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Electronic discovery

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631:) had become the standard document review method for almost two decades, native format review has increased in popularity as a method for document review since around 2004. Because it requires the review of documents in their original file formats, applications and toolkits capable of opening multiple file formats have also become popular. This is also true in the ECM (Enterprise Content Management) storage markets, which converge quickly with ESI technologies. 768:
stabilizing the TAR tool. The Court would have liked the City to use TAR in this case. But the Court cannot, and will not, force the City to do so. There may come a time when TAR is so widely used that it might be unreasonable for a party to decline to use TAR. We are not there yet. Thus, despite what the Court might want a responding party to do, Sedona Principle 6 controls. Hyles' application to force the City to use TAR is DENIED.
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Learning Algorithms to distinguish Relevant from Non-Relevant Documents, based on Training Examples Coded as Relevant or Non-Relevant by the Subject Matter Experts(s), while other TAR methods derive systematic Rules that emulate the expert(s)’ decision-making process. TAR processes generally incorporate Statistical Models and/or Sampling techniques to guide the process and to measure overall system effectiveness.
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As compared to eDiscovery, information governance as a discipline is relatively new. Yet, there is traction for convergence. eDiscovery—a multi-billion-dollar industry—is rapidly evolving, ready to embrace optimized solutions that strengthen cybersecurity (for cloud computing). Since the early 2000s,
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as "the specification of decision rights and an accountability framework to encourage desirable behavior in the valuation, creation, storage, use, archival, and deletion of information. It includes the processes, roles, standards, and metrics that ensure the effective and efficient use of information
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Given the complexities of modern litigation and the wide variety of information systems on the market, electronic discovery often requires IT professionals from both the attorney's office (or vendor) and the parties to the litigation to communicate directly to address technology incompatibilities and
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document) with a load file for use in image-based discovery review database applications. Increasingly, database review applications have embedded native file viewers with TIFF capabilities. With both native and image file capabilities, it could either increase or decrease the total necessary storage
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New technology is able to address problems created by the first approach by running an application entirely in memory on each custodian machine and only pushing responsive data across the network. This process has been patented and embodied in a tool that has been the subject of a conference paper.
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or sensitive information since redaction tools for images are traditionally more mature and easier to apply on uniform image types by non-technical people. Efforts to redact similarly petrified PDF files by incompetent personnel have removed redacted layers and exposed redacted information, such as
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During the review phase, documents are reviewed for responsiveness to discovery requests and for privilege. Different document review platforms and services can assist in many tasks related to this process, including rapidly identifying potentially relevant documents and culling documents according
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LLC lawsuit. Throughout the case, the plaintiff claimed that the evidence needed to prove the case existed in emails stored on UBS' own computer systems. Because the emails requested were either never found or destroyed, the court found that they were more likely to exist than not. The court found
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Any data that is stored in an electronic form may be subject to production under common eDiscovery rules. This type of data has historically included email and office documents (spreadsheets, presentations, documents, PDFs, etc.) but can also include photos, video, instant messaging, collaboration
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techniques are often employed to ensure a complete identification of data sources. Since the scope of data can be overwhelming or uncertain in this phase, attempts are made to reasonably reduce the overall scope during this phase - such as limiting the identification of documents to a certain date
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Regardless of the method adopted to collect and process data there are few resources available for practitioners to evaluate the different tools. This is an issue due to the significant cost of eDiscovery solutions. Notwithstanding the limited options for obtaining trial licences for the tools, a
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A process for Prioritizing or Coding a Collection of Documents using a computerized system that harnesses human judgments of one or more Subject Matter Expert(s) on a smaller set of Documents and then extrapolates those judgments to the remaining Document Collection. Some TAR methods use Machine
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To be clear, the Court believes that for most cases today, TAR is the best and most efficient search tool. That is particularly so, according to research studies (cited in Rio Tinto), where the TAR methodology uses continuous active learning ("CAL") which eliminates issues about the seed set and
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Displaying and explaining evidence before audiences (at depositions, hearings, trials, etc.). The idea is that the audience understands the presentation, and non-professionals can follow the interpretation. Clarity and ease of understanding are the focus here. The native form of data needs to be
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Once documents have been preserved, collection can begin. The collection is the transfer of data from a company to its legal counsel, who will determine the relevance and disposition of data. Some companies that deal with frequent litigation have software in place to quickly place legal holds on
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notice whenever litigation is reasonably anticipated will be deemed grossly negligent. This holding brought additional focus to the concepts of legal holds, eDiscovery, and electronic preservation. Custodians who are in possession of potentially relevant information or documents are identified.
