1. Technical Field
The invention relates to electronic discovery (eDiscovery). More particularly, the invention relates to an enterprise evidence repository.
2. Description of the Prior Art
Electronic discovery, also referred to as e-discovery or eDiscovery, concerns discovery in civil litigation, as well as tax, government investigation, and criminal proceedings, which deals with information in electronic form. In this context, the electronic form is the representation of information as binary numbers. Electronic information is different from paper information because of its intangible form, volume, transience, and persistence. Also, electronic information is usually accompanied by metadata, which is rarely present in paper information. Electronic discovery poses new challenges and opportunities for attorneys, their clients, technical advisors, and the courts, as electronic information is collected, reviewed, and produced. Electronic discovery is the subject of amendments to the Federal Rules of Civil Procedure which are effective Dec. 1, 2006. In particular, for example, but not by way of limitation, Rules 16 and 26 are of interest to electronic discovery.
Examples of the types of data included in e-discovery include e-mail, instant messaging chats, Microsoft Office files, accounting databases, CAD/CAM files, Web sites, and any other electronically-stored information which could be relevant evidence in a law suit. Also included in e-discovery is raw data which forensic investigators can review for hidden evidence. The original file format is known as the native format. Litigators may review material from e-discovery in any one or more of several formats, for example, printed paper, native file, or as TIFF images.
The revisions to the Federal Rules formally address e-discovery and in the process, have made it a nearly certain element of litigation. For corporations, the rules place a very early focus on existing retention practices and the preservation and discovery of information.
In response to the climate change in the e-discovery arena, corporations are:
1) enhancing their processes for issuing legal holds and tracking collections;
2) looking for ways to reduce the costs of collecting, processing and reviewing electronic data; and
3) looking upstream to reduce the volume of unneeded data through better retention policies that are routinely enforced.
The new field of e-discovery management has emerged to assist companies that are overwhelmed by the requirements imposed by the new rules and the spate of legal and regulatory activity regarding e-discovery.
Currently, e-discovery management applications (EMA) rely on a variety of approaches to store electronic data for e-discovery. For example:
EMAs store content as binary objects in a database. Transaction information as well as file collections are typically stored in the same relational database located on a database server;
EMAs also store content as content objects in a content management system. EMAs can use a content management system, such as EMC DOCUMENTUM, EMC CORPORATION, Hopkinton, Mass., to store unstructured content; and
EMAs can use a local or networked file system to store content as files in a file system and a database to store file metadata.
Such conventional methods provide convenience and functionality, such as allowing the data to be updated, allowing it to be checked in and checked out, and so on. However, data stored for the purpose of e-discovery typically has the character of being immutable and unstructured, i.e. the data is to be permanently stored, or at least stored for a very long time; the data is not to be changed or updated or checked-in or -out very often; and it is typically unnecessary to organize or structure the data in a database or content base. In view of the immutable, unstructured nature of e-discovery data, such conventional storage approaches, in spite of their convenience and functionality, involve a number of disadvantages:
Thus, there exists a need to provide a way of storing collected content in e-discovery applications that eliminates unnecessary expense and managerial and administrative overhead, thus achieving cost savings and simplifying operations.
An embodiment of the invention comprises a system that includes a controller that is configured to generate and propagate instructions to an execution agent. The execution agent is configured to collect and deposit collected artifacts into a repository. The controller coordinates allocation of the storage in the repository. The controller propagates the collection instructions to the execution agent: the instructions contain a location for depositing collected artifacts. Write access must be granted to the execution agent. Such access is provided to a location in the repository for collected artifacts that are to be deposited into a specified location. Once the execution agent deposits the collected artifacts in the specified location in the repository, a summary of collected artifacts is propagated to the controller, thus providing transparency into the overall collection process.
Collected artifacts can be made available to a processing agent that is configured to perform various processing functions on them. The controller manages appropriate levels of access to the collected artifacts, while the repository enforces the level of access. The controller can grant read only access to the collected artifacts or it can allow for controlled changes to be made to the metadata associated with the collected artifact. An agent can process the data and generate additional metadata that can be associated with the collected artifacts and then saved in the repository.
Collected artifacts, along with the contextual data and additional metadata, reside in the repository. The controller can grant read only access to an agent that is capable of extracting all of the data from the repository and exporting it out.
A system can have more than one repository to store collected artifacts and metadata. In such a configuration, the controller allocates storage in an appropriate repository. The controller issues instructions to the execution agent with the location in an appropriate repository. The summary of the actual collections is then propagated to the controller from the repositories.
