Extracting and capturing knowledge found in social software tools

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My presentation from the Knowledge capture and retention in law firms workshop in London, November 2008

My presentation from the Knowledge capture and retention in law firms workshop in London, November 2008

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  • 1. Extracting and capturing knowledge found in social software tools Neil Richards KM Consultant www.knowledgethoughts.com
  • 2. Today?
    • How law firms are using web2.0
    Quality control Indexing, archiving and distributing Extracting structured data
  • 3. How law firms are using web2.0?
  • 4. No single tool
  • 5.
    • Social networking
    • Wikis
    • Blogs
    • RSS
    • Tagging
  • 6. Different needs Client knowledge Idea sharing Communications Managing Projects Team knowledge Subject knowledge Firm knowledge
  • 7. Examples: Magic circle  team wikis, practice wikis and “Pedias" Dewey & Leboeuf  wikis, blogs, rss & social bookmarking The Rosen Law Firm  wikis for reports, profile pages, communications Goodwin Proctor  wikis for managing projects, clients & legal knowledge Dykema  RSS, communication, information distribution Over 25% of the AMLaw 200  Client facing blogs
  • 8. Extracting structured information
  • 9.
    • garbage in  garbage out
    • To extract useful knowledge you first have to have some
  • 10. It requires the contributions of many
  • 11. But lawyers are often too busy…
  • 12. … or doing other things
  • 13. Nobody likes filling out forms…
  • 14.
    • … and structured mark-up is too complex.
    '''Berlin''' is the capital of [[capital of::Germany]] and also its largest city; the city is now home to [[population::3,391,407]], down from a peak of 4.5 million before [[World War II]]. It measures [[area::891.69 square kilometers]] and has the coordinates [[coordinates::52°31'N; 13°24'E]]. Berlin is located in the north of [[located in::Germany]] [[Category:City]][[Category:sample pages]] {{#ask: [[Category:City]] [[located in::Germany]] | ?population | ?area#km² = Size in km² }}
  • 15. Submitting knowledge needs to be simple
  • 16. Order from chaos Tags / categories Favourites Social ratings Usage stats Enrichment Data analysis Social platforms
  • 17. Quality control
  • 18. Monitor key content Track changes Watch usage
  • 19.
    • Have some content PSL & Partner approved
    • Embed visual indicators of quality
    • Make the names of contributors visible
    • Content-appropriate levels of review
  • 20. Indexing and archiving Low volume – high value. You can’t index everything. Take usage into account Where possible, track “expiry dates” and have a process to retire knowledge
  • 21.
    • Distribution
  • 22. Additional information & reference material http://www.knowledgethoughts.com/blog/?page_id=215 Photo credits http://www.sxc.hu/photo/787433 http://www.sxc.hu/photo/938865 http://www.sxc.hu/photo/604247 http://www.sxc.hu/photo/989421 http://www.sxc.hu/photo/334026 http://www.sxc.hu/photo/1088897 http://www.sxc.hu/photo/304293 http://www.sxc.hu/photo/292426 http://www.sxc.hu/photo/253955 http://www.sxc.hu/photo/1005156 http://www.sxc.hu/photo/839415 http://www.sxc.hu/photo/765550 http://www.sxc.hu/photo/590355 http://www.sxc.hu/photo/468027 http://www.sxc.hu/photo/761191 http://www.sxc.hu/photo/821903 http://www.sxc.hu/photo/1032278 http://www.sxc.hu/photo/182201 http://www.sxc.hu/photo/819168 http://www.sxc.hu/photo/866529 http://www.sxc.hu/photo/647502 http://www.sxc.hu/photo/428182 http://www.sxc.hu/photo/575060 http://www.sxc.hu/photo/970189 http://www.sxc.hu/photo/1080889 http://www.sxc.hu/photo/949308 http://www.sxc.hu/photo/228778 Neil Richards KM Consultant www.knowledgethoughts.com