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Qualitative analysis of the content discovered in the collection phase and after being reduced by the preprocessing phase. The Evidence is looked at in context. Correlation analysis or contextual analysis to extract structured information relevant to the case. Structuring like Timelineing or
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The Information Governance Reference Model (IGRM) illustrates the relationship between key stakeholders and the Information Lifecycle and highlights the transparency required to enable effective governance. The updated IGRM v3.0 emphasizes that Privacy & Security Officers are essential
496:. Litigators may review material from ediscovery in one of several formats: printed paper, "native file", or a petrified, paper-like format, such as PDF files or TIFF images. Modern document review platforms accommodate the use of native files and allow for them to be converted to TIFF and 454:
Documents are turned over to opposing counsel based on agreed-upon specifications. Often this production is accompanied by a load file, which is used to load documents into a document review platform. Documents can be produced either as native files or in a petrified format (such as
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In relation to the second approach, despite self-collection being a hot topic in eDiscovery, concerns are being addressed by limiting the involvement of the custodian to simply plugging in a device and running an application to create an encrypted container of responsive documents.
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A number of different people may be involved in an electronic discovery project: lawyers for both parties, forensic specialists, IT managers, and records managers, amongst others. Forensic examination often uses specialized terminology (for example, "image" refers to the
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from the native files. Various data culling techniques are employed during this phase, such as deduplication and de-NISTing. Sometimes native files will be converted to a petrified, paper-like format (such as PDF or TIFF) at this stage to allow for easier redaction and
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Voicemail is often discoverable under electronic discovery rules. Employers may have a duty to retain voicemail if there is an anticipation of litigation involving that employee. Data from voice assistants like Amazon Alexa and Siri have been used in criminal cases.
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Clustering into Topics can be done. An example structure could be the analysis from a client-based perspective; here, each investigator looks at one agent included in the evidence additional Patterns like discussions or network analysis around people can be done.
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to various criteria (such as keyword, date range, etc.). Most review tools also make it easy for large groups of document review attorneys to work on cases, featuring collaborative tools and batches to speed up the review process and eliminate work duplication.
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Structured data are most often produced in delimited text format. When the number of tables subject to discovery is large or relationships between the tables are of essence, the data are produced in native database format or as a database backup file.
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eDiscovery practitioners have developed skills and techniques that can be applied to information governance. Organizations can apply the lessons learned from eDiscovery to accelerate their path to a sophisticated information governance framework.
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significant barrier to the evaluation process is creating a suitable environment in which to test such tools. Adams suggests the use of the Microsoft Deployment Lab which automatically creates a small virtual network running under HyperV
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To establish authenticity, some archiving systems apply a unique code to each archived message or chat. The systems prevent alterations to original messages, messages cannot be deleted, and unauthorized persons cannot access the messages.
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agree on production formats. Failure to get expert advice from knowledgeable personnel often leads to additional time and unforeseen costs in acquiring new technology or adapting existing technologies to accommodate the collected data.
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a legal hold has been issued by unknowing technicians performing their regular duties. Many companies are deploying software that properly preserves data across the network to combat this trend, preventing inadvertent data spoliation.
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since there may be multiple formats and files associated with each individual native file. Deployment, storage, and best practices are becoming especially critical and necessary to maintain cost-effective strategies.
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While attorneys involved in case litigation try their best to understand the companies and organizations they represent, they may fail to understand the policies and practices that are in place in the company's
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that while the corporation's counsel directed that all potential discovery evidence, including emails, be preserved, the staff that the directive applied to did not follow through. This resulted in significant
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The formalized changes to the Federal Rules of Civil Procedure in December 2006 and 2007 effectively forced civil litigants into a compliance mode with respect to their proper retention and management of
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tools, text (SMS), messaging apps, social media, ephemeral messaging, Internet of things (smart devices like Fitbits, smart watches, Alexa Alexa, Apple Siri, Nest), databases, and other file types.
