Abstract: A privacy management system that is adapted for, in the course of processing a particular data subject access request, automatically determining a type of the data subject access request, such as: (1) a request to delete personal data of the requestor that is being stored by a particular organization; (2) a request to provide, to the requestor, personal data of the requestor that is being stored by the particular organization; (3) a request to update personal data of the requestor that is being stored by the particular organization; and (4) a request to opt out of having the particular organization use the requestor's personal information in one or more particular ways. After making this determination, the system may determine, based on the determined type of data subject access request, a particular workflow to follow in authenticating the data subject before fulfilling the data subject access request.

Abstract: In particular embodiments, in response a data subject submitting a request to delete their personal data from an organization's systems, the system may: (1) automatically determine where the data subject's personal data is stored; (2) in response to determining the location of the data (which may be on multiple computing systems), automatically facilitate the deletion of the data subject's personal data from the various systems; and (3) determine a cause of the request to identify one or more processing activities or other sources that result in a high number of such requests.

Abstract: Data processing systems and methods, according to various embodiments, are adapted for automatically assessing the level of security and/or privacy risk associated with doing business with a particular vendor or other entity and for generating training material for such vendors. In various embodiments, the systems may automatically obtain and use any suitable information to assess such risk levels including, for example: (1) any security and/or privacy certifications held by the vendor; (2) the terms of one or more contracts between a particular entity and the vendor; (3) the results of one or more privacy impact assessments for the vendor; and/or (4) any other suitable data. The system may be configured to automatically approve or reject a particular vendor based on the assessed risk level associated with the vendor and this information may be automatically communicated to an entity considering doing business with the vendor and/or the vendor itself.

Abstract: In particular embodiments, a data processing data inventory generation system is configured to: (1) generate a data model (e.g., a data inventory) for one or more data assets utilized by a particular organization; (2) generate a respective data inventory for each of the one or more data assets; and (3) map one or more relationships between one or more aspects of the data inventory, the one or more data assets, etc. within the data model. In particular embodiments, a data asset (e.g., data system, software application, etc.) may include, for example, any entity that collects, processes, contains, and/or transfers personal data (e.g., such as a software application, “internet of things” computerized device, database, website, data-center, server, etc.). The system may be configured to identify particular data assets and/or personal data in data repositories using any suitable intelligent identity scanning technique.

Abstract: Data processing systems and methods, according to various embodiments, are adapted for automatically assessing the level of security and/or privacy risk associated with doing business with a particular vendor or other entity and for generating training material for such vendors. In various embodiments, the systems may automatically obtain and use any suitable information to assess such risk levels including, for example: (1) any security and/or privacy certifications held by the vendor; (2) the terms of one or more contracts between a particular entity and the vendor; (3) the results of one or more privacy impact assessments for the vendor; and/or (4) any other suitable data. The system may be configured to automatically approve or reject a particular vendor based on the assessed risk level associated with the vendor and this information may be automatically communicated to an entity considering doing business with the vendor and/or the vendor itself.

Abstract: Data processing systems and methods according to various embodiments are adapted for automatically detecting and documenting privacy-related aspects of computer software. Particular embodiments are adapted for: (1) automatically scanning source code to determine whether the source code include instructions for collecting personal data; and (2) facilitating the documentation of the portions of the code that collect the personal data. For example, the system may automatically prompt a user for comments regarding the code. The comments may be used, for example, to populate: (A) a privacy impact assessment; (B) system documentation; and/or (C) a privacy-related data map. The system may comprise, for example, a privacy comment plugin for use in conjunction with a code repository.

Abstract: A computer-implemented method for populating a privacy-related data model by: (1) providing a data model that comprises one or more respective populated or unpopulated fields; (2) determining that at least a particular one of the fields for a particular data asset is an unpopulated field; (3) at least partially in response to determining that the at least one particular field is unpopulated, automatically generating a privacy questionnaire comprising at least one question that, if properly answered, would result in a response that may be used to populate the at least one particular unpopulated field; (4) transmitting the privacy questionnaire to at least one individual; (5) receiving a response to the questionnaire, the response comprising a respective answer to the at least one question; and (6) in response to receiving the response, populating the at least one particular unpopulated field with information from the received response.