The following documents are cited herein to provide background information in connection with various embodiments of the herein disclosed invention. These documents are incorporated herein in their entirety based upon this reference thereto:
Discovery Cost Forecasting Patent Applications:
Forecasting Discovery Costs Using Historic Data; Ser. No. 12/165,018; filed 30 Jun. 2008; publication no. 2010/0017239 A1;
Forecasting Discovery Costs Based On Interpolation Of Historic Event Patterns; U.S. Pat. No. 8,073,729; issued 6 Dec. 2011;
Forecasting Discovery Costs Based on Complex and Incomplete Facts; Ser. No. 12/553,055; filed 2 Sep. 2009; publication no. 2009/0327048 A1; and
Forecasting Discovery Costs Based On Complex And Incomplete Facts; Ser. No. 12/553,068; filed 2 Sep. 2009; publication no. 2009/0327049 A1;
Automation Patent Application:
Method And Apparatus For Electronic Data Discovery; Ser. No. 11/963,383; filed 21 Dec. 2007; publication no. 2009/0165026 A1; and
Collection Transparency Patent Application:
Providing Collection Transparency Information To An End User To Achieve A Guaranteed Quality Document Search And Production In Electronic Data Discovery; U.S. Pat. No. 8,140,494; issued 20 Mar. 2012.
The following terms have the meaning associated with them below for purposes of the discussion herein:
Enterprise Discovery Management System (EDMS): technology to manage eDiscovery workflow in an enterprise such as the Atlas Enterprise Discovery Management system offered by PSS Systems of Mountain View, Calif.;
Enterprise Content Management (ECM) tools: a set of technologies to capture, manage, retain, search, and produce enterprise content, such as IBM's FileNet;
Early Case Assessment (ECA) tools: technology to evaluate risks associated with eDiscovery by identifying and analyzing relevant evidence;
Discovery Cost Forecasting (DCF): technology to model, forecast costs associated with eDiscovery, such as the Atlas DCF;
Evidence Repository (EvR): a system and processes for securely collecting, preserving, and providing access to documents and related metadata collected as part of eDiscovery;
Collection Manifest: a file describing various attributes of the contents of a collection including, but not limited to, the following type of metadata: chain of custody, file types, sizes, MAC dates, original locations, etc; and
Self-collections: a process of collection in which a legal function sends collection instructions directly to custodians and the custodians perform collection from local PCs, email, PDAs, file share, etc.
Abstract System
Collected artifacts can be made available to a processing agent (see 510 on
Collected artifacts, along with the contextual data and additional metadata, reside in the repository. The controller can grant read only access to an agent that is capable of extracting all of the data from the repository and exporting it out.
A system can have more than one repository to store collected artifacts and metadata (see
eDiscovery System
The EDMS propagates the legal case and other process data and metadata to the evidence repository, including (see
The EDMS 210 also generates a structured collection plan with detailed collection instructions. The IT 220 receives the instructions and performs collections from the data source 230, depositing the collected documents to the location of the directory in the staging area specified in the collection instructions received from EDMS.
Content source metadata is propagated along with the content of the collected documents. This type of metadata is derived from the content of collected file, for example size in bytes, page count, checksum, or hash code, calculated based on the content of a file, MIME type, etc.
Location metadata is propagated along with the contents of collected files. This type of metadata represents the location from where the files were originally collected. Examples of the metadata include: name or address of a PC, server, file path, file name, and modified, accessed, and created date of the file.
Collected documents and the metadata are ingested from the staging area to the evidence repository. Collected documents are grouped and linked to appropriate metadata that has been previously propagated to the evidence repository.
Collection Staging Area
When a new collection plan is created and published, the EDMS automatically propagates the collection plan, custodians, and data source information, and creates a directory structure in the collection staging area, which in
The EDMS also propagates the access control rules to the staging area by granting an appropriate level of access on a target collection deposit directory to an appropriate user or a group of users, based on the work assignment as defined in the EDMS.
Having an automatically managed staging area for collections enables simple and reliable collection process. The EDMS contains all of the data necessary to execute a collection based on the collection parameters specified by the legal department as part of the collection plan. Folders in the staging area are automatically provisioned for collections, data sources, and custodians. IT does not need to create folders manually. Collection instructions are automatically issued by the EDMS when the collection plan is published. The drop-off location parameters are automatically generated based on the network file share location path of an auto-provisioned directory in the collection staging area.
Evidence Repository
The evidence repository manages large volumes of collected documents and metadata and can be built on top of an existing content management system, such as an ECM.
The legal case entity is a container for the collection or interview plans 440, 441, 442, 443 which can be further categorized into structured collection plans, such as 440, 442, 443, and self collection plans 441. Collection plans have process metadata propagated from the EDMS that includes, for example, the following properties: name, status, date, collection parameters, etc.
Collection plans contain collection logs 460, 461, 462, 463, 464, 465. Collection logs have process metadata that includes, for example custodian, data source, log entry, conducted by, date conducted, status, etc. The collection logs contain evidence items that include the content and metadata of the collected documents. The metadata for the collection log is comprised of the process, source, and location metadata, as defined above.