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abstracted, visualized, and broad into context for the presentation. The results of the analysis should be the subject of the presentation. The clear documentation should provide reproducibility.
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Structured data typically resides in databases or datasets. It is organized in tables with columns, rows, and defined data types. The most common are Relational Database Management Systems (
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Electronic information is considered different from paper information because of its intangible form, volume, transience and persistence. Electronic information is usually accompanied by
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created a category for electronic records that, for the first time, explicitly named emails and instant message chats as likely records to be archived and produced when relevant.
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approaches to infer the relevance (or responsiveness, privilege, or other categories of interest) of ESI. Technology-assisted review has evolved rapidly since its inception
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effective December 1, 2006, and December 1, 2015. In addition, state law and regulatory agencies increasingly also address issues relating to electronic discovery. In
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Following research studies indicating its effectiveness, TAR was first recognized by a U.S. court in 2012, by an Irish court in 2015, and by a U.K. court in 2016.
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and Practice Direction 31B on Disclosure of Electronic Documents apply. Other jurisdictions around the world also have rules relating to electronic discovery.
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stakeholders. This topic is addressed in an article entitled "Better Ediscovery: Unified Governance and the IGRM," published by the American Bar Association.
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certain custodians when an event (such as legal notice) is triggered and begin the collection process immediately. Other companies may need to call in a
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that is not found in paper documents and that can play an important part as evidence (e.g. the date and time a document was written could be useful in a
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Petrification involves the conversion of native files into an image format that does not require the use of native applications. This is useful in the
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A duty to preserve begins upon the reasonable anticipation of litigation. Data identified as potentially relevant during preservation is placed in a
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In a typical collection process large volumes of data are transmitted across the network for indexing and this impacts normal business operations
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that where the producing party wants to utilize TAR for document review, courts will permit it." In a subsequent matter, the same court stated,
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Traditionally, electronic discovery vendors had been contracted to convert native files into TIFF images (for example, 10 images for a 10-page
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The identification phase is when potentially responsive documents are identified for further analysis and review. In the United States, in
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expert to prevent the spoliation of data. The size and scale of this collection are determined by the identification phase.
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The number of concurrent custodian machines that can be processed is severely limited due to the network bandwidth required
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https://espace.curtin.edu.au/bitstream/handle/20.500.11937/93974/Adams%20RB%202023%20Public.pdf?sequence=1&isAllowed=y
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Perspectives on Predictive Coding and Other Advanced Search and Review Technologies for the Legal Practitioner (ABA 2016)
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Technology-assisted review (TAR)—also known as computer-assisted review or predictive coding—involves the application of
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is an ubiquitous diagram that represents a conceptual view of these stages involved in the ediscovery process.
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Technology-assisted review in ediscovery can be more effective and more efficient than manual review
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case). The preservation of metadata from electronic documents creates special challenges to prevent
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Currently the two main approaches for identifying responsive material on custodian machines are:
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tools to help document review attorneys more accurately identify potentially relevant documents.
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Best practices recommendations & principles for addressing electronic document production
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IT administrators are generally unhappy with the installation of agents on custodian machines
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Grossman, Maura R., and Gordon V. Cormack. "A tour of technology-assisted review."
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In the United States, at the federal level, electronic discovery is governed by
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Anecdotal evidence for this emerging trend points to the business value of
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During the processing phase, native files are prepared to be loaded into a
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The indexing process is not 100% reliable in finding responsive material
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platform. Often, this phase also involves the extraction of text and
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Electronically stored information (Federal Rules of Civil Procedure)
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Journal of the Association for Information Science and Technology
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Grossman and Cormack define TAR in Federal Courts Law Review as:
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Gricks, Thomas C. III; Ambrogi, Robert J. (November 17, 2015).
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In relation to the first approach there are several issues:
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Qualcomm v. Broadcom: Implications for Electronic Discovery
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PRACTICE DIRECTION 31B – DISCLOSURE OF ELECTRONIC DOCUMENTS
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Federal Judicial Center: Materials on Electronic Discovery
1111:"Yet Another Redacting Failure]. Schneier on Security" 27:
Discovery in legal proceedings seeking digital information
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Irish Bank Resolution Corporation Limited v. Sean Quinn
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Grossman, Maura R.; Cormack, Gordon V. (January 2013).
