect from certain custodians in a matter, the e-discovery manager may use the user interface 118 to release the custodians from the matter to the underlying case. This release triggers the commencement of collection of the custodians' data. In some embodiments, the electronic discovery management server 110 is configured to allow all custodians assigned to the matter to be released to the case at the same time. In addition, in instances where the e-discovery manager has previously created groups of custodians within the case, the electronic discovery management server 110 is configured to allow a group of custodians to be released from a matter to a case at the same time.
Data
Once a custodian has been identified for collection, whether manually by the e-discovery manager or by being released from a matter to a case, the electronic discovery system 100 is configured to automatically collect the custodian's data using the location information stored in the Unified Directory 122. Therefore, the electronic discovery management server 110 accesses the custodian profile of the custodian to be collected in the Unified Directory 122 and determines, from the information stored therein, the different locations of data storage for the particular custodian that must be collected. There are many different locations that the system 100 can address, including personal computers, email accounts, and network storage areas, including HomeSpaces and Shared Drives.
If a custodian profile (for a custodian released for collection) includes at least one personal computer(s) associated with the custodian, then the electronic discovery management server 110 may undertake to collect the files on these machines. Therefore, the electronic discovery management server 110 may retrieve the relevant machine identifying information, such as domain, name, IP address, etc., and may initialize deployment of a local collection application 132 running on collections server 130 (as shown in
The local collection application 132 is configured to be deployed from the collections server 130 or another server within the network 102 to any of the enterprise personal computers 140. Therefore, for a particular custodian, the local collection application 132 is configured to utilize the machine identifying information supplied by the electronic discovery management server 110 to be deployed to the identified custodian computer. According to one embodiment, the local collection application 132 is configured to be automatically installed on the target custodian's personal computer. The local collection application 132 is further configured to generate a snapshot of the data residing on the local storage of the personal computer 140, for example, by using a commercially available application such as the Volume Shadow Copy Service, store the snapshot in a storage area on the personal computer, and transmit copies of the files included in the snapshot to the collections server 130. By transmitting the data from the snapshot of the data stored on the hard drive of the personal computer, the local collection application 132 advantageously allows the custodian to continue to use her machine without substantial interference from the local collection application 132 and even interact with the data stored on the hard drive as the snapshot of the data is being transmitted to the collections server 130.
In addition to the functions described above, the local collection application 132 may also be configured to transmit to the database server 120 a catalog of the files included in the snapshot to be stored in the ongoing collections database. This catalog may be referenced by the collections server 130 in order to determine whether collection is complete and to resume interrupted collections at the point of interruption. Additionally, in accordance with some embodiments, the local collection application 132 is configured to compile and transmit to the electronic discovery management server 110 a list of network resources the user is using, including, for example, network applications and file servers that the user has used or accessed. This list of resources may be stored in the database server 120 in the custodian's profile in the Unified Directory 122. With regard to transmission of the files themselves, according to one embodiment of the invention, the local collection application 132 is configured to compress, hash, and upload the files included in the snapshot to the collections server 130.
In some embodiments, the electronic discovery management server 110 may utilize a computer monitoring application 117 to determine when to attempt a collection from a custodian's machine. The computer monitoring application 117 is configured to monitor the network 102 and determine which of the enterprise personal computers 140 are online. Therefore, in the event there is a custodian whose local machine needs to be collected, the computer monitoring application 117 is configured to determine when that machine joins the network 102 (i.e., when it appears to the computer monitoring application 117) and inform the electronic discovery management server 110 that it should initialize the local collection application 132 immediately.
If a custodian profile (for a custodian released for collection) includes any paths for HomeSpaces or Shared Drives, then the electronic discovery management server 110 may undertake to collect the files from these file servers by initializing the file server collection application 134 running on collection server 130 (as shown in
If a custodian profile (for a custodian released for collection) includes an email address for an email account on the enterprise email server 160, then the electronic discovery management server 110 may undertake to collect the files from the enterprise email server 160 by initializing the active email collection application 136 running on collections server 130 (as shown in
Regardless of the storage resource location from which data is being collected, or the particular type of data being collected, the collections server 130 is configured to store the data first (while the collection is still ongoing) in the short-term staging drive 180 until the particular collection is complete, attach a barcode to the set of data resulting from the particular collection, and then copy the data set to the long-term storage area network 190 for permanent storage. Furthermore, the collections server 130 transmits the barcode information to the electronic discovery management server 110 to be stored in the database server 120, for example, in the custodian's profile in the Unified Database 122, in relation to the stored information about the particular collection, whether it was a local collection, an active email collection, a file server collection, etc. Therefore, the barcode can be used for reference at a later date to determine the origin of the data. After the data has been copied to the long-term storage area network 190, the collections server 130 compares the hashing of the data in permanent storage to the original data in the staging drive 180 and, if the hashing is identical, purges the data from the staging drive 180.
