This eLaw presentation was done at Thursday March 14 I at café ‘t Keizertje, Kaiserstraat in Leiden. The presentation contains a brief overview of big data analytics for legal fact finding.

1. BIG DATA ANALYTICS FOR LEGAL FACT-FINDING
Also known as eDiscovery
Prof dr ir Jan C. Scholtes
CSO, ZyLAB
Text-Mining, Maastricht University

2. MORE TRANSPARENCY

3. WE LEAVE DIGITAL TRACES EVERYWHERE
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• Email
• File shares
• SharePoint
• Cloud
• Social media
• Mobile devices
• Other content
management
systems
• …

4. OTHERS KNOW THAT AS WELL …..
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• Unhappy clients
• Upset employees
• Regulatory
agencies
• Auditors
• Investigators
• Citizens
• Media

5. AND THEN COMES AN INFORMATION REQUEST…
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• Audit or Internal
Investigation
• Litigation & Arbitration
• Patents, Contracts &
HR Disputes
• M&A, refinancing and
restructuring
• Bankruptcy
• Subject Access
Requests
eDiscovery

6. SLIDE / 6
• Data Breach
Investigation
• GDPR Compliance PII
check
• Subject Access
Requests & Right to
be Forgotten
• M&A Virtual Data
Room Anonymization
• GDPR compliant
(encrypted) storage

7. CHALLENGES IN EDISCOVERY
Different origin:
• Legal
• Process
• Data
• Human

8. WHY IS LEGAL SEARCH DIFFERENT?
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• Completeness
• Incomplete
search
• Find unknown
unknowns
• Defensibility
• Transparency

10.  Leer de computer wat je
zoekt aan de hand van
voorbeelden.
 Nuttig bij het vinden van
gerelateerde documenten:
alle documenten die leiden
tot een bepaald eind
document.
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MACHINE LEARNING (SUPERVISED)

11. ANALYTICS FOR DECISION MAKING
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12. WHAT, WHO, WHY, WHEN, WHERE, HOW, HOW
MUCH, BY WHICH MEANS, …?
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13. NEXT STEP: ANOMALY DETECTION
Σ(Φ)