Self-Collections
Advanced EDMS systems, such as the Atlas LCC, allow for custodian self-collections. This is a type of collection process when individual custodians receive collection instructions from the legal department and collect evidence, such as emails, documents, and other data, with easy to use tools provided to individual custodians. When using that mechanism the content and metadata may be collected to a dedicated EDMS storage.
The EDMS is responsible for propagating the data collected as part of a self-collection to the evidence repository.
Existing collections stored in EDMS are automatically migrated by moving the content and related case metadata to the evidence repository. This allows for centralized evidence management regardless of the type of a collection and its origins.
Data Processing
Data processing is an important part of the overall eDiscovery process. The EDMS can grant an appropriate level of access to users authorized to use a processing tools against the collected data stored in the evidence repository to enable the data processing. Examples of such access include read-only access to the case data and metadata or a subset of this data, and write access to a subset of metadata. Some data processing tools, such as Early Case Assessment (ECA) tools, can generate additional metadata, such as tags, notes, etc. The metadata generated by such a tool can be stored in the evidence repository if the EDMS grants write access on the subset of metadata associated with documents in the context of a specified legal case, plan, etc.
Data Export
Export tools 520 (see
Export metadata is a metadata associated with an event of exporting set of documents for an outside review. The metadata contains, for example, the date of export, volume of export in bytes, estimated number of pages exported, number of documents exported, etc.
DCF Metadata
The evidence repository is expected to track the overwhelming majority of the collected data. Facts created as a result of the collection, processing, and exporting of the collected data are automatically propagated from the evidence repository to a DCF system. Having the most accurate and up-to date facts is critical for reliable and precise eDiscovery cost modeling and forecasting.
The collected content is processed and analyzed by using an ECA 510 or similar set of tools. The collected content is tagged with additional ECA metadata and the metadata is propagated to the evidence repository. The metadata can be further aggregated and propagated to the DCF system and used to improve the accuracy of the discovery cost modeling and forecasting further.
Export tools 520 are used to extract the content and metadata of documents collected in the evidence repository and package and ship the data for an outside review or other use. The volume and timing metrics, such as volume collected in pages and GB, timing of collections, and number of custodians collected from or associated with an export event, are critical for an accurate discovery cost modeling and forecasting. The evidence repository enables highly reliable and repeatable automated process of propagating the export metadata to DCF when it becomes available.
The export data propagated to the DCF includes, for example, volume of export in bytes, estimated page count, date of export, number of documents, etc.
Ingestion Process
The ingestion process is responsible for ingesting the documents and metadata deposited into the collection drop-off locations within the staging area to the evidence repository.
The ingestion process relies on relationships between a folder in the staging area and collection log entity in the ECM that were previously established by the EDMS. Based on the location of documents in the staging area, the ingestion process finds previously created corresponding collection log entities in the evidence repository and links documents ingested from a collection log folder to the collection log entity in the evidence repository.
In some cases collections might also include additional metadata in a form of a collection manifest which can be in proprietary formats or in an XML based formats, such as EDRM XML. Collection manifest metadata is ingested along with collected contents. A collection manifest contains additional metadata including, for example, chain of custody, original location, etc. That metadata gets associated with document evidence entity as part of the ingestion process.
Improve Reliability
The reliability and accuracy of the collection process can be further improved by adding a secure token to the collection instructions for the IT. The secure token is a file containing information that uniquely identifies the identity of an individual collection target in a context of a collection plan.
The IT is instructed to deposit the token along with the collected files into the drop-off location specified in the instructions. As part of the ingestion process the system automatically validates the integrity of the collection including chain of custody and detects inconsistencies by comparing the information in the secure token against the expected collection target, collection plan, and other attributes based on the location from the where collected data is being ingested Depending on the ingestion policies such as a collection can be rejected. Exceptions are escalated to an appropriate authority for handling. If, upon the ingestion validation, the system detects that IT has mistakenly deposited data collected for a target into incorrect location along with a secure token for a given target, the system rejects the collection and alerts appropriate IT users and, optionally the legal department, with all of the details necessary to correct the situation by placing collected data in an appropriate location. This affects the overall status of the collection process propagated to EDMS, making it transparent to all of the parties involved until the issue is resolved.
Collection and Metadata Re-use
The evidence repository holds large volumes of collected data including, for example, content, source, location, process, export, DCF metadata and the metadata generated by ECA and other data processing tools. Collection with subsequent analysis and culling can be very costly, especially if done repeatedly. Redundant collection can be reduced or eliminated through the collection re-use.
An entire set the evidence metadata or a subset can also be reused taking a full advantage of the analysis, culling, and export that occurred in the legal case and collection plan being reused.
Monitoring
The EDMS 210 is responsible for the overall collection process. All the stages of the overall process report exceptions, a summary, and important statistics back to the EDMS. The EDMS aggregates the monitoring data from all the stages of the collection process, thus providing additional analytics. The EDMS thus enables visibility into the overall collection process.
