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Searching through e discovery

Searching throughe-Discovery

Greg Buckles Julie Wade

April 9, 2009


Gotowebinartips
GoToWebinarTips

  • Click to hide or display the control panel on your screen

  • Type your question into the Question and Answer Panel. The moderator will notify the presenter of submitted questions


Thank you

Thank you!

Benchmark Legal Solutions 5101 Navigation,Houston, TX 77011

Telephone:713.528.0002

[email protected]


Greg buckles
Greg Buckles

  • Owner of Reason-eD LLC

  • 19 years of experience in forensics, discovery, record systems and software design to support Fortune 1000 companies.

  • Started career as forensic criminalist working for the Houston Police Department’s Crime Lab.

  • Mr. Buckles has worked for industry leaders such as Arnold, White & Durkhee, El Paso Corporation, Symantec Corporation and Attenex Corporation.


Julie wade
Julie Wade

  • Contract Paralegal with Donovan and Watkins,Marketing Consultant for In2itive Technologies.

  • Over 25 years experience in the legal profession, having worked on complex litigation cases in state, federal and multi-jurisdictional courts of law.

  • Received Advanced Certification in Electronic Discovery from Kroll OnTrack, Paralegal Certificate from University of North Texas.

  • Member of the State Bar of Texas Paralegal Division (Chair District CLE, 2008-09); Women in eDiscovery (Secretary, Houston Chapter, 2008-09); ALSP; AIIM.


Agenda
Agenda

  • Information Management Challenges

  • Court’s View of Search

  • Search Basics

  • Types of Search

  • Search Applications

  • Tips & Tricks

  • Resources


Structured and unstructured data
Structured and Unstructured Data

  • Structured data is data that sits in a database and can be mined and searched for information.

  • Unstructured data consists of emails, word documents, instant messages, blogs, PDFs, videos, and audio recordings – all data that falls outside the traditional database.

  • Merrill Lynch in 1998 estimated that 80% of all potentially usable business information originated in unstructured form.


Information management challenges
Information Management Challenges

  • Unstructured data resides in different applications, databases, email exchanges and archives.

  • Unstructured file-type data fastest growing area of all data types.

  • “not go into business to begin with” – structured or unstructured, how do you search that anyway?


Dealing with unstructured data
Dealing with unstructured data

  • Enterprise Content Management systems provide solutions to managing unstructured data content.

  • Data mining software and other text analytics are used to find patterns in, or otherwise interpret, unstructured information.

  • Common techniques for structuring text also involve manual tagging with metadata or crawling and indexing the data.


Getting a handle on file management
Getting a Handle on File Management

  • Litigation support and e-discovery are two examples of current applications requiring existing data to be indexed and searched – which is relatively easy to do with structured and semi-structured data, but has proven daunting with unstructured file-based data.

  • Paralegals must acquire their client’s data maps and interview custodians.


Court s view of search
Court’s View of Search

  • Peskoff v. Faber, 2006 WL 1933483 (D.D.C. July 11, 2006)

  • United States v. O’Keefe, No. 06-249 (D.D.C. Feb. 18, 2008).

  • Victor Stanley v. Creative Pipe, Civil Action No. MJG-06-2662 (D. Md. May 29, 2008).

  • Diabetes Centers of America, Inc. v. Healthpia America, Inc., 2008 WL 336382 (S.D. Tex. Feb. 5, 2008).


Peskoff v faber
Peskoff v. Faber

  • Defendant asserted computer disks contained “all electronic files and email there were,” but the production did not include 2 years worth of emails received or authored by the plaintiff from 2001 – 2003.

  • Court ordered defendant to search again and provide a detailed affidavit within 10 days specifying the nature of the search used in locating the responsive emails.


United states v o keefe
United States v. O’Keefe

First opinion to suggest judicial review of alleged search deficiencies requires expert testimony.

“Given this complexity, for lawyers and judges to dare opine that a certain search term or terms would be more likely to produce information than the terms that were used is truly to go where angels fear to tread.”