Abstract: In particular embodiments, a data processing data inventory generation system is configured to: (1) generate a data model (e.g., a data inventory) for one or more data assets utilized by a particular organization; (2) generate a respective data inventory for each of the one or more data assets; and (3) map one or more relationships between one or more aspects of the data inventory, the one or more data assets, etc. within the data model. In particular embodiments, a data asset (e.g., data system, software application, etc.) may include, for example, any entity that collects, processes, contains, and/or transfers personal data (e.g., such as a software application, “internet of things” computerized device, database, website, data-center, server, etc.). For example, a first data asset may include any software or device (e.g., server or servers) utilized by a particular entity for such data collection, processing, transfer, storage, etc.

Abstract: A consent receipt management system may, for example, be configured to track data on behalf of an entity that collects and/or processes persona data related to: (1) who consented to the processing or collection of personal data; (2) when the consent was given (e.g., a date and time); (3) what information was provided to the consenter at the time of consent (e.g., a privacy policy, what personal data would be collected following the provision of the consent, for what purpose that personal data would be collected, etc.); (4) how consent was received (e.g., one or more copies of a data capture form, webform, etc. via which consent was provided by the consenter); (5) when consent was withdrawn (e.g., a date and time of consent withdrawal if the consenter withdraws consent); and/or (6) any other suitable data related to receipt or withdrawal of consent.

Abstract: Responding to a data subject access request includes receiving the request and identifying the requestor and source. In response to identifying the requestor and source, a computer processor determines whether the data subject access request is subject to fulfillment constraints, including whether the requestor or source is malicious. If so, then the computer processor denies the request or requests a processing fee prior to fulfillment. If not, then the computer processor fulfills the request.

Abstract: In various embodiments, a data map generation system is configured to receive a request to generate a privacy-related data map for particular computer code, and, at least partially in response to the request, determine a location of the particular computer code, automatically obtain the particular computer code based on the determined location, and analyze the particular computer code to determine privacy-related attributes of the particular computer code, where the privacy-related attributes indicate types of personal information that the particular computer code collects or accesses. The system may be further configured to generate and display a data map of the privacy-related attributes to a user.

Abstract: Data processing systems and methods, according to various embodiments, are adapted for automatically assessing the level of security and/or privacy risk associated with doing business with a particular vendor or other entity and for generating training material for such vendors. In various embodiments, the systems may automatically obtain and use any suitable information to assess such risk levels including, for example: (1) any security and/or privacy certifications held by the vendor; (2) the terms of one or more contracts between a particular entity and the vendor; (3) the results of one or more privacy impact assessments for the vendor; and/or (4) any other suitable data. The system may be configured to automatically approve or reject a particular vendor based on the assessed risk level associated with the vendor and this information may be automatically communicated to an entity considering doing business with the vendor and/or the vendor itself.

Abstract: Data processing systems and methods, according to various embodiments, are adapted for automatically assessing the level of security and/or privacy risk associated with doing business with a particular vendor or other entity and for generating training material for such vendors. In various embodiments, the systems may automatically obtain and use any suitable information to assess such risk levels including, for example: (1) any security and/or privacy certifications held by the vendor; (2) the terms of one or more contracts between a particular entity and the vendor; (3) the results of one or more privacy impact assessments for the vendor; and/or (4) any other suitable data. The system may be configured to automatically approve or reject a particular vendor based on the assessed risk level associated with the vendor and this information may be automatically communicated to an entity considering doing business with the vendor and/or the vendor itself.