Once the data has entered the long-term storage area network 190, it is not necessarily ready for review. Indeed, it is likely that the data may need to be processed before it is searchable and suitable for review by investigators and attorneys. For example, the files may be encrypted in the form in which they are collected and sent to the long-term storage area network 190. Therefore, according to some embodiments, the data may be copied to the conversion services server 170 where a series of decryption and standardization functions may be applied to it. After the data is decrypted and standardized, it is returned to the long-term storage area network 190 and may remain there to be accessed for review purposes.
With reference now to
The first process that falls within the case management category is creation of a matter or case as a framework for litigation support activities, as shown in Block 202. As described above, the e-discovery manager may enter into the user interface 118 certain information about a particular matter or case, such as a case name and/or number, a short description of the matter/case, a legal identifier, the particular requester (i.e., who asked for the case to be opened), managers or contacts for the matter (i.e., individuals involved in the substance of the matter rather than the process, like the e-discovery manager) etc.
It is noted that custodian information is stored separately from the case information allowing for the same custodian in multiple cases. This provides for the electronic discovery system of the present invention to have scalability, whereby evidence associated with one custodian may be used in multiple cases.
The electronic discovery management server 110 stores this information in the case database 124 in the database server 120. The case database 124 houses this information such that all information relating to a particular matter or case is related within the case database 124 and a user, such as a manager or contact, can use the user interface 118 to view and edit a profile of the matter or case.
The next process within case management is the creation of preservation notices and surveys specific to the matter, as shown in Block 204. In this regard, the e-discovery manager may, through the user interface 118, either generate a new preservation notices or surveys relevant to the particular case or matter to be stored in the case profile in the case database 124 or, alternatively, link a preservation notice or survey already stored in the database server 120 to the case profile of the specific case or matter at issue. Also within case management is the creation of search terms pertinent to the case, as represented by Block 206. As described above, the e-discovery manager or a contact or manager for the case may use the user interface 118 to input individual search terms or search term sets to be applied to the data harvested in the case. In some embodiments, the search terms may be limited to be used with particular custodians and/or with particular harvested data types. The search terms will be saved in the case database 124 so that they may be readily applied to harvested data and used in connection with storing the resulting responsive data.
The processes of entering relevant attachments, notes and updates to a particular case or matter also falls within the case management category, as demonstrated by Blocks 208 and 210. The e-discovery manager or a case contact or manager may use the user interface 118 to upload documents and enter notes and other relevant data, including updates and reminders, to be stored in the case profile of the case in the case database 124. Once these attachments, notes and updates are added, they may be referenced whenever a user views the case profile through the user interface 118. The cost estimation modules of the present invention are also processes that are categorized as case management processes, as shown in Block 212. In this regard, the electronic discovery management server 110 utilizes a cost estimation application to determine the cost of harvesting and reviewing data, based on a number of factors including, for example, number of custodians, amount of harvested data, data types, etc. Finally, case management also includes a number of tasking and workflow processes that are represented by block 214.
Moving now to custodian management, certain processes falling within the category of custodian management are shown in Block 220. While the processes involving generation of the Unified Directory 122 certainly could be categorized as custodian management, the processes shown in
Also falling within custodian management is the process of releasing custodians from a matter to a case, as shown in Block 228. The e-discovery manager uses the user interface 118 to mark the custodian's profile so that the custodian is now activated for collection of data. This may occur within the case database 124 since the custodian's profile is linked thereto. Once the custodian is released/marked, the electronic discovery management server 110 may access the custodian's profile and initialize collection based on the various data storage locations identified in the profile. Therefore, as represented by Block 230, the electronic discovery management server 110 may automatically determine the data types and locations of data to be harvested by accessing the custodian's profile in the Unified Directory 122. Alternatively, the e-discovery manager may manually make the same determination by accessing and viewing the custodian's profile. Finally, as with case management, custodian management also includes a number of tasking and workflow processes that are represented by Block 232.
