Abstract: A media file system, apparatus, computer program product and method are provided for storing a file relationship graph and media data files. An exemplary method includes obtaining a new media file and determining the one or more portions of essence data from which the new media file is derived. The method further including generating a new materials data file for the new media file indicating the determined one or more portions of essence data. Moreover, storing the new materials data file in the media file system, and updating the file relationship graph using the new materials data file.

Abstract: Systems and methods are described for scheduling a query for execution. The system receives and parses a query to identify one or more portions of the query. The system determines a resource allocation for each portion of the query, and determines an availability of compute resources for the different portions of the query. Based on the resource allocation and the availability of compute resources, the system schedules the query.

Abstract: A method, computer program and computer program product for allowing update of digital objects as well as to an edge node and process control system including an edge node. The edge node obtains a copy of an original digital object from a process control server, the original object having a number of aspects and being provided according to a first process control data format, provides the copy as a modified object in a second data format that is open for applications external to the process control system, in which second data format the modified object compromises a number of data models receive an update of the modified object from the application, where the update includes a new data model.

Abstract: A hash corresponding to a bit string is generated. The hash corresponds to an address location in a data structure associated with the bit string. An index and a modifier correspond to the address location in the data structure corresponding to the hash associated with a first address location in the data structure are determined. In response to determining that the modifier has a first value associated therewith, index information corresponding to the bit string is written to the first address location in the data structure. In response to determining that the modifier has a second value other than the first value associated therewith, the index information corresponding to the bit string is written to a second address location in the data structure.

Abstract: Network appliances can record log entries in log objects. An object store can receive the log objects and can use the log objects to create index objects and flow log objects. Each flow log object and index object can be associated with a time period wherein the flow log object includes flow log entries received during that time period. The index object includes shard tables that can be stored in different nonvolatile memories and can thereby be concurrently searched. Shard entries in the shard tables indicate flow entry indicators. The flow entry indicators indicate log entries in the flow log object. An internally indexed searchable object can include the flow log object and the index object. Numerous indexed fields in the flow log entries and can be indexed with each indexed field searchable via the shard entries.

Abstract: Implementations of this disclosure provide for automated monitoring of configuration parameters of a primary data intake and query system instance operating within a distributed deployment environment. Further implementations provide for automatically generating instructions in response to a detected change in a configuration parameter of the primary data intake and query system instance and transmitting those instructions to one or more secondary data intake and query system instances. The instructions, upon execution by one or more processors, cause the configuration parameters of the one or more secondary data intake and query system instances to be updated in accordance with the detected change in the configuration parameter of the primary data intake and query system instance.

Abstract: Cost attribution using resource switching including receiving, by a workbook manager from a first client computing system, a first request for a workbook presenting a dataset from a cloud-based data warehouse, wherein the first request comprises a first user attribute; selecting, by the workbook manager, a first resource warehouse on the cloud-based data warehouse based on the first user attribute, wherein the first resource warehouse tracks resources used to service data requests on the cloud-based data warehouse; retrieving, by the workbook manager, the dataset from the cloud-based data warehouse using the first resource warehouse matched to the first user attribute; and presenting, on the first client computing system by the workbook manager, the workbook presenting the dataset.

Abstract: Generating and assigning metadata relating to action objects which arise in audio and/or visual media contents. The action objects are visual and/or audible objects or elements which can be perceived by a viewer and/or listener in audio and/or visual media contents and which originate from different production steps of the audio and/or visual media contents.

Abstract: Provided is a system and method for generating and updating a data model for use in retrieving data from an information retrieval system such as a database, a server, and the like. In one example, the method may include monitoring data that is written to database tables of a database by a software process, identifying links between the database tables where the monitored data is written, determining whether the software process has a pre-existing data model for retrieving data stored in the database, and in response to a determination that the software process does not include the pre-existing data model, creating a new data model for the software process which includes names of the database tables where the monitored data is written and links between the database tables, and storing the new data model via a database repository.

Abstract: A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.

Abstract: A cognate specification system manages and enforces digital, canonical representations of entities that are added to and in the system by creating a composite entity key (“EntityKey”) that uniquely and immutably identifies each entity within the system, and that is created based upon the attributes of the entity rather than being arbitrarily assigned. Entities may be organized into various types or cognates, each associated with distinct sets of attributes. A physical or digital referent may be added to the system as an entity by specifying attributes. In such a system, any entity, whether a physical or digital referent, a process, or other type, is uniquely and verifiably identifiable, and may be linked to or associated with other entities, allowing users of the system to produce and access specification granularity beyond traditional approaches focused on systems interoperability.