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social security numbers and other private information.
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Although petrifying documents to static image formats (
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High Court of Justice Chancery Division, U.K. (2016).
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TAR Case Law Primer Public Comment Version August 2016
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and agreed-upon processes, often involving review for
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Richard, Adams; Graham, Mann; Valerie, Hobbs (2017).
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before data are turned over to the requesting party.
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or ESI). Electronic discovery is subject to rules of
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department. As a result, some data may be destroyed
795:in enabling an organization to achieve its goals." 101:. Unsourced material may be challenged and removed. 519:One type of preservation problem arose during the 858:Legal governance, risk management, and compliance 424:Modern processing tools can also employ advanced 974:PART 31 - DISCLOSURE AND INSPECTION OF DOCUMENTS 668:of digital media), which can lead to confusion. 1280:"A brief history of technology assisted review" 893:Handbook of Digital Forensics and Investigation 765: 759:Recently a U.S. court has declared that it is " 1524:American Bar Association article on eDiscovery 277:requests, where the information sought is in 186:The examples and perspective in this article 8: 1529:eDiscovery with AI (Artificial intelligence) 1489:Article (2012). Ledergerber, Marcus (ed.). 550:, attorneys can be brought before the bar. 345:Electronic Discovery Reference Model (EDRM) 64:Learn how and when to remove these messages 1493:. American Bar Association. Archived from 1403:Pyrrho Investments Ltd v. MWB Property Ltd 885: 883: 480:Types of electronically stored information 1355:Richmond Journal of Law & Technology 242:Learn how and when to remove this message 224:Learn how and when to remove this message 161:Learn how and when to remove this message 879: 782:Convergence with information governance 1163: 1152: 365:ruled that failure to issue a written 1014:"Case Law AJ Holdings v. IP Holdings" 7: 1085:Kincaid, Jason (February 11, 2009). 890:Various (2009). Eoghan Casey (ed.). 99:adding citations to reliable sources 554:Databases and other structured data 1445:Continuous Active Learning for TAR 1321:Roitblat, Herbert; Kershaw, Anne. 925:"Federal Rules of Civil Procedure" 25: 929:LII / Legal Information Institute 868:Telecommunications data retention 540:electronically stored information 283:electronically stored information 45:This article has multiple issues. 514:Federal Rules of Civil Procedure 488:Also included in ediscovery is " 321:Federal Rules of Civil Procedure 273:, government investigations, or 177: 75: 34: 896:. Academic Press. p. 567. 86:needs additional citations for 53:or discuss these issues on the 1443:Practical Law Journal (2016). 694:Alternative collection methods 1: 269:in legal proceedings such as 1388:High Court, Ireland (2015). 1216:"Digital Forensics Services" 976:, accessed 11 September 2022 813:Catalyst Repository Systems 743:supervised machine learning 500:-stamped for use in court. 