The last category is data management, represented by Block 240. One major set of processes within data management are the processes relating to the harvesting of data, as shown in Block 242. These processes include the collection of data from all the different storage areas of a particular custodian, including the custodian's local storage on her personal computer(s), the custodian's network storage areas, the custodian's email, and any other areas, as are described herein. All of the data in the various storage areas is copied and transmitted to the collections server 130, as described in detail for each particular collection application or process. Upon reaching the collections server 130, data resulting from a particular collection is temporarily stored in the short-term staging drive 180 until the collection is complete, at which point it is stored in the long-term storage area network 190 in association with a specific identifying barcode. The foregoing process is represented by Block 244. The data may require decryption or standardization functions to be applied to it in order for it to be searchable and/or otherwise usable, so the next process that falls within data management is the copying of the data to the conversion services server 170 for analysis and conversion as necessary, as shown in Block 246. Once the data is converted, it is returned to the long-term storage area network 190 to be used in review.
Also falling within data management is the association of particular data sets with particular sets of search terms stored in the case profile of the case database 124. In this regard, certain search terms stored in the case profile are stored with the intention of being applied to certain types of data and/or certain custodian's data. Alternatively, certain search terms may be applied to all data collected for a specific case. In either instance, the electronic discovery management server 110 accesses the case profile, determines the search terms to be applied, and associates the search terms with the barcode of the appropriate data sets in long-term storage. Thus, the search terms will be applied to that data and the results will be generated and presented to reviewers for analysis. Finally, as with the other management categories, data management also includes a number of tasking and workflow processes that are represented by Block 250.
With reference to
The preservation notice, as shown in Block 314 is transmitted to the custodians added to the matter, perhaps using email. As shown in Block 316, a reminder notice module may be employed. As shown in Block 318, the reminder notice module transmits periodic reminder notices to custodians. The notices may be sent over email and may remind custodians about the preservation notice and/or remind custodians to fill out surveys. With regard to surveys, in the event a survey is required or desired, according to Block 320, a survey is created. The survey may be saved in the case profile in the case database 124. As shown in Block 322, it is possible to enable the survey to be attached to and transmitted with the preservation notices.
Next, as shown in Block 324, the e-discovery manager may release custodians from the matter to the case, which initialized collection of the custodian's data. As shown in Block 326, the e-discovery manager or the electronic discovery management server 122 accesses the custodian profile, determines the data types and location to be collected, and initializes the applicable collection applications to go collect the data. Once the data has been collected and a unique barcode has been assigned to each dataset based on the particular custodian and storage location from which it originated, as shown in Block 328, the search terms previously stored in the case profile may be assigned to the dataset based on the input instructions regarding the search terms. These search terms may be applied to the dataset and the results saved to be presented to reviewers for analysis.
With reference to
As represented by Block 406, the electronic discovery management server 110 may determine whether the particular custodian added is a member of the enterprise “do-not-call list.” In this regard, there may be an indication in the custodian's profile in the Unified Directory 122 that the particular custodian should not be contacted regarding collections, and an alternative contact should be used, such as an administrative assistant of the custodian. Alternatively, there may be a separate do-not-call list stored in the database server 120 that must be accessed and searched to determine whether or not the custodian appears on that list. In either instance, a determination is made as to whether or not the custodian should be directly contacted, and in the event the custodian should not be directly contacted, the contact information for the custodian's assistant (or other stand-in) should be obtained. This information will be used later for transmitting preservation notices and surveys.
Next, in accordance with Block 408, a determination is made by the electronic discovery management server 110 as to whether the custodian has been added to a matter or a case. If it is a case, then the custodian is verified, as shown in Block 424, supplemental data may be added to the custodian profile in the Unified Directory 122 as required, as shown in Block 426, and then the various collection applications are initialized by the electronic discovery management server 110 for collection of the custodian's data, as shown in Block 428. On the other hand, if it is a matter, then preservation notices are required. Therefore, as shown in Block 410, a preservation notice is sent via email to the custodian or custodian stand-in. As shown in Block 412, the custodian may then be inactivated from the case because, for some reason, data does not need to be collected from the custodian. In the future, when it comes time to collect from the custodian, the custodian will be reactivated, as shown in Block 422.
After a preservation notice is sent, a determination is made by the electronic discovery management server 110 as to whether a survey is required, as shown in Block 414. It should be noted that in alternate embodiments the decision on whether to send a survey may be made prior to sending the preservation notice. In such alternate embodiments, if the survey is required, it may become a component of the preservation notice and, thus, accessed simultaneously by the custodian. If a survey is required, it is transmitted in conjunction with a preservation notice, and the answers are collected by the electronic discovery management server 110 and stored in the database server 120, as shown in Block 416. Reminder notices for the preservation notices and surveys may also be transmitted to the custodian, as shown in Block 420. Next, once it is time to collect data, the custodian is released from the matter to the case, as shown in Block 418, and the various collection applications are initialized by the electronic discovery management server 110 for collection of the custodian's data, as shown in Block 428. In this process, the custodian's profile in the Unified Directory 122 is accessed in order to determine the various locations where the custodian may have stored data. Finally, as shown in Block 430, the custodian's data is collected.
