SharePoint 2010 Findability

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How Smartlogic Semaphore improves Findability in SharePoint 2010, through content enrichment and semantic search enhancement.

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  • SharePoint 2010 Findability

    1. 1. Metadata and Findability in SharePoint 2010<br />Dave Maskell<br />European Sales Manager<br />dave.maskell@smartlogic.com<br />
    2. 2. Smartlogic Semaphore<br />Semaphore improves Findability in SharePoint and other applications, through automated content classification and search enhancement.<br />Findability: brings people and knowledge together. Enables users to find the information they seek and promotes content to the relevant audience.<br />
    3. 3. Customer Benefit Examples<br />Internal Knowledge Management<br />SharePoint<br />Inform/Serve Customers<br />Monetise Information<br />
    4. 4. Knowledge Management Trends<br />Increasing demand for “information about information”<br /><ul><li>Support knowledge workers
    5. 5. Records Management
    6. 6. Legal (e.g. eDiscovery, Freedom Of Information, Audit)</li></ul>Systems consolidation<br /><ul><li>From departmental to enterprise repositories</li></ul>Little editorial control<br /><ul><li>People are encouraged/compelled to upload everything
    7. 7. No SEO on the intranet</li></li></ul><li>Goal<br />Knowledge<br />Information<br />Hidden<br />Data<br />Unknown<br />Knowing What You have<br />The British Museum has a collection of 7 million items, of which 50,000 are on display<br />US museums have 146 million items, 53% of which are not catalogued<br />Surfaced<br />Knowledge<br />You know where it is<br />Value<br />Information<br />You know it’s somewhere<br />Data<br />You don’t know it exists<br />
    8. 8. Free-Text SearchThe “long tail” problem<br />20% of content “wins” 80% of searches<br />Free-Text search is a blunt instrument<br />Heavy documents float, light ones sink!<br />What are the “right questions”?<br />
    9. 9. Language and Meaning<br />Aboutness- what is it?<br />Terminology - what do we call it?<br /><ul><li>Netbook
    10. 10. Laptop
    11. 11. Notebook
    12. 12. Apple
    13. 13. MacBook</li></ul>Ambiguity – what did you mean?<br />
    14. 14. Precision and Recall<br />When is a Lift not a Lift?<br />Poor Precision – “false positives”<br />Document mentions Lift once in 100 pages – it is not about Lifts<br />Wrong kind of lift – document about “valve lift” systems for cars<br />Poor Recall – “hidden knowledge”<br />Oops!<br />
    15. 15. Investing in Context<br />Broader Topics<br />Related Topics<br />Narrower<br />Topics<br />Topic-Relevant<br />Content<br />
    16. 16. Failure of Context<br />
    17. 17. The Value of Metadata<br />Standardisation and Context<br /><ul><li>Standardise Naming & Context:
    18. 18. Preferred Term = Elevator
    19. 19. Synonym = Lift</li></ul>Taxonomy/Ontology<br />Term Set<br />Model Metadata<br /><ul><li>Tag Content for “aboutness”
    20. 20. Based on weight of evidence
    21. 21. Some documents are about Elevators others are about Valve-lift Systems</li></ul>Classification<br />Enterprise Keywords<br />Item Metadata<br />Search<br />Enhancement<br /><ul><li>Improve Search Recall:
    22. 22. “Did you mean elevator”?
    23. 23. Improve Search Precision
    24. 24. Filter by Metadata
    25. 25. Improve Search Recall & Precision:
    26. 26. Search by Metadata
    27. 27. Guided Discovery</li></li></ul><li>SharePoint 2010<br />“Metadata 1.0”<br />
    28. 28. SharePoint Metadata 1.0Structural attributes: Type, Author, Date etc.<br />
    29. 29. SharePoint Metadata 1.0“Aboutness” (Term Store & Keywords)<br />
    30. 30. SharePoint Metadata 1.0Column Filters<br />
    31. 31. SharePoint Metadata 1.0Free-text search, topic refinement<br />
    32. 32. Metadata 1.0 Challenges<br />“…many departments and organisations in the public sector arbitrarily pick a convenient high-level term from IPSV* to classify all their web pages just so that they can tick the box…” <br /><ul><li>Human tagging is costly, unenforceable, inconsistent
