1. Automated Process of Electronic Discovery October 4, 2010

2. Complaint Document Acquisition DepositionsReview Discovery Begins Collection & EDD Processing Discovery Closes Produce & Share 95% Settle Electronic Discovery Trial Coding & Scanning

3. Electronic Discovery Legal Issues Chain of Custody/Data Integrity –“Chain of Custody” Requires that “the one who offers real evidence…must account for the custody of the evidence from the moment in which it reaches his custody until the moment in which it is offered in evidence.” Black’s Law Dictionary, page 156 (6 th ed. Abr. 1991) –Inexpert handling of electronic media (e.g., open, print, & scan) has serious drawbacks Human error Missing data or inadvertent changes Time to produce No detailed audits

4. Electronic Discovery Legal Issues Electronic Marginalia –Simple spreadsheets and word processing files contain an array of formatting elements including: comments, headers, hidden rows/columns –Counsel should proactively ensure the process used provides at a minimum: hidden rows and columns uncovered comments exposed and converted passwords broken blank pages eliminated

5. Electronic Discovery Terms Metadata Media Tape Restoration Text Extraction Forensics/Collection De-duplication Data Culling

6. Electronic Discovery Process Receive Data Process Reduce Search Convert Package Burn

7. 1 - Receive Data Identify locations of all data and prescribe systematic uniform collection of data Media is sent in many formats –CD –DVD –DLT –DAT Tape Media is signed in and a strict chain of custody process begins

8. 2 - Index Data Extract Unzip Index Copy Rename (uniform fashion – while maintaining data integrity) Capture valuable info. (metadata) Each file is examined to detect any changes to file extension – possible smoking gun/file –another reason why you cannot “just print them”

9. 3 - Reduce the Data Set De-duplication option –Our process ensures accuracy and integrity MD5 Hash – “bit” level count Bit Level most accurate!! Filtering Data –Narrow by a specific “date range” –Uses metadata to eliminate files outside of the discoverable date range

10. 4 - Keyword Searching Select keywords or phrases to narrow your search/discovery Advanced searching using Boolean, proximity, etc. Responsive files are flagged and continue through the process Non-responsive files are still preserved Saves Hours Saves $s

11. 5 - Convert the Data Full Text of files is extracted Hidden information is uncovered –rows, columns, changes (if enabled) –embedded comments exposed –“electronic marginalia” Files converted to Tiff or PDF images

12. 6 - Package the Data Batchload Application Begins Images bundled and a customized load file is created for uploading to client document management system –e.g., Summation, Concordance, etc.

13. 7 - Burn & Return Final (of several) quality checks performed CDs Burned Data Integrity still intact CDs are shipped to client Data remains on system

14. Key Considerations Automation = Integrity & Speed –Provides Data Integrity – Chain of Custody – Cannot “Just Print Them Out” –Allows De-duping, Filtering, & Searching to Reduce Data Set –Uncovers Hidden & Meaningful Data Examines all files for hidden file types Hidden Rows/Columns Uncovered Comments are Exposed Metadata Uncovered & Searchable Electronic Marginalia

15. FILE NAMEFILE TYPEMD5 HASHFILE CREATEDLAST MODIFIEDSIZE oeold.xmlXMLDOCbfd4f3f518d771ed1e163a74360c878210/07/09 11:25:57AM 260 WMSDKNS.XMLXMLDOC80fa7e4e669210f3fb8f2675c13b339b10/07/09 11:26:18AM10/07/09 11:26:34AM10,191 08_Video.wpla6adb26ddc7d2ea50760f857239bc57110/07/09 11:26:14AM 1,020 03_Music_rate.wpl28b57c7cdd412e5bc7d04eccefe6c28910/07/09 11:26:13AM 1,267 05_Pictures.wpl109071511d084d628bbf736c8bace7a210/07/09 11:26:14AM 797 07_TV.wpl81ed540e1204e3237f63da49df05a7d510/07/09 11:26:14AM 1,040 10_All_Music.wpl31f2fcd102025f1c452573311f03f17710/07/09 11:26:14AM 1,063 OrangeCircles.jpgJPEG2e9fa5e6ffb09ccddf228cd27f047b2410/07/09 11:26:01AM10/07/09 02:03:52PM6,381 Notebook.jpgJPEG5132c7884dd9cff1365f61fec897e29e10/07/09 11:26:01AM10/07/09 02:03:52PM2,950 Monet.jpgJPEGad9197afb34f4c6120f573685e619d7310/07/09 11:26:01AM10/07/09 02:03:52PM2,209 HandPrints.jpgJPEG5078fbc5b4f3404d23ac213883ed902110/07/09 11:26:01AM10/07/09 02:03:52PM4,222 ShadesOfBlue.jpgJPEG754a2ff52ee7556dcb6a242a0950b06810/07/09 11:26:01AM10/07/09 02:03:52PM4,734

16. Administration & Management Utility for Litigation Support  Litigation pipeline database and reports  Database Utilities (productions, attachments, comparisons, OCR, etc) Discovery Pipeline show the legacy of each document. The information starts by grouping in the Case Container list. Case Documents are organized in Case Load Volumes. Actual document history is tracked from initial collection to final evidence production. Doc. details are linked.

17.  Scan, classify, and upload to centrally stored and organized repository  Access from anywhere, at any time  Perform complex searches, annotation and redaction with any document  Streamline productions for opposing counsel

18. Document review progress & status reports Each matter is given reports on its own home page. Brief summary of document review status. “Executive Summary” overview. Forecasting project completion dates and project progress are shown in %’s Graphs are used to provide a visual aid to see your project’s “Big Picture” status.

19. Equivio Near-Duplication  Reduce document review time by 15% to 20% - directly impacting the bottom line costs The Problem:  No clear method to organize and allocate documents across reviewers  Documents are reviewed multiple times by different reviewers  High risk of different coding among similar documents Near-Duping – Step 1  Group the near-duplicates  Identify the differences among the near-duplicates Near-Duping – Step 2  Assign near-dupe sets for coherent review to reviewers  Reviewers prioritize and review only the differences  Apply coding to entire near- dupe sets where appropriate Less Cost Less Time Less Errors

20. Equivio eMail Threads  Reduce eMail review time by up to 70% - directly impacting the bottom line costs The Problem:  No clear method to identify eMail threads, originals, replies  eMails are reviewed multiple times  Extremely difficult to identify where missing eMails exist  High risk of different coding among similar documents eMail Threads – Step 1  Group into eMail sets eMail Threads – Step 2  Build tree structure  Identify missing links  Suppress duplicates  Focus on inclusives Less Cost Less Time Less Errors

21. Equivio eMail Threads  Review “conversation threads”, identifying missing links  Review only differences