Referring to
At Event 510, a barcoding application is implemented at a staging location, such as short-term staging drive (180) to attach a barcode to the set of email resulting from the particular collection. The barcoded data is then copied and communicated to the long-term storage area network (190) for permanent storage. Furthermore, the collections server (130) transmits the barcode information to the electronic discovery management server (110) to be stored in the database server (120), for example, in the custodian's profile in the Unified Database (122), in relation to the stored information about the particular collection. Therefore, the barcode can be used for reference at a later date to determine the origin of the data. After the data has been copied to the long-term storage area network (190), the collections server (130) compares the hashing of the data in permanent storage to the original data in the staging drive (180) and, if the hashing is identical, purges the data from the staging drive (180). As such, barcoding is performed without the need to execute the barcoding application on an exchange server and, as such no human intervention is needed in the barcode process. In accordance with embodiments of the present invention, one barcode may be assigned per custodian, per data type and per event (i.e., case, matter, etc.)
At Event 512, the collected email data may be associated with a specific search term set or sets. When the search terms are applied, a listing of the files and documents including those terms (the “search term hit list”) are presented to the reviewer and also stored in the database server (120). The reviewer may provide an indication of this to the electronic discovery management server 110, which may then make a determination that other documents within the search term hit list are more likely to be responsive.
At Event 514, the collected and barcoded active email data is copied to a processing drive for subsequent analysis. It should be noted that the nature of email data obviates the need to perform conversion and/or decryption on the data set. At Event 516, the active email data set is loaded into the analysis application and, at Event 518, the data set is exported to the requestor/reviewer for analysis.
Data Block 520 signifies other non-exchange server based email, such as email accessed through a client-server, collaborative application, such as Lotus Notes® or the like. At Event 522, NSF files or any other file types associated with non-exchange server based email is manually harvested from an enterprise-grade email server having collaborative capabilities, such as a Lotus Domino server or the like.
At Event 522, a barcoding application is implemented at a staging location, such as short-term staging drive (180) to attach a barcode to the set of non-exchange server email resulting from the particular collection. The barcoded data is then copied and communicated to the long-term storage area network (190) for permanent storage. Furthermore, the collections server (130) transmits the barcode information to the electronic discovery management server (110) to be stored in the database server (120), for example, in the custodian's profile in the Unified Database (122), in relation to the stored information about the particular collection. Therefore, the barcode can be used for reference at a later date to determine the origin of the data. After the data has been copied to the long-term storage area network (190), the collections server (130) compares the hashing of the data in permanent storage to the original data in the staging drive (180) and, if the hashing is identical, purges the data from the staging drive (180).
At Event 526, the collected non-exchange server email data may be associated with a specific search term set or sets. When the search terms are applied, a listing of the files and documents including those terms (the “search term hit list”) are presented to the reviewer and also stored in the database server (120). The reviewer may provide an indication of this to the electronic discovery management server 110, which may then make a determination that other documents within the search term hit list are more likely to be responsive.
At Event 528, the NSF files or any other file types associated with non-exchange server based email that may be encrypted is decrypted using a decryption application, in accordance with embodiments of the present invention. The encryption of NSF files occurs at the user level and, therefore only the user has the password necessary for decryption. The decryption application allows for decryption of the NSF file-type data without the knowledge of the user/encrypter. The decryption application finds ID files that exist anywhere in the enterprise system, creates a database of the ID files, associates the database with the user/encrypter and subsequently decrypts the data.
At Event 530, the non-exchange server email data set is loaded into the analysis application and, at Event 532, the data set is exported to the requestor/reviewer for analysis.
Data Block 534 signifies journaled data, such as electronic commerce data stored on a repository for the purpose of regulation, compliance to regulating bodies, such as the Securities and Exchange Commission (SEC) or the like. At Event 536, criteria is extracted from input system and manually entered in a designated third party system for data retrieval.
At Event 538, the barcoding application is implemented at a staging location, such as short-term staging drive (180) to attach a barcode to the set of journaled data resulting from the particular collection. The barcoded data is then copied and communicated to the long-term storage area network (190) for permanent storage. At Event 540, the collected and barcoded journaled data may be associated with a specific search term set or sets.
