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