Abstract: A method, a system, and computer program product for updating various database artifacts using design definitions. A design time definition is received for a database artifact stored in a database. Design time metadata is extracted from the design time definition. Runtime metadata is retrieved from the database, the runtime metadata corresponding to the database artifact. Differences are determined between the design time metadata and the runtime metadata. An update query is generated based on the differences between the design time metadata and the runtime metadata. The update query is executed to update the database artifact.

Abstract: An enterprise ontology, an application data usage model, and/or cross-application data dependencies may be developed using artificial intelligence. Using pattern recognition and/or information extraction techniques, the artificial intelligence may analyze application source code to identify common DDL or SQL statements to formulate an ontology and/or a usage model for the application. A plurality of application ontologies and/or data usage models may be used to build a semantic hub. The semantic hub may be analyzed to identify data redundancies, data use frequency, potential data quality challenges, and/or data dependencies between applications to produce a data abstraction model that allows legacy applications to communicate with one or more data stores.

Abstract: Enabling editable tables on a cloud-based data warehouse including receiving, by a query manager, a client-provided table; receiving, by the query manager from a query manager client, a request to create a referencing worksheet using, as data sources, the client-provided table and a database table on a cloud-based data warehouse; storing, by the query manager, the client-provided table in the schema storage location on the cloud-based data warehouse, wherein the schema storage location is a storage location on the cloud-based data warehouse to which the query manager has read and write access, and wherein the database table is external to the schema storage location; generating, by the query manager, a database query to create the referencing worksheet, wherein the database query targets the client-provided table in the schema storage location and the database table; and issuing, by the query manager, the database query to the cloud-based data warehouse.

Abstract: This disclosure discloses systems, devices, and methods for parallelized data structure processing in context of machine learning and reverse proxy servers.

Abstract: A computer analyzes a relational schema of a database to generate a data entry schema and encodes the data entry schema as JSON. The data entry schema is sent to a database client so that the client can validate entered data before the entered data is sent for storage. From the client, entered data is received that conforms to the data entry schema because the client used the data entry schema to validate the entered data before sending the data. Into the database, the entered data is stored that conforms to the data entry schema. The data entry schema and the relational schema have corresponding constraints on a datum to be stored, such as a range limit for a database column or an express set of distinct valid values. A constraint may specify a format mask or regular expression that values in the column should conform to, or a correlation between values of multiple columns.

Abstract: A method for converting a spreadsheet into a data model includes: obtaining the spreadsheet including a plurality of cells containing data; identifying local structures within the spreadsheet using attributes of the data in the spreadsheet; combining the local structures of the spreadsheet into a generic multi-dimensional model comprising dimensions and data cubes; generating the data model using the generic multi-dimensional model by mapping elements of the generic multi-dimensional model to elements of the data model; and displaying, on a display and to a user, the data model. The dimensions and the data cubes are the elements of the generic multi-dimensional model.

Abstract: Embodiments of the disclosure provide for improved integration of third-party devices in a system. Specifically, embodiments provide for improved integration management, including creation, deployment, maintenance, and monitoring of integrations utilizing integration templates. Embodiments include operation using a specially configured templating system that enables creation of integration template(s), management of integration template(s), searching of integration template(s), and initiation of such integration template(s) into integration instance(s) for particular client system(s), as well as updating of integration instance(s) based on integration template(s). Some embodiments provide dashboard(s) for accessing and/or managing integration instance(s) or associated information.

Abstract: A containerized data classification and automated metadata publishing system (DCAMPS-C) is disclosed. DCAMPS-C is powered by a data classification engine. The containerized data classification and automated metadata publishing system hosts a data classification and automated metadata cloud application publishing service. DCAMPS-C offers a containerized solution that automates the data classification and metadata generation processes, eliminates the need for manual input, reduces the chances of human error, and ensures seamless integration with modern cloud and on-premise infrastructures for better resource utilization, scalability, and overall efficiency in managing digital content within an organization.

Abstract: A system and method for query selection are provided. The method may include acquiring a natural language sentence, pre-processing to obtain a standard node sequence, constructing a node tree based on the relationship between an index node and other nodes, generating a data query command based on the node tree, querying data using the data query command, and filtering the results. The standard node sequence may include at least an index node and a condition node. The node tree may be used to characterize the index-condition combination. The system may include an acquisition unit, a pre-processing unit, a node tree construction unit, a translation unit, and a querying and filtering unit.