At Event 542 source-to-processing is implemented to insure that any loose files are properly formatted in a standardized format. In this regard, according to one embodiment of the invention, loose files are examined for relevancy and, if relevant, stored in a proper data format, such as a PST file or the like. The metadata associated with the non-standardized files is retained and remains with the reformatted data files. Source-to-processing file conversions may be required on EML formatted files, MSG formatted files and the like.
At Event 544, the journaled data set is loaded into the analysis application and, at Event 546, the journaled data set is exported to the requestor/reviewer for analysis.
Referring to
At Event 552, the barcoding application is implemented at a staging location, such as short-term staging drive (180) to attach a barcode to the set of local PC data resulting from the particular collection. The barcoded data is then copied and communicated to the long-term storage area network (190) for permanent storage. At Event 554, the collected and barcoded local PC data may be associated with a specific search term set or sets.
At Event 556 source-to-processing is implemented to insure that any loose files are properly formatted in a standardized format. In this regard, according to one embodiment of the invention, loose files are examined for relevancy and, if relevant, stored in a proper data format, such as a PST file or the like. The metadata associated with the non-standardized files is retained and remains with the reformatted data files. Source-to-processing file conversions may be required on EML formatted files, MSG formatted files, IPD formatted files and the like.
At Event 558, the local PC files that may be encrypted are decrypted using a decryption application, in accordance with embodiments of the present invention. The decryption application allows for decryption of the PC files data without the knowledge of the user/encrypter. The decryption application finds ID files that exist anywhere in the enterprise system, creates a database of the ID files, associates the database with the user/encrypter and subsequently decrypts the data.
At Event 560, the local PC data set is loaded into the analysis application and, at Event 562, the local PC data set is exported to the requestor/reviewer for analysis.
Data block 564 signifies data from network storage, such as a shared drive or HomeSpace. At Event 566, the file server collection application (134) is implemented to automatically collect data from shared drives and/or HomeSpace. According to one embodiment of the invention, the file server collection application (134) may be autodeployed thus, obviating the need for any manual entry by the e-discovery manager or the like.
At Event 568, the barcoding application is implemented at a staging location, such as short-term staging drive (180) to attach a barcode to the set of network storage data resulting from the particular collection. The barcoded data is then copied and communicated to the long- term storage area network (190) for permanent storage. At Event 570, the collected and barcoded network storage data may be associated with a specific search term set or sets.
At Event 572 source-to-processing is implemented to insure that any loose files are properly formatted in a standardized format. In this regard, according to one embodiment of the invention, loose files are examined for relevancy and, if relevant, stored in a proper data format, such as a PST file or the like. The metadata associated with the non-standardized files is retained and remains with the reformatted data files. Source-to-processing file conversions may be required on EML formatted files, MSG formatted files, IPD formatted files and the like.
At Event 574, the network storage files that may be encrypted are decrypted using a decryption application, in accordance with embodiments of the present invention. The decryption application allows for decryption of the network storage data without the knowledge of the user/encrypter. The decryption application finds ID files that exist anywhere in the enterprise system, creates a database of the ID files, associates the database with the user/encrypter and subsequently decrypts the data.
At Event 576, the network storage data set is loaded into the analysis application and, at Event 578, the network storage data set is exported to the requestor/reviewer for analysis.
Data block 580 signifies electronic data for forensics. At Event 582, a forensic collector application, such as EnCase® may be executed on the devices of interest to collect data. According to one embodiment of the invention, the forensic collector application may be automatically deployed on the device of interest without the knowledge of the device user. In accordance with another embodiment of the invention, a computer monitoring application may be implemented (not shown in
At Event 584, the barcoding application is implemented at a staging location, such as short-term staging drive (180) to attach a barcode to the set of forensic data resulting from the particular collection. The barcoded data is then copied and communicated to the long-term storage area network (190) for permanent storage. At Event 586, the collected and barcoded forensic data may be associated with a specific search term set or sets.
At Event 588 source-to-processing is implemented to insure that any loose files are properly formatted in a standardized format. In this regard, according to one embodiment of the invention, loose files are examined for relevancy and, if relevant, stored in a proper data format, such as a PST file or the like. The metadata associated with the non-standardized files is retained and remains with the reformatted data files. Source-to-processing may be required on EML formatted files, MSG formatted files, IPD formatted files and the like.