    33. 33. Who tags legacy/imported documents?
    34. 34. Changed documents do not get re-tagged
    35. 35. Term Set changes make metadata obsolete
    36. 36. Untagged or badly-tagged documents are “filtered out” or waste user time/attention</li></ul>*IPSV = UK Integrated Public Sector Vocabulary (3,000 terms)<br />
    37. 37. Semaphore for<br />SharePoint 2010<br />Complete, consistent, correct Metadata<br />Improved Search Experience<br />
    38. 38. Complete, consistent, correct MetadataClassification Requirements<br /><ul><li>Automatic Classification is essential for complete, consistent and correct Metadata.
    39. 39. Automatic Classification needs to include a number of capabilities:
    40. 40. Quality Classification, not just keyword matching
    41. 41. Classification triggered on document creation and update
    42. 42. Ability for users to add/delete tags
    43. 43. Protect manually tagged documents from reclassification
    44. 44. Bulk Classification of libraries</li></li></ul><li>Complete, consistent, correct MetadataModel-Driven Classification<br />How would YOU decide whether a document is ABOUT Apollo 11?<br />Encapsulate this knowledge map in a formal rule<br />
    45. 45. Complete, consistent, correct MetadataModel-Driven Classification<br />
    46. 46. Complete, consistent, correct MetadataUser Classification<br />
    47. 47. Complete, consistent, correct MetadataProtecting User Choices<br />
    48. 48. Improved Search Experience“Did you mean?”<br />
    49. 49. Improved Search ExperienceSemantic Enhancement<br />Metadata Search<br />Related Topics<br />Recommended Links<br />
    50. 50. Improved Search ExperienceRelated Topics – Guided Discovery<br />
    51. 51. Solution Architecture<br />SharePoint 2010 and SharePoint 2007<br />Smartlogic Semaphore<br />Content<br />Classification<br />Term Store<br />Management<br />Search<br />Enhancement<br />Other Enterprise Applications?<br />
    52. 52. Enterprise-Wide Hunger for Context…<br />Enterprise<br />Search<br />Content<br />Management<br />Portal<br />Infrastructure<br />Document<br /> Management<br />?<br />?<br />?<br />?<br />SharePoint<br />?<br />Records<br />Management<br />?<br />Publishing<br />Systems<br />?<br />Digital<br />Asset<br />Management<br />?<br />?<br />?<br />Process <br />Management &<br />Workflow<br />eDiscovery<br />
    53. 53. …requiring an Enterprise Solution<br />Enterprise<br />Search<br />Content<br />Management<br />Portal<br />Infrastructure<br />Document<br /> Management<br />Subject<br />Geography<br />Process<br />Metadata<br />(Tags)<br />Model<br />(Ontology)<br />SharePoint<br />Records<br />Management<br />Publishing<br />Systems<br />Digital<br />Asset<br />Management<br />Semaphore EnterpriseSemanticPlatform<br />Process <br />Management &<br />Workflow<br />eDiscovery<br />
    54. 54. Case Study:<br />UK National Health Service<br />
    55. 55. Medical Information for PatientsSharePoint with GSA Search<br />Topic Filters<br />Recommendation<br />
    56. 56. Interactive Term Map - Visualisation<br />
    57. 57. Interactive Term Map - Visualisation<br />
    58. 58. Social Media Content Classification<br />
    59. 59. Medical Information for PractitionersFAST ESP across 100+ web sites<br />
    60. 60. Conclusions<br />The SharePoint 2010 Term Store and Managed Metadata are a first step towards improved Findability. <br />To be effective, Metadata must be complete, consistent and correct. This requires automation.<br />SharePoint 2010 findability can be further improved through semantic concepts like “did you mean?”, metadata searching and related topic suggestions.<br />The same is true for other applications that use unstructured content.<br />Smartlogic Semaphore provides an enterprise platform for metadata management and semantic search enhancement.<br />
    61. 61. Thank You<br />Dave Maskell<br />European Sales Manager<br />dave.maskell@smartlogic.com<br />

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