Victor stanley v creative pipe
Victor Stanley v. Creative Pipe

[A]ll keyword searches are not created equal…. The only prudent way to test the reliability of the keyword search is to perform some appropriate sampling…


D iabetes centers of america inc v healthpia america inc
Diabetes Centers of America, Inc. v. Healthpia America, Inc.

[S]anctions may be appropriate in other cases where evidence is lost because important searches were recklessly entrusted to untrained, unsupervised personnel.




Define the goal results
Define the Goal/Results

  • Inclusion vs. Exclusion, Find vs. Filter

  • Pinpoint identification of a particular document

  • Identify privileged documents

  • Identify responsive materials to discovery requests

  • Cost constraints & budgetary considerations

  • Identify who is best positioned to conduct and implement the search (vendor, paralegal)


Realistic search goals
Realistic Search Goals

ESI Collection

NO SEARCH IS PERFECT

  • False Negatives

Search Results

  • False Positives

  • True Positives


Structure the search
Structure the Search

  • Plan and structure the search

  • Identify the scope of data to be searched

  • Identify who will be performing the search

  • Identify the technology to be deployed

  • Identify the processes to be implemented


Execute the search
Execute the Search

  • All your definitional planning work is now put to the test

  • Monitor the search as it is being conducted and document the results captured from your search

  • Document the results of your data hits, data samples, and your other search protocols


Validate the search
Validate the Search

  • The validation steps you undertake will uphold the veracity of the search methods you deployed

  • Did the search include all the records that were to be searched

  • Did you achieve the goals established during the definitional phase?


Report
Report

  • Attorneys and client depend on the report to assess success and completeness.

  • Known exceptions and errors must be declared.

  • Reports are iterative, e.g., the results may require the search to be re-run.

  • Final process of search is the “Report.”


How search works
How Search Works

  • Build an Index

    • 10-30% additional storage

    • Static Copy

    • Run once – search many

  • Crawl/Streaming Text

    • No storage

    • Dynamic selection


Types of search methodologies
Types of Search Methodologies

  • Full Text

    • Boolean – Keywords

    • Natural Language – hidden risks

    • Expanded Words

      • Synonyms, grouping, related words, thesaurus

  • Concept Clustering – folders v. visual analysis


Keyword search normal parameters
Keyword Search Normal Parameters

  • The syntax in the search string

  • Use of the keywords with or without stemming

  • Use of keywords with certain wildcard specifications and their syntax

  • Case-sensitivity of keywords used

  • Consideration of target data sources


Assumed parameters
Assumed Parameters

  • Character coding of the text – UTF-8, UTF-16, CP1252, Unicode/WideChar etc.

  • Language of the keyword, to select appropriate stemming

  • Special character sets

  • Tokenization schemes


Phrase searches
Phrase Searches

  • Double quoting: “smoking gun email”

  • Noise words: ‘a’, ‘and’, ‘the’, ‘from’, and ‘because’

  • Boolean operators in phrases

  • Wildcard specifications: fail* & spec*

  • Truncation & Stemming specifications

  • Fuzzy searches, Booleans, Concept, Latent Semantic Indexing, Text Clustering, Bayesian Classifier, Concept Search Specification


Search applications
Search Applications

  • Desktop Search

    • X1, Google, Isys, dtSearch, WDS, OmniFind

  • Enterprise Search

    • IDOL, StoredIQ, Recommind, Kazeon, Symantec

  • Processing Platforms

    • Cracker, Discover-e, Extractiva

  • Review Platforms

    • Summation, Concordance, Attenex

  • Forensic Search


Tips and tricks
Tips and Tricks

  • Foreign Languages

  • Exception Handling

  • Email Address Issues

  • Partial Non-Indexed File Types/Locations

  • Term Frequency Lists

  • Analytics and Sampling


Resources
Resources

  • EDRM Search Guide

  • Text REtrieval Conference

  • George L. Paul & Jason R. Baron, Information Inflation: Can the Legal System Adapt?, 13 RICH. J.L. & TECH. 10 (2007)

  • The Sedona Conference, Best Practices Commentary on the Use of Search and Information Retrieval, 8 THE SEDONA CONF. J. 189 (2008)

  • Information Organization & Access (IOA) Certificate Program – www.aiim.org


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