The staging area 260 is monitored by analyzing the contents of the drop-off collection locations. The following exceptions and statistics, for example, are reported back to the EDMS: number of files deposited, pending ingestion, failed to delete, failed to ingest within the time limit, etc. These statistics are grouped by collection log, collection plan, legal case, and repository.
The evidence repository is monitored using platform specific mechanisms to detect new documents matching appropriate criterions. The following exceptions and statistics, for example, are reposted back to the EDMS: number of files ingested, failed to link to an appropriate collection log, various timeouts, etc. These statistics are grouped by collection log, collection plan, legal case, and repository and are propagated to the EDMS.
The data processing tools 910 may require an additional content indexing or linking steps for the collected data to become available for processing. For example, many ECA tools employ more sophisticated content and metadata indexing mechanism that evidence repository may provide. This requires additional processing as part of making the collected data available for the analysis. The following exceptions and statistics, for example, are reposted back to the EDMS from the data processing step: number of files available for analysis, number of files pending, number of files failed, various timeouts, etc. These statistics are grouped by collection log, collection plan, legal case, and repository and are propagated to the EDMS.
Multiple Repositories
The system supports a configuration with multiple repositories. All the repositories have a dedicated staging area from where the collected data is ingested to each individual repository. The EDMS maintains a catalog of evidence repositories which contains the names, access control rules, and path to the root of the staging area for each repository.
The evidence repository can be selected for a matter type, legal case, and collection plan. When a collection plan is published, the EDMS allocates storage and provision directories in the staging area of a selected evidence repository. The EDMS propagates the legal case and other process data and metadata to the appropriate evidence repository.
The EDMS generates and propagates collection instructions to an IT or an automated collection tools such as Atlas ACA containing the location of the staging area for a selected repository.
Many countries have data protection laws designed to protect information considered to be personally identifiable. For example, EU directives establish a level of protection that effectively makes data transfer from an EU member to the US illegal.
A multiple local evidence repositories can be set up to eliminate the need to transfer the data across jurisdictions. The instructions are generated such that collected content and metadata are deposited in a location within the jurisdiction specific staging area. Collection is ingested into a local ECM within the local evidence repository.
Multiple repositories with various levels of security can be used depending on a legal case security group, individual legal case, and collection plan. Thus, a collection plan involving custodians and data sources located in an IT department 121 is propagated to a default repository 1010. For a case with increased level of security the collection instructions are generated in a way that collected content and metadata are deposited and managed by a secure repository.
Structured Collection Indexed by Custodian
Paralegal Creates Manual Structured Collection Plan:
Access control is propagated from EDMS so only authorized users get access to the case data
The computer system 1600 includes a processor 1602, a main memory 1604 and a static memory 1606, which communicate with each other via a bus 1608. The computer system 1600 may further include a display unit 1610, for example, a liquid crystal display (LCD) or a cathode ray tube (CRT). The computer system 1600 also includes an alphanumeric input device 1612, for example, a keyboard; a cursor control device 1614, for example, a mouse; a disk drive unit 1616, a signal generation device 1618, for example, a speaker, and a network interface device 1628.
The disk drive unit 1616 includes a machine-readable medium 1624 on which is stored a set of executable instructions, i.e. software, 1626 embodying any one, or all, of the methodologies described herein below. The software 1626 is also shown to reside, completely or at least partially, within the main memory 1604 and/or within the processor 1602. The software 1626 may further be transmitted or received over a network 1630 by means of a network interface device 1628.
In contrast to the system 1600 discussed above, a different embodiment uses logic circuitry instead of computer-executed instructions to implement processing entities. Depending upon the particular requirements of the application in the areas of speed, expense, tooling costs, and the like, this logic may be implemented by constructing an application-specific integrated circuit (ASIC) having thousands of tiny integrated transistors. Such an ASIC may be implemented with complementary metal oxide semiconductor (CMOS), transistor-transistor logic (TTL), very large systems integration (VLSI), or another suitable construction. Other alternatives include a digital signal processing chip (DSP), discrete circuitry (such as resistors, capacitors, diodes, inductors, and transistors), field programmable gate array (FPGA), programmable logic array (PLA), programmable logic device (PLD), and the like.
It is to be understood that embodiments may be used as or to support software programs or software modules executed upon some form of processing core (such as the CPU of a computer) or otherwise implemented or realized upon or within a machine or computer readable medium. A machine-readable medium includes any mechanism for storing or transmitting information in a form readable by a machine, e.g. a computer. For example, a machine readable medium includes read-only memory (ROM); random access memory (RAM); magnetic disk storage media; optical storage media; flash memory devices; electrical, optical, acoustical or other form of propagated signals, for example, carrier waves, infrared signals, digital signals, etc.; or any other type of media suitable for storing or transmitting information.