Abstract: A privacy management system that is adapted for, in the course of processing a particular data subject access request, automatically determining a type of the data subject access request, such as: (1) a request to delete personal data of the requestor that is being stored by a particular organization; (2) a request to provide, to the requestor, personal data of the requestor that is being stored by the particular organization; (3) a request to update personal data of the requestor that is being stored by the particular organization; and (4) a request to opt out of having the particular organization use the requestor's personal information in one or more particular ways. After making this determination, the system may determine, based on the determined type of data subject access request, a particular workflow to follow in authenticating the data subject before fulfilling the data subject access request.

Abstract: In particular embodiments, in response a data subject submitting a request to delete their personal data from an organization's systems, the system may: (1) automatically determine where the data subject's personal data is stored; (2) in response to determining the location of the data (which may be on multiple computing systems), automatically facilitate the deletion of the data subject's personal data from the various systems; and (3) determine a cause of the request to identify one or more processing activities or other sources that result in a high number of such requests.

Abstract: In particular embodiments, a data subject request processing system may be configured to utilize one or more local storage nodes in order to process a data subject access request on behalf of a data subject. In particular embodiments, the one or more local storage nodes may be local to the data subject making the request (e.g., in the same country as the data subject, in the same jurisdiction, in the same geographic area, etc.). The system may, for example, be configured to: (1) receive a data subject access request from a data subject (e.g., via a web form); (2) identify a suitable local storage node based at least in part on the request and/or the data subject; (3) route the data subject access request to the identified local storage node; and (4) process the data subject access request at the identified local storage node.

Abstract: Data processing systems and methods according to various embodiments are adapted for automatically detecting and documenting privacy-related aspects of computer software. Particular embodiments are adapted for: (1) automatically scanning source code to determine whether the source code include instructions for collecting personal data; and (2) facilitating the documentation of the portions of the code that collect the personal data. For example, the system may automatically prompt a user for comments regarding the code. The comments may be used, for example, to populate: (A) a privacy impact assessment; (B) system documentation; and/or (C) a privacy-related data map. The system may comprise, for example, a privacy comment plugin for use in conjunction with a code repository.

Abstract: Data processing systems and methods, according to various embodiments, are adapted for automatically assessing the level of security and/or privacy risk associated with doing business with a particular vendor or other entity and for generating training material for such vendors. In various embodiments, the systems may automatically obtain and use any suitable information to assess such risk levels including, for example: (1) any security and/or privacy certifications held by the vendor; (2) the terms of one or more contracts between a particular entity and the vendor; (3) the results of one or more privacy impact assessments for the vendor; and/or (4) any other suitable data. The system may be configured to automatically approve or reject a particular vendor based on the assessed risk level associated with the vendor and this information may be automatically communicated to an entity considering doing business with the vendor and/or the vendor itself.

Abstract: A computer-implemented method for populating a privacy-related data model by: (1) providing a data model that comprises one or more respective populated or unpopulated fields; (2) determining that at least a particular one of the fields for a particular data asset is an unpopulated field; (3) at least partially in response to determining that the at least one particular field is unpopulated, automatically generating a privacy questionnaire comprising at least one question that, if properly answered, would result in a response that may be used to populate the at least one particular unpopulated field; (4) transmitting the privacy questionnaire to at least one individual; (5) receiving a response to the questionnaire, the response comprising a respective answer to the at least one question; and (6) in response to receiving the response, populating the at least one particular unpopulated field with information from the received response.

Abstract: In various embodiments, an organization may be required to comply with one or more legal or industry requirements related to the storage of personal data (e.g., which may, for example, include personally identifiable information) even when responding to and fulfilling Data Subject Access Requests. In particular, when responding to a DSAR, the system may compile one or more pieces of personal data for provision to a data subject. The system may store this compilation of personal data at least temporarily in order to provide access to the data to the data subject. As such, the system may be configured to implement one or more data retention rules in order to ensure compliance with any legal or industry requirements related to the temporary storage of the collected data while still fulfilling any requirements related to providing the data to data subjects that request it, deleting the data upon request, etc.