Transcript CCTI

Automated Process
of
Electronic Discovery
October 19, 2009
Coding &
Scanning
Document
Acquisition
Complaint
Discovery
Begins
Review
Photocopy
Produce &
Share
95% Settle
Depositions
Discovery
Closes
Electronic Discovery
Trial
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 (6th ed. Abr. 1991)
– Inexpert handling of electronic media
(e.g., open, print, & scan) has serious
drawbacks
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Human error
Missing data or inadvertent changes
Time to produce
No detailed audits
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:
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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
Reduce
Index
Convert
Search
Burn
Package
1 - Receive Data
 Identify locations of all data and prescribe
systematic uniform collection of data
 Media is sent in many formats
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CD
DVD
DLT
DAT Tape
 Media is signed in and a strict chain of
custody process begins
2 - Index Data
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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”
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 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
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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
Less Time
The Problem:
Near-Duping – Step 1
Near-Duping – Step 2
 No clear method to organize
and allocate documents
across reviewers
 Group the near-duplicates
 Assign near-dupe sets for
coherent review to reviewers
 Documents are reviewed
multiple times by different
reviewers
 High risk of different coding
among similar documents
 Identify the differences
among the near-duplicates
 Reviewers prioritize and
review only the differences
 Apply coding to entire neardupe sets where appropriate
Less Errors
Less Cost
Equivio eMail Threads
 Reduce eMail review time by up to 70% - directly impacting
the bottom line costs
Less Time
The Problem:
eMail Threads – Step 1
eMail Threads – Step 2
 No clear method to identify
eMail threads, originals,
replies
 Group into eMail sets
 Build tree structure
 eMails are reviewed multiple
times
 Extremely difficult to identify
where missing eMails exist
 High risk of different coding
among similar documents
 Identify missing links
 Suppress duplicates
 Focus on inclusives
Less Errors
Less Cost
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
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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