Although the invention is described herein with reference to the preferred embodiment, one skilled in the art will readily appreciate that other applications may be substituted for those set forth herein without departing from the spirit and scope of the present invention. Accordingly, the invention should only be limited by the Claims included below.
Number | Name | Date | Kind |
---|---|---|---|
5313609 | Baylor et al. | May 1994 | A |
5355497 | Cohen-Levy | Oct 1994 | A |
5608865 | Midgely et al. | Mar 1997 | A |
5701472 | Koerber et al. | Dec 1997 | A |
5875431 | Heckman et al. | Feb 1999 | A |
5903879 | Mitchell | May 1999 | A |
5963964 | Nielsen | Oct 1999 | A |
6049812 | Bertram et al. | Apr 2000 | A |
6115642 | Brown et al. | Sep 2000 | A |
6128620 | Pissanos et al. | Oct 2000 | A |
6151031 | Atkins et al. | Nov 2000 | A |
6173270 | Cristofich et al. | Jan 2001 | B1 |
6330572 | Sitka | Dec 2001 | B1 |
6332125 | Callen et al. | Dec 2001 | B1 |
6343287 | Kumar et al. | Jan 2002 | B1 |
6401079 | Kahn et al. | Jun 2002 | B1 |
6425764 | Lamson | Jul 2002 | B1 |
6460060 | Maddalozzo, Jr. et al. | Oct 2002 | B1 |
6539379 | Vora et al. | Mar 2003 | B1 |
6553365 | Summerlin et al. | Apr 2003 | B1 |
6607389 | Genevie | Aug 2003 | B2 |
6622128 | Bedell et al. | Sep 2003 | B1 |
6738760 | Krachman | May 2004 | B1 |
6805351 | Nelson | Oct 2004 | B2 |
6832205 | Aragones et al. | Dec 2004 | B1 |
6839682 | Blume et al. | Jan 2005 | B1 |
6944597 | Callen et al. | Sep 2005 | B2 |
6966053 | Paris et al. | Nov 2005 | B2 |
6976083 | Baskey et al. | Dec 2005 | B1 |
6981210 | Peters et al. | Dec 2005 | B2 |
7016919 | Cotton et al. | Mar 2006 | B2 |
7076439 | Jaggi | Jul 2006 | B1 |
7082573 | Apparao et al. | Jul 2006 | B2 |
7103602 | Black et al. | Sep 2006 | B2 |
7104416 | Gasco et al. | Sep 2006 | B2 |
7107416 | Stuart et al. | Sep 2006 | B2 |
7120914 | Manthos et al. | Oct 2006 | B1 |
7127470 | Takeya | Oct 2006 | B2 |
7146388 | Stakutis et al. | Dec 2006 | B2 |
7162427 | Myrick et al. | Jan 2007 | B1 |
7197716 | Newell | Mar 2007 | B2 |
7206789 | Hurmiz et al. | Apr 2007 | B2 |
7225249 | Barry et al. | May 2007 | B1 |
7233959 | Kanellos et al. | Jun 2007 | B2 |
7236953 | Cooper et al. | Jun 2007 | B1 |
7240296 | Matthews et al. | Jul 2007 | B1 |
7249315 | Moetteli | Jul 2007 | B2 |
7281084 | Todd et al. | Oct 2007 | B1 |
7283985 | Schauerte et al. | Oct 2007 | B2 |
7284985 | Genevie | Oct 2007 | B2 |
7292965 | Mehta et al. | Nov 2007 | B1 |
7333989 | Sameshima et al. | Feb 2008 | B1 |
7386468 | Calderaro et al. | Jun 2008 | B2 |
7433832 | Bezos et al. | Oct 2008 | B1 |
7451155 | Slackman et al. | Nov 2008 | B2 |
7478096 | Margolus et al. | Jan 2009 | B2 |
7496534 | Olsen et al. | Feb 2009 | B2 |
7502891 | Shachor | Mar 2009 | B2 |
7512636 | Verma et al. | Mar 2009 | B2 |
7558853 | Alcorn et al. | Jul 2009 | B2 |
7580961 | Todd et al. | Aug 2009 | B2 |
7594082 | Kilday et al. | Sep 2009 | B1 |
7596541 | deVries et al. | Sep 2009 | B2 |
7614004 | Milic-Frayling et al. | Nov 2009 | B2 |
7617458 | Wassom, Jr. et al. | Nov 2009 | B1 |
7636886 | Wyle et al. | Dec 2009 | B2 |
7720825 | Pelletier et al. | May 2010 | B2 |
7730148 | Mace et al. | Jun 2010 | B1 |
7742940 | Shan et al. | Jun 2010 | B1 |
7774721 | Milic-Frayling et al. | Aug 2010 | B2 |
7778976 | D'Souza et al. | Aug 2010 | B2 |
7861166 | Hendricks | Dec 2010 | B1 |