200:, discuss the issue on the 1580: 1456:Sedona Conference (2007). 1379:Retrieved August 13, 2016. 1333:(1). Hoboken, New Jersey: 737:Technology-assisted review 275:Freedom of Information Act 1447:Retrieved August 14, 2016 1434:Retrieved August 14, 2016 1421:Retrieved August 14, 2016 1405:Retrieved August 13, 2016 1392:Retrieved August 13, 2016 1359:Retrieved August 14, 2016 1311:Retrieved August 17, 2016 1253:Federal Courts Law Review 1288:American Bar Association 1202:10.4225/75/5a838d3b1d27f 1129:"The Sedona Conference®" 1133:thesedonaconference.org 522:Zubulake v. UBS Warburg 358:Zubulake v. UBS Warburg 1559:Information governance 1432:Hyles v. New York City 1162:Cite journal requires 853:Information governance 788:information governance 779: 770: 281:(often referred to as 110:"Electronic discovery" 1286:. Chicago, Illinois: 1054:accessdate=2014-10-19 985:Ministry of Justice, 972:Ministry of Justice, 833:Early case assessment 774: 512:'s amendments to the 375:range or custodians. 333:Civil Procedure Rules 1284:Law Technology Today 843:File hosting service 572:Microsoft SQL Server 548:Qualcomm v. Broadcom 255:Electronic discovery 206:create a new article 198:improve this article 188:may not represent a 95:improve this article 1307:Sedona Conference. 1173:CS1 maint: others ( 1064:Sullivan, Casey C. 1016:. January 13, 2015. 504:Electronic messages 1564:Records management 1463:2016-07-06 at the 1375:2013-03-10 at the 510:U.S. Supreme Court 323:(FRCP), including 1554:Digital forensics 1430:S.D.N.Y. (2016). 1419:Rio Tinto v. Vale 1370:Moore v. Publicis 1368:S.D.N.Y. (2012). 1220:www.ricoh-usa.com 1109:(June 26, 2006). 1002:. March 28, 2016. 943:"2015 Amendments" 903:978-0-12-374267-4 790:(IG), defined by 619:Reporting formats 398:digital forensics 339:Stages of process 331:, Part 31 of the 329:England and Wales 279:electronic format 252: 251: 244: 234: 233: 226: 208:, as appropriate. 171: 170: 163: 145: 68: 16:(Redirected from 1571: 1506: 1505: 1503: 1502: 1486: 1480: 1473: 1467: 1454: 1448: 1441: 1435: 1428: 1422: 1417:S.D.N.Y (2015). 1415: 1406: 1399: 1393: 1386: 1380: 1366: 1360: 1353: 1347: 1346: 1344: 1342: 1318: 1312: 1305: 1299: 1298: 1296: 1294: 1275: 1269: 1268: 1266: 1264: 1250: 1241: 1235: 1230: 1224: 1223: 1212: 1206: 1205: 1185: 1179: 1178: 1171: 1165: 1160: 1158: 1150: 1143: 1137: 1136: 1125: 1119: 1118: 1103: 1097: 1096: 1082: 1076: 1075: 1073: 1072: 1061: 1055: 1049: 1043: 1042: 1040: 1039: 1024: 1018: 1017: 1010: 1004: 1003: 996: 990: 983: 977: 970: 964: 963: 961: 960: 954: 948:. Archived from 947: 939: 933: 932: 921: 915: 914: 912: 910: 887: 863:Machine learning 761:black letter law 588:Microsoft Access 544:summary judgment 363:Shira Scheindlin 247: 240: 229: 222: 218: 215: 209: 181: 180: 173: 166: 159: 155: 152: 146: 144: 103: 79: 71: 60: 38: 37: 30: 21: 1579: 1578: 1574: 1573: 1572: 1570: 1569: 1568: 1544:Civil procedure 1534: 1533: 1515: 1510: 1509: 1500: 1498: 1488: 1487: 1483: 1474: 1470: 1465:Wayback Machine 1455: 1451: 1442: 1438: 1429: 1425: 1416: 1409: 1400: 1396: 1387: 1383: 1377:Wayback Machine 1367: 1363: 1354: 1350: 1340: 1338: 1335:Wiley-Blackwell 1320: 1319: 1315: 1306: 1302: 1292: 1290: 1277: 1276: 1272: 1262: 1260: 1248: 1243: 1242: 1238: 1231: 1227: 1214: 1213: 1209: 1194:Research Online 1187: 1186: 1182: 1172: 1161: 1151: 1145: 1144: 1140: 1127: 1126: 1122: 1107:Schneier, Bruce 1105: 1104: 1100: 1084: 1083: 1079: 1070: 1068: 