Semantic User Interfaces Ian Dickinson Epimorphics Ltd [email_address] @ephemerian
Agenda Context Semantic UI  patterns Cautions
Framing: who, what & why? “ Semantic user interface” ... For semantic professionals End-user value Triples inside
We want to help users to: <ul><li>do new things, or
perform their current tasks more ... </li><ul><li>easily
accurately
cheaply
reliably </li></ul><li>technology is not the goal </li></ul>
Patterns
Travel travails
Pattern: independent identities <ul><li>the  identities  of  things we are interested in  are not tied to the application
identities can be: </li><ul><li>shared
copied
disambiguated
merged </li></ul></ul>
Let's visit ... Berlin <ul><li>which is ... </li><ul><li>within Land Berlin
which is within FDR </li></ul><li>also which </li><ul><li>contains Mitte district
which contains Museum Island
which contains the Pergamon  Museum </li></ul></ul>
Pattern: use “spine” datasets <ul><li>relate identifiers to widely-used: </li><ul><li>datasets
ontologies
taxonomies </li></ul><li>dbpedia, geonames, umbel, ... many more
present users with richer descriptions </li></ul>
Location, location, integration
R&D R&D
 
Pattern: visualizing data linkages <ul><li>heterogeneous data
reduce cognitive workload
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Semantic User Interfaces

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Talk given at Semantic Business 2011, London, UK

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  • often visually impressive but hard to use low-level structure not conceptual structure sometimes useful “meaningful” at the right level of description: the natural view of something may be much more compact than the “sum of triples” graphs can show heterarchical relations spatial location &amp; proximity should be meaningful - what does it mean to be near or far from a given node? “management” console!
  • Always needed? No, but can be very powerful. With great power comes difficult problems that need solving! And perhaps a key for leaving the walled garden ad hoc data juggling: forcing users to use a spreadsheet, notebook or back-of-an-envelope to remember and keep track of investigation elements and criteria
  • Semantic User Interfaces

    1. 1. Semantic User Interfaces Ian Dickinson Epimorphics Ltd [email_address] @ephemerian
    2. 2. Agenda Context Semantic UI patterns Cautions
    3. 3. Framing: who, what & why? “ Semantic user interface” ... For semantic professionals End-user value Triples inside
    4. 4. We want to help users to: <ul><li>do new things, or
    5. 5. perform their current tasks more ... </li><ul><li>easily
    6. 6. accurately
    7. 7. cheaply
    8. 8. reliably </li></ul><li>technology is not the goal </li></ul>
    9. 9. Patterns
    10. 10. Travel travails
    11. 11. Pattern: independent identities <ul><li>the identities of things we are interested in are not tied to the application
    12. 12. identities can be: </li><ul><li>shared
    13. 13. copied
    14. 14. disambiguated
    15. 15. merged </li></ul></ul>
    16. 16. Let's visit ... Berlin <ul><li>which is ... </li><ul><li>within Land Berlin
    17. 17. which is within FDR </li></ul><li>also which </li><ul><li>contains Mitte district
    18. 18. which contains Museum Island
    19. 19. which contains the Pergamon Museum </li></ul></ul>
    20. 20. Pattern: use “spine” datasets <ul><li>relate identifiers to widely-used: </li><ul><li>datasets
    21. 21. ontologies
    22. 22. taxonomies </li></ul><li>dbpedia, geonames, umbel, ... many more
    23. 23. present users with richer descriptions </li></ul>
    24. 24. Location, location, integration
    25. 25. R&D R&D
    26. 27. Pattern: visualizing data linkages <ul><li>heterogeneous data
    27. 28. reduce cognitive workload
    28. 29. show relationships </li><ul><li>common identifiers
    29. 30. common properties </li></ul><li>support sense-