7865817 | Ryan et al. | Jan 2011 | B2 |
7895229 | Paknad | Feb 2011 | B1 |
7912804 | Talwar et al. | Mar 2011 | B1 |
7962843 | Milic-Frayling et al. | Jun 2011 | B2 |
8073729 | Kisin et al. | Dec 2011 | B2 |
20010053967 | Gordon et al. | Dec 2001 | A1 |
20020007333 | Scolnik et al. | Jan 2002 | A1 |
20020010708 | McIntosh | Jan 2002 | A1 |
20020022982 | Cooperstone et al. | Feb 2002 | A1 |
20020035480 | Gordon et al. | Mar 2002 | A1 |
20020083090 | Jeffrey et al. | Jun 2002 | A1 |
20020091553 | Callen et al. | Jul 2002 | A1 |
20020091836 | Moetteli | Jul 2002 | A1 |
20020095416 | Schwols | Jul 2002 | A1 |
20020103680 | Newman | Aug 2002 | A1 |
20020108104 | Song et al. | Aug 2002 | A1 |
20020119433 | Callender | Aug 2002 | A1 |
20020120859 | Lipkin et al. | Aug 2002 | A1 |
20020123902 | Lenore et al. | Sep 2002 | A1 |
20020143595 | Frank et al. | Oct 2002 | A1 |
20020143735 | Ayi et al. | Oct 2002 | A1 |
20020147801 | Gullotta et al. | Oct 2002 | A1 |
20020162053 | Os | Oct 2002 | A1 |
20020178138 | Ender et al. | Nov 2002 | A1 |
20020184068 | Krishnan et al. | Dec 2002 | A1 |
20020184148 | Kahn et al. | Dec 2002 | A1 |
20030004985 | Kagimasa et al. | Jan 2003 | A1 |
20030014386 | Jurado | Jan 2003 | A1 |
20030018663 | Cornette et al. | Jan 2003 | A1 |
20030018693 | Rosenfeld et al. | Jan 2003 | A1 |
20030031991 | Genevie | Feb 2003 | A1 |
20030033295 | Adler et al. | Feb 2003 | A1 |
20030036994 | Witzig et al. | Feb 2003 | A1 |
20030046287 | Joe | Mar 2003 | A1 |
20030051144 | Williams | Mar 2003 | A1 |
20030069839 | Whittington et al. | Apr 2003 | A1 |
20030074354 | Lee et al. | Apr 2003 | A1 |
20030097342 | Whittingtom | May 2003 | A1 |
20030110228 | Xu et al. | Jun 2003 | A1 |
20030139827 | Phelps | Jul 2003 | A1 |
20030208689 | Garza | Nov 2003 | A1 |
20030229522 | Thompson et al. | Dec 2003 | A1 |
20040002044 | Genevie | Jan 2004 | A1 |
20040003351 | Sommerer et al. | Jan 2004 | A1 |
20040019496 | Angle et al. | Jan 2004 | A1 |
20040034659 | Steger | Feb 2004 | A1 |
20040039933 | Martin et al. | Feb 2004 | A1 |
20040060063 | Russ et al. | Mar 2004 | A1 |
20040068432 | Meyerkopf et al. | Apr 2004 | A1 |
20040078368 | Excoffier et al. | Apr 2004 | A1 |
20040088283 | Lissar et al. | May 2004 | A1 |
20040088332 | Lee et al. | May 2004 | A1 |
20040088729 | Petrovic et al. | May 2004 | A1 |
20040103284 | Barker | May 2004 | A1 |
20040133573 | Miloushev et al. | Jul 2004 | A1 |
20040138903 | Zuniga | Jul 2004 | A1 |
20040143444 | Opsitnick et al. | Jul 2004 | A1 |
20040187164 | Kandasamy et al. | Sep 2004 | A1 |
20040193703 | Loewy et al. | Sep 2004 | A1 |
20040204947 | Li et al. | Oct 2004 | A1 |
20040215169 | Li | Oct 2004 | A1 |
20040216039 | Lane et al. | Oct 2004 | A1 |
20040260569 | Bell et al. | Dec 2004 | A1 |
20050060175 | Farber et al. | Mar 2005 | A1 |
20050071251 | Linden et al. | Mar 2005 | A1 |
20050071284 | Courson et al. | Mar 2005 | A1 |
20050074734 | Randhawa | Apr 2005 | A1 |
20050114241 | Hirsch et al. | May 2005 | A1 |
20050144114 | Ruggieri et al. | Jun 2005 | A1 |
20050149307 | Gurpinar et al. | Jul 2005 | A1 |
20050160361 | Young | Jul 2005 | A1 |
20050165734 | Vicars et al. | Jul 2005 | A1 |
20050187813 | Genevie | Aug 2005 | A1 |
20050203821 | Petersen et al. | Sep 2005 | A1 |
20050203931 | Pingree et al. | Sep 2005 | A1 |
20050240578 | Biederman, Sr. et al. | Oct 2005 | A1 |