At Event 590, the forensic files that may be encrypted are decrypted using a decryption application, in accordance with embodiments of the present invention. The decryption application allows for decryption of the network storage data without the knowledge of the user/encrypter. The decryption application finds ID files that exist anywhere in the enterprise system, creates a database of the ID files, associates the database with the user/encrypter and subsequently decrypts the data.
At Event 592, the forensic data set is loaded into the analysis application and, at Event 594, the network storage data set is exported to the requestor/reviewer for analysis.
Data block 596 signifies collaborative data, such as data residing at discovery sites, for example LiveLink® or the like. At Event 598, a discovery site collector application, such as a LiveLink® collector application may be executed on the devices of interest to collect data. According to one embodiment of the invention, the discovery site collector preserves at least a portion of the discovery site database in the e-discovery database, including all files and all revisions of the files. In this regard, the discovery site collector application queries against the database to define what files need to be retrieved, then copies those files based on the result of the query. Metadata pertaining to the files is retained in the case management system tables. In accordance with another embodiment of the invention, the discovery site collector application collects the documents and the related metadata and uses the metadata to automatically rename the files.
At Event 600, the barcoding application is implemented at a staging location, such as short-term staging drive (180) to attach a barcode to the set of discovery site data resulting from the particular collection. The barcoded data is then copied and communicated to the long-term storage area network (190) for permanent storage. At Event 602, the collected and barcoded discovery site data may be associated with a specific search term set or sets.
At Event 604 source-to-processing is implemented to insure that any loose files are properly formatted in a standardized format. In this regard, according to one embodiment of the invention, loose files are examined for relevancy and, if relevant, stored in a proper data format, such as a PST file or the like. The metadata associated with the non-standardized files is retained and remains with the reformatted data files. Source-to-processing may be required on EML formatted files, MSG formatted files, IPD formatted files and the like.
At Event 606, the discovery site data set is loaded into the analysis application and, at Event 608, the discovery site data set is exported to the requestor/reviewer for analysis.
Thus, present embodiments herein disclosed provide for improvements in electronic discovery. Embodiments herein disclosed provide for an enterprise-wide e-discovery system that provides for data to be identified, located, retrieved, preserved, searched, reviewed and produced in an efficient and cost-effective manner across the entire enterprise system. In addition, by structuring management of e-discovery based on case/matter, custodian and data and providing for linkage between the same, further efficiencies are realized in terms of identifying, locating and retrieving data and leveraging results of previous e-discoveries with current requests.
Specifically, embodiments of the invention previously disclosed provide predictive and automated coding of identical or highly similar documents for the purpose of limiting the volume of documents requiring review and thereby increasing the overall efficiency of the document review process. Additional embodiments provide for targeted document review assignments that determine concept-related data groupings within the overall corpus of data associated with a case and generate the targeted document review assignments based on the concept-related data groupings. As such, document reviewers are presented with assignments that have highly conceptually-related documents, which results in further efficiency in the review process.
While certain exemplary embodiments have been described and shown in the accompanying drawings, it is to be understood that such embodiments are merely illustrative of and not restrictive on the broad invention, and that this invention not be limited to the specific constructions and arrangements shown and described, since various other updates, combinations, omissions, modifications and substitutions, in addition to those set forth in the above paragraphs, are possible.
Those skilled in the art may appreciate that various adaptations and modifications of the just described embodiments can be configured without departing from the scope and spirit of the invention. Therefore, it is to be understood that, within the scope of the appended claims, the invention may be practiced other than as specifically described herein.