1063: 1062: 1058: 1050: 1046: 1037: 1035: 1026: 1025: 1021: 1012: 1011: 1007: 998: 997: 993: 984: 980: 971: 967: 958: 956: 952: 945: 941: 940: 936: 923: 922: 918: 908: 906: 904: 889: 888: 881: 876: 848:Forensic search 828:Discovery (law) 809: 784: 739: 696: 691: 689:Emerging trends 661: 621: 612: 604:data warehouses 556: 506: 494:"native" format 482: 473: 452: 443: 434: 410:document review 406: 393: 381: 353: 341: 287:civil procedure 248: 237: 236: 235: 230: 219: 213: 210: 195: 182: 178: 167: 156: 150: 147: 104: 102: 92: 80: 39: 35: 28: 23: 22: 15: 12: 11: 5: 1577: 1575: 1567: 1566: 1561: 1556: 1551: 1546: 1536: 1535: 1532: 1531: 1526: 1521: 1514: 1513:External links 1511: 1508: 1507: 1481: 1468: 1449: 1436: 1423: 1407: 1394: 1381: 1361: 1348: 1313: 1300: 1270: 1236: 1225: 1207: 1180: 1164:|journal= 1138: 1120: 1098: 1077: 1056: 1044: 1019: 1005: 991: 978: 965: 934: 916: 902: 878: 877: 875: 872: 871: 870: 865: 860: 855: 850: 845: 840: 835: 830: 825: 823:Data retention 820: 815: 808: 805: 783: 780: 738: 735: 722: 721: 718: 715: 712: 695: 692: 690: 687: 660: 657: 648:Microsoft Word 620: 617: 611: 608: 555: 552: 505: 502: 481: 478: 472: 469: 451: 448: 442: 439: 433: 430: 419:bates-labeling 405: 402: 392: 389: 380: 377: 352: 351:Identification 349: 340: 337: 250: 249: 232: 231: 192:of the subject 190:worldwide view 185: 183: 176: 169: 168: 83: 81: 74: 69: 43: 42: 40: 33: 26: 24: 14: 13: 10: 9: 6: 4: 3: 2: 1576: 1565: 1562: 1560: 1557: 1555: 1552: 1550: 1547: 1545: 1542: 1541: 1539: 1530: 1527: 1525: 1522: 1520: 1517: 1516: 1512: 1497:on 2016-10-11 1496: 1492: 1485: 1482: 1478: 1472: 1469: 1466: 1462: 1459: 1453: 1450: 1446: 1440: 1437: 1433: 1427: 1424: 1420: 1414: 1412: 1408: 1404: 1398: 1395: 1391: 1385: 1382: 1378: 1374: 1371: 1365: 1362: 1358: 1352: 1349: 1336: 1332: 1328: 1324: 1317: 1314: 1310: 1304: 1301: 1289: 1285: 1281: 1274: 1271: 1258: 1254: 1247: 1240: 1237: 1234: 1229: 1226: 1221: 1217: 1211: 1208: 1203: 1199: 1195: 1191: 1184: 1181: 1176: 1169: 1156: 1148: 1142: 1139: 1134: 1130: 1124: 1121: 1116: 1112: 1108: 1102: 1099: 1094: 1093: 1088: 1081: 1078: 1067: 1060: 1057: 1053: 1048: 1045: 1034: 1030: 1023: 1020: 1015: 1009: 1006: 1001: 995: 992: 988: 982: 979: 975: 969: 966: 955:on 2017-06-12 951: 944: 938: 935: 930: 926: 920: 917: 905: 899: 895: 894: 886: 884: 880: 873: 869: 866: 864: 861: 859: 856: 854: 851: 849: 846: 844: 841: 839: 836: 834: 831: 829: 826: 824: 821: 819: 816: 814: 811: 810: 806: 804: 800: 796: 793: 789: 781: 778: 773: 769: 764: 762: 757: 754: 752: 748: 744: 736: 734: 730: 726: 719: 716: 713: 710: 709: 708: 705: 702: 699: 693: 688: 686: 682: 679: 675: 669: 667: 659:Common issues 658: 656: 652: 649: 644: 641: 637: 632: 630: 626: 618: 616: 609: 607: 605: 601: 597: 593: 590:, structured 589: 585: 581: 577: 573: 569: 565: 561: 553: 551: 549: 545: 541: 535: 531: 530:against UBS. 529: 524: 523: 517: 515: 511: 508:In 2006, the 503: 501: 499: 495: 491: 486: 479: 477: 470: 468: 466: 462: 458: 449: 447: 440: 438: 431: 429: 427: 422: 420: 415: 411: 403: 401: 399: 390: 388: 386: 378: 376: 373: 368: 364: 360: 359: 350: 348: 346: 338: 336: 334: 330: 326: 322: 318: 313: 311: 307: 303: 298: 296: 292: 288: 284: 280: 276: 272: 268: 264: 260: 256: 246: 243: 228: 225: 217: 207: 203: 199: 193: 191: 184: 175: 174: 165: 162: 154: 143: 140: 136: 133: 129: 126: 122: 119: 115: 112: â€“  111: 107: 106:Find sources: 100: 96: 90: 89: 84:This article 