Upload
toril
View
38
Download
0
Tags:
Embed Size (px)
DESCRIPTION
Automated Process of Electronic Discovery March 8, 2010. Coding & Scanning. Document Acquisition. 95% Settle. Review. Depositions. Complaint. Discovery Begins. Discovery Closes. Trial. Photocopy. Produce & Share. Electronic Discovery. Electronic Discovery Legal Issues. - PowerPoint PPT Presentation
Citation preview
Automated Processof
Electronic Discovery
March 8, 2010
Complaint
Document Acquisition DepositionsReview
DiscoveryBegins
PhotocopyDiscovery
ClosesProduce &
Share
95% Settle
Electronic Discovery
Trial
Coding &Scanning
Electronic Discovery Legal IssuesChain 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 (6th 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
Electronic Discovery Legal IssuesElectronic 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
Electronic Discovery Terms
Metadata
Media
Tape Restoration
Text Extraction
Forensics/Collection
De-duplication
Data Culling
Electronic Discovery Process
Receive Data
Index
Reduce
Search
Convert
Package
Burn
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
2 - Index DataExtractUnzip IndexCopyRename (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”
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
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
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
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.
7 - Burn & Return
Final (of several) quality checks
performed
CDs Burned
Data Integrity still intact
CDs are shipped to client
Data remains on system
Key ConsiderationsAutomation = 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
FILE NAME FILE TYPE MD5 HASH FILE CREATED LAST MODIFIED SIZE
oeold.xml XMLDOC bfd4f3f518d771ed1e163a74360c8782 10/07/09 11:25:57AM 10/07/09 11:25:57AM 260
WMSDKNS.XML XMLDOC 80fa7e4e669210f3fb8f2675c13b339b 10/07/09 11:26:18AM 10/07/09 11:26:34AM 10,191
08_Video.wpl a6adb26ddc7d2ea50760f857239bc571 10/07/09 11:26:14AM 10/07/09 11:26:14AM 1,020
03_Music_rate.wpl 28b57c7cdd412e5bc7d04eccefe6c289 10/07/09 11:26:13AM 10/07/09 11:26:13AM 1,267
05_Pictures.wpl 109071511d084d628bbf736c8bace7a2 10/07/09 11:26:14AM 10/07/09 11:26:14AM 797
07_TV.wpl 81ed540e1204e3237f63da49df05a7d5 10/07/09 11:26:14AM 10/07/09 11:26:14AM 1,040
10_All_Music.wpl 31f2fcd102025f1c452573311f03f177 10/07/09 11:26:14AM 10/07/09 11:26:14AM 1,063
OrangeCircles.jpg JPEG 2e9fa5e6ffb09ccddf228cd27f047b24 10/07/09 11:26:01AM 10/07/09 02:03:52PM 6,381
Notebook.jpg JPEG 5132c7884dd9cff1365f61fec897e29e 10/07/09 11:26:01AM 10/07/09 02:03:52PM 2,950
Monet.jpg JPEG ad9197afb34f4c6120f573685e619d73 10/07/09 11:26:01AM 10/07/09 02:03:52PM 2,209
HandPrints.jpg JPEG 5078fbc5b4f3404d23ac213883ed9021 10/07/09 11:26:01AM 10/07/09 02:03:52PM 4,222
ShadesOfBlue.jpg JPEG 754a2ff52ee7556dcb6a242a0950b068 10/07/09 11:26:01AM 10/07/09 02:03:52PM 4,734
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.
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.
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
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 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
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 CostLess Cost
Less TimeLess Time
Less ErrorsLess Errors
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
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 1
Group into eMail sets
eMail Threads – Step 2
Build tree structure
Identify missing links
Suppress duplicates
Focus on inclusives
eMail Threads – Step 2
Build tree structure
Identify missing links
Suppress duplicates
Focus on inclusives
Less CostLess Cost
Less TimeLess Time
Less ErrorsLess Errors
Equivio eMail Threads Review “conversation threads”, identifying missing links
Review only differences
doeDiscovery’s compare function allows you to sort and de-dup each document set for coding.
Choose your criteria for the compare.
Select the action you want to use from a drop-down list.
Using EquivioTM as the basis for the custom compare functions increases its power.
The Compare Features in doeDiscovery… Help you find the pertinent data faster!
Summation Enterprise Enhancements
PrivAlert– Search within database for potentially privileged documents using key
terms– Documents that match have a field populated with the term that is found
Compare– Allows sets of docs, grouped by either similarity or parent/child
relationship, to be coded in one pass….time savings up to 30% Search
– Ability to save advanced searches & data “snapshots”– Expand search based on similarity or parent/child relationship– Verify consistency of coding among similar docs– Create review sets using Equisets– Enable Transaction Level audit capabilities
Reports– Pipeline reports to be able to see real time status of your review