Claims
1. An apparatus for determining targeted document review assignments in an electronic discovery system, the apparatus comprising:
- a computing platform including a memory and a processor;
- a targeted document review assignment application stored in the memory, executable by the processor;
- a concept-based data grouping mechanism configured to: receive a plurality of document coding inputs that each assign a review code to one of a plurality of first documents included within previously collected electronic data associated with a case in the electronic discovery system, wherein the review code indicates a level of relevancy or importance in relation to the case; in response to receiving the at least one document coding input that assigns a review code to the first document, determining if one or more second documents, which are associated with other cases in the electronic discovery system which are pending review are same or similar to the first document based comparing one or more hash marks associated with the first document and one or more hash marks associated with the one or more second documents; in response to receiving the at least one document coding input that codes the first document, determining, via a computing device, if one or more third documents, which are associated with other cases in the electronic discovery system, have been collected and are pending review are same as the first document; in response to determining that the second documents are the same as the first document, automatically assign, via the computing device, the review code assigned to the first document to the second documents that are the same as the first document, wherein automatically assigning further comprises providing a confidence indicator for the one or more second documents, wherein the confidence indicator indicates a level of similarity between the second documents and the first document; in response to determining that the third documents are same as the first document, automatically assigning, via a computing device processor, the review code assigned to the first document to the third documents that are the same as the first document, wherein automatically assigning further comprises providing a confidence indicator for the one or more third documents, wherein the confidence indicator indicates a level of similarity between the third documents and the first and second documents; determine a plurality of data groupings based at least partially on each of the plurality of document coding inputs for assigning a review code to each of the first documents, the second documents, and the third documents; and
- a document review assignment generator configured to: generate a plurality of document review assignments based on the plurality of data groupings, wherein each of the plurality of document review assignments comprise a predetermined number of allowable documents or files, wherein one or more of the plurality of document review assignments generated includes a first data grouping of the plurality of data groupings that is associated with a first review code of the plurality of document coding inputs and at least a portion of a second data grouping of the plurality of data groupings that is associated with a second review code of the plurality of document coding inputs when the first data grouping has less documents than the predetermined number of documents or files allowable for each of the one or more of the plurality of document review assignments.
2. The apparatus of claim 1, wherein the concept-based data grouping mechanism is further configured to receive a plurality of predetermined concepts, wherein the predetermined concepts are further defined as a final search term set.
3. The apparatus of claim 1, wherein the document review assignment generator is further configured to generate the plurality of document review assignments, wherein each of assignments includes at least a portion of one of the plurality of data groupings.
4. The apparatus of claim 1, wherein the document review assignment generator is further configured to generate the plurality of document review assignments, wherein each of the assignments include one or more of the plurality of data groupings.
5. The apparatus of claim 1, wherein the targeted document review assignment application further includes a targeted document review assignor configured to assign one or more of the plurality of document review assignments to each of a plurality of document reviewers, wherein the assignment is based on associated data groupings within the document review assignments.
6. The apparatus of claim 5, wherein the targeted document review assignor is further configured to assign the one or more of the plurality of document review assignments to each of the plurality of document reviewers, such that two or more document review assignments that include a portion of a same grouping are assigned to a same document reviewer.
7. The apparatus of claim 1, wherein the document review assignment generator is further configured to generate the document review assignments wherein each assignment includes at least approximately 2,000 documents.
8. A computer program product comprising:
- a non-transitory computer-readable medium comprising: a first set and a second set of codes for causing a computer to: receive a plurality of document coding inputs that each assign a review code to one of a plurality of first documents included within previously collected electronic data associated with a case in the electronic discovery system, wherein the review code indicates a level of relevancy or importance in relation to the case; in response to receiving the at least one document coding input that assigns a review code to the first document, determining if one or more second documents, which are associated with other cases in the electronic discovery system which are pending review are same or similar to the first document based comparing one or more hash marks associated with the first document and one or more hash marks associated with the one or more second documents; in response to receiving the at least one document coding input that codes the first document, determining, via a computing device, if one or more third documents, which are associated with other cases in the electronic discovery system, have been collected and are pending review are same as the first document; in response to determining that the second documents are the same as the first document, automatically assign, via the computing device, the review code assigned to the first document to the second documents that are the same as the first document, wherein automatically assigning further comprises providing a confidence indicator for the one or more second documents, wherein the confidence indicator indicates a level of similarity between the second documents and the first document; in response to determining that the third documents are same as the first document, automatically assigning, via a computing device processor, the review code assigned to the first document to the third documents that are the same as the first document, wherein automatically assigning further comprises providing a confidence indicator for the one or more third documents, wherein the confidence indicator indicates a level of similarity between the third documents and the first and second documents; a second set of codes for causing a computer to: determine a plurality of data groupings based at least partially on each of the plurality of document coding inputs for assigning a review code to each of the first documents, the second documents, and the third documents; and a third set of codes for causing a computer to: generate a plurality of document review assignments based on the plurality of data groupings, wherein each of the plurality of document review assignments comprise a predetermined number of allowable documents or files, wherein one or more of the plurality of document review assignments generated includes a first data grouping of the plurality of data groupings that is associated with a first review code of the plurality of document coding inputs and at least a portion of a second data grouping of the plurality of data groupings that is associated with a second review code of the plurality of document coding inputs when the first data grouping has less documents than the predetermined number of documents or files allowable for each of the one or more of the plurality of document review assignments.
9. The computer program product of claim 8, wherein the first set of codes is further configured to cause the computer to receive a plurality of predetermined concepts, wherein the predetermined concepts are further defined as a final search term set.