20050246451 | Silverman et al. | Nov 2005 | A1 |
20050283346 | Elkins, II et al. | Dec 2005 | A1 |
20060036464 | Cahoy et al. | Feb 2006 | A1 |
20060036649 | Simske et al. | Feb 2006 | A1 |
20060074793 | Hibbert et al. | Apr 2006 | A1 |
20060095421 | Nagai et al. | May 2006 | A1 |
20060126657 | Beisiegel et al. | Jun 2006 | A1 |
20060136435 | Nguyen et al. | Jun 2006 | A1 |
20060143248 | Nakano et al. | Jun 2006 | A1 |
20060143464 | Ananthanarayanan et al. | Jun 2006 | A1 |
20060149407 | Markham et al. | Jul 2006 | A1 |
20060149735 | DeBie et al. | Jul 2006 | A1 |
20060156381 | Motoyama | Jul 2006 | A1 |
20060156382 | Motoyama | Jul 2006 | A1 |
20060167704 | Nicholls et al. | Jul 2006 | A1 |
20060174320 | Maru et al. | Aug 2006 | A1 |
20060178917 | Merriam et al. | Aug 2006 | A1 |
20060184718 | Sinclair | Aug 2006 | A1 |
20060195430 | Arumainayagam et al. | Aug 2006 | A1 |
20060229999 | Dodell et al. | Oct 2006 | A1 |
20060230044 | Utiger | Oct 2006 | A1 |
20060235899 | Tucker | Oct 2006 | A1 |
20060242001 | Heathfield | Oct 2006 | A1 |
20070016546 | DeVorchik et al. | Jan 2007 | A1 |
20070048720 | Billauer | Mar 2007 | A1 |
20070061156 | Fry et al. | Mar 2007 | A1 |
20070061157 | Fry et al. | Mar 2007 | A1 |
20070078900 | Donahue | Apr 2007 | A1 |
20070099162 | Sekhar | May 2007 | A1 |
20070100857 | DeGrande et al. | May 2007 | A1 |
20070112783 | McCreight et al. | May 2007 | A1 |
20070118556 | Arnold et al. | May 2007 | A1 |
20070156418 | Richter et al. | Jul 2007 | A1 |
20070162417 | Cozianu et al. | Jul 2007 | A1 |
20070179829 | Laperi et al. | Aug 2007 | A1 |
20070179939 | O'Neil et al. | Aug 2007 | A1 |
20070203810 | Grichnik | Aug 2007 | A1 |
20070208690 | Schneider et al. | Sep 2007 | A1 |
20070219844 | Santorine et al. | Sep 2007 | A1 |
20070220435 | Sriprakash et al. | Sep 2007 | A1 |
20070245013 | Saraswathy et al. | Oct 2007 | A1 |
20070271230 | Hart et al. | Nov 2007 | A1 |
20070271308 | Bentley et al. | Nov 2007 | A1 |
20070271517 | Finkelman et al. | Nov 2007 | A1 |
20070282652 | Childress et al. | Dec 2007 | A1 |
20070288659 | Zakarian et al. | Dec 2007 | A1 |
20080033904 | Ghielmetti et al. | Feb 2008 | A1 |
20080034003 | Stakutis et al. | Feb 2008 | A1 |
20080059265 | Biazetti et al. | Mar 2008 | A1 |
20080059543 | Engel | Mar 2008 | A1 |
20080070206 | Perilli | Mar 2008 | A1 |
20080071561 | Holcombe | Mar 2008 | A1 |
20080086506 | DeBie et al. | Apr 2008 | A1 |
20080091283 | Balci et al. | Apr 2008 | A1 |
20080126156 | Jain et al. | May 2008 | A1 |
20080147642 | Leffingwell et al. | Jun 2008 | A1 |
20080148193 | Moetteli | Jun 2008 | A1 |
20080148346 | Gill et al. | Jun 2008 | A1 |
20080154969 | DeBie | Jun 2008 | A1 |
20080154970 | DeBie | Jun 2008 | A1 |
20080177790 | Honwad | Jul 2008 | A1 |
20080195597 | Rosenfeld et al. | Aug 2008 | A1 |
20080209338 | Li | Aug 2008 | A1 |
20080229037 | Bunte et al. | Sep 2008 | A1 |
20080262898 | Tonchev et al. | Oct 2008 | A1 |
20080294674 | Reztlaff et al. | Nov 2008 | A1 |
20080301207 | Demarest et al. | Dec 2008 | A1 |
20080312980 | Boulineau et al. | Dec 2008 | A1 |
20080319958 | Bhattacharya et al. | Dec 2008 | A1 |
20080319984 | Proscia et al. | Dec 2008 | A1 |
20090037376 | Archer et al. | Feb 2009 | A1 |
20090043625 | Yao | Feb 2009 | A1 |
20090064184 | Chacko et al. | Mar 2009 | A1 |
20090094228 | Bondurant et al. | Apr 2009 | A1 |