82: 78: 73: 72: 67: 65: 58: 57: 52: 51: 46: 41: 32: 31: 19: 1499:. Retrieved 1495:the original 1484: 1476: 1471: 1452: 1439: 1426: 1397: 1384: 1364: 1351: 1339:. Retrieved 1330: 1326: 1316: 1303: 1291:. Retrieved 1283: 1273: 1261:. Retrieved 1256: 1252: 1239: 1228: 1219: 1210: 1193: 1183: 1155:cite journal 1141: 1132: 1123: 1115:Schneier.com 1114: 1101: 1090: 1080: 1069:. Retrieved 1059: 1047: 1036:. Retrieved 1032: 1022: 1008: 994: 981: 968: 957:. Retrieved 950:the original 937: 928: 919: 907:. Retrieved 892: 801: 797: 785: 775: 771: 766: 758: 755: 750: 740: 731: 727: 723: 706: 703: 700: 697: 683: 677: 670: 662: 653: 645: 633: 622: 613: 557: 547: 536: 532: 520: 518: 507: 487: 483: 474: 471:Presentation 463:) alongside 453: 444: 435: 423: 407: 394: 382: 379:Preservation 372:Data mapping 356: 354: 342: 314: 299: 265:) refers to 262: 258: 254: 253: 238: 220: 211: 187: 157: 151:October 2012 148: 138: 131: 124: 117: 105: 93:Please help 88:verification 85: 61: 54: 48: 47:Please help 44: 1027:Logikcull. 818:Data mining 666:acquisition 263:e-discovery 1538:Categories 1501:2016-08-21 1341:August 14, 1293:August 14, 1263:August 14, 1092:TechCrunch 1071:2018-06-08 1038:2018-06-08 959:2017-06-27 874:References 747:rule-based 640:privileged 600:data marts 592:flat files 450:Production 404:Processing 391:Collection 385:legal hold 367:legal hold 325:amendments 317:common law 310:spoliation 271:litigation 259:ediscovery 121:newspapers 50:improve it 18:EDiscovery 1033:Logikcull 909:27 August 636:redaction 584:FileMaker 528:sanctions 306:copyright 295:relevance 291:privilege 267:discovery 202:talk page 56:talk page 1461:Archived 1373:Archived 807:See also 586:Pro and 580:Teradata 490:raw data 465:metadata 441:Analysis 426:analytic 414:metadata 302:metadata 214:May 2011 196:You may 1479:(2016). 792:Gartner 606:, etc. 598:files, 568:IBM Db2 361:, Hon. 135:scholar 1337:: 1–10 900:  753:2005. 627:& 578:, and 576:Sybase 564:Oracle 432:Review 257:(also 137:  130:  123:  116:  108:  1549:Email 1249:(PDF) 953:(PDF) 946:(PDF) 751:circa 678:after 610:Audio 560:RDBMS 498:Bates 204:, or 142:JSTOR 128:books 1343:2016 1295:2016 1265:2016 1175:link 1168:help 911:2010 898:ISBN 629:JPEG 625:TIFF 461:TIFF 343:The 293:and 114:news 1198:doi 745:or 638:of 596:XML 459:or 457:PDF 261:or 97:by 1540:: 1410:^ 1331:61 1329:. 1325:. 1282:. 1255:. 1251:. 1218:. 1196:. 1192:. 1159:: 1157:}} 1153:{{ 1131:. 1113:. 1089:. 1031:. 927:. 882:^ 674:IT 602:, 594:, 574:, 570:, 566:, 467:. 421:. 312:. 59:. 1504:. 1345:. 1297:. 1267:. 1257:7 1222:. 1204:. 1200:: 1177:) 1170:) 1166:( 1135:. 1117:. 1095:. 1074:. 1041:. 962:. 931:. 913:. 245:) 239:( 227:) 221:( 216:) 212:( 194:. 164:) 158:( 153:) 149:( 139:· 132:· 125:· 118:· 91:. 66:) 62:( 20:)

Index

EDiscovery
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talk page
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verification
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adding citations to reliable sources
"Electronic discovery"
news
newspapers
books
scholar
JSTOR
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worldwide view
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talk page
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discovery
litigation
Freedom of Information Act
electronic format
electronically stored information
civil procedure
privilege
relevance
metadata

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