10. The computer program product of claim 8, wherein the third set of codes is further configured to cause the computer to generate the plurality of document review assignments, wherein each of assignments includes at least a portion of one of the plurality of data groupings.
11. The computer program product of claim 8, wherein the third set of codes is further configured to cause the computer to generate the plurality of document review assignments, wherein each of the assignments include one or more of the plurality of data groupings.
12. The computer program product of claim 8, further comprising a fourth set of codes for causing a computer to assign one or more of the plurality of document review assignments to each of a plurality of document reviewers, wherein the assigning is based on associated data groupings within the document review assignments.
13. The computer program product of claim 12, wherein the fourth set of codes is further configured to cause the computer to assign one or more of the plurality of document review assignments to each of a plurality of document reviewers, such that two or more document review assignments that include a portion of a same grouping are assigned to a same document reviewer.
14. The computer program product of claim 8, wherein the second set of codes is further configured to cause the computer to generate the document review assignments wherein each assignment includes at least approximately 2,000 documents.
15. A method for determining targeted document review assignments in an electronic discovery system, the method comprising:
- receiving, at a computing device, a plurality of document coding inputs that each assign a review code to one of a plurality of first documents included within previously collected electronic data associated with a case in the electronic discovery system, wherein the review code indicates a level of relevancy or importance in relation to the case;
- in response to receiving the at least one document coding input that assigns a review code to the first document, determining if one or more second documents, which are associated with other cases in the electronic discovery system which are pending review are same or similar to the first document based comparing one or more hash marks associated with the first document and one or more hash marks associated with the one or more second documents;
- in response to receiving the at least one document coding input that codes the first document, determining, via a computing device, if one or more third documents, which are associated with other cases in the electronic discovery system, have been collected and are pending review are same as the first document;
- in response to determining that the second documents are the same as the first document, automatically assigning, via the computing device, the review code assigned to the first document to the second documents that are the same as the first document, wherein automatically assigning further comprises providing a confidence indicator for the one or more second documents, wherein the confidence indicator indicates a level of similarity between the second documents and the first document;
- in response to determining that the third documents are same as the first document, automatically assigning, via a computing device processor, the review code assigned to the first document to the third documents that are the same as the first document, wherein automatically assigning further comprises providing a confidence indicator for the one or more third documents, wherein the confidence indicator indicates a level of similarity between the third documents and the first and second documents;
- determining, via a computing device, a plurality of data groupings based at least partially on each of the plurality of document coding inputs for assigning a review code to each of the first documents, the second documents, and the third documents; and
- generating, by the computing device processor, a plurality of document review assignments based on the plurality of data groupings, wherein each of the plurality of document review assignments comprise a predetermined number of allowable documents or files, wherein one or more of the plurality of document review assignments generated includes a first data grouping of the plurality of data groupings that is associated with a first review code of the plurality of document coding inputs and at least a portion of a second data grouping of the plurality of data groupings that is associated with a second review code of the plurality of document coding inputs when the first data grouping has less documents than the predetermined number of documents or files allowable for each of the one or more of the plurality of document review assignments.
16. The method of claim 15, wherein receiving further comprises receiving, at the computing device a plurality of predetermined concepts, wherein the predetermined concepts are further defined as a final search term set.
17. The method of claim 15, wherein generating further comprises generating, via the computing device processor, the plurality of document review assignments, wherein each of assignments includes at least a portion of one of the plurality of data groupings.
18. The method of claim 15, wherein generating further comprises, generating, via the computing device, the plurality of document review assignments, wherein each of the assignments include one or more of the plurality of data groupings.
19. The method of claim 15, further comprising computer-executable instruction code, that when executed causes the processing device to:
- assign, at the computing device, one or more of the plurality of document review assignments to each of a plurality of document reviewers, wherein the assigning is based on associated data groupings within the document review assignments.
20. The method of claim 19, wherein assigning further comprises assigning, at the computing device, one or more of the plurality of document review assignments to each of a plurality of document reviewers, such that two or more document review assignments that include a portion of a same grouping are assigned to a same document reviewer.
Type: Application
Filed: Mar 6, 2015
Publication Date: Jun 25, 2015
Inventors: Phillip L. Richards (Charlotte, NC), David M. Andersen (Charlottle, NC), Emerson D. Miller (Charlotte, NC), Benjamin Clark (Matthews, NC), Jeffrey V. Knox (Charlotte, NC), Michael J. Mayer (Charlotte, NC)
Application Number: 14/640,203