20090100021 | Morris et al. | Apr 2009 | A1 |
20090106815 | Brodie et al. | Apr 2009 | A1 |
20090119677 | Stefansson et al. | May 2009 | A1 |
20090132262 | Paknad | May 2009 | A1 |
20090150168 | Schmidt | Jun 2009 | A1 |
20090150866 | Schmidt | Jun 2009 | A1 |
20090150906 | Schmidt et al. | Jun 2009 | A1 |
20090157465 | Heathfield | Jun 2009 | A1 |
20090193210 | Hewett et al. | Jul 2009 | A1 |
20090241054 | Hendricks | Sep 2009 | A1 |
20090249179 | Shieh et al. | Oct 2009 | A1 |
20090249446 | Jenkins et al. | Oct 2009 | A1 |
20090254572 | Redlich et al. | Oct 2009 | A1 |
20090287658 | Bennett | Nov 2009 | A1 |
20100017756 | Wassom, Jr. et al. | Jan 2010 | A1 |
20100050064 | Liu et al. | Feb 2010 | A1 |
20100057418 | Li et al. | Mar 2010 | A1 |
20100070315 | Lu et al. | Mar 2010 | A1 |
20100088583 | Schachter | Apr 2010 | A1 |
20100250541 | Richards et al. | Sep 2010 | A1 |
20100250625 | Olenick et al. | Sep 2010 | A1 |
20100251109 | Jin et al. | Sep 2010 | A1 |
20110040748 | Williams et al. | Feb 2011 | A1 |
20110106773 | Smith et al. | May 2011 | A1 |
20110191344 | Jin et al. | Aug 2011 | A1 |
20130091175 | Richards et al. | Apr 2013 | A1 |
Number | Date | Country |
---|---|---|
2110781 | Oct 2009 | EP |
WO 2004092902 | Oct 2004 | WO |
Entry |
---|
Julie A. Lewis, “Digital Mountain—Where Data Resides—Data Discovery from the Inside Out”,2004 Digital Mountain, Inc, pp. 1-5. |
Judith Sears, E-Discovery:A Tech Tsunami Rolls in,Apr. 2006 pp. 1-7. |
Yukihisa Fujita et al., “Proposal and Evaluation of Metadata Management Method for eDiscovery”,2012 Service Research and Innovation Institute Global Conference, pp. 778-786. |
Sachindra Joshi et al., “Improving the Efficiency of Legal E-Discovery Services using Text Mining Techniques”,2011 Annual SRII Global Conference, pp. 448-458. |
Human Capital Mangement; “mySAP ERP Human Capital Management: Maximizing Workforce Potential”; retrieved from archive.org Aug. 18, 2009 www.sap.com, 1 page. |
Cohasset Associates, “White Paper: Compliance Requirements Assessment, IBM DB2 Records Manager and Record-Enabled Solutions”, Oct. 2004, 54 pgs. |
“HEI Records Management: Guidance on Developing a File Plan”, JISC infoNet, Jan. 2007, 7 pgs. |
www.pss-systems.com; retrieved from www. Archive.org any linkage dated Dec. 8, 2005, 130 pages. |
PSS Systems, Inc., Atlas LCC for Litigation, pp. 1-2, www.pss-systems.com (Feb. 2008); PSS Systems, Inc., Map Your Data Sources, www.pss-systems.com (Feb. 200*); PSS Systems, Inc., “PSS Systems Provides Legal Hold and Retention Enforcement Automation Solutions for File Shares, Documentum, and other Data Sources” (Feb. 2008). |
PSS Systems, Inc., Preservation Benchmarks for 2007 and Beyond, www.pss-systems.com, pp. 1-3 (2007). |
PSS Systems, Inc., “Industry Leader PSS Systems Launches Third Generation of Atlas Legal Hold and Retention Management Software”, pp. 1-2, www.pss-systems.com (Aug. 2007). |
PSS Systems, Inc., Litigation Communications and Collections, www.pss-systems.com (2006), retrieved online on Dec. 8, 2010 from archive.org, 1 page. |
Zhu, et al.; “Query Expansion Using Web Access Log Files”; Lecture Notes in Computer Science, 2005, vol. 3588/2005, pp. 686-695, Springer-Verlag, Berlin, Hedelberg. |
“Microsoft Computer Dictionary”, Microsoft Press, Fifth Edition, 2002, p. 499. |
Number | Date | Country | |
---|---|---|---|
20110320480 A1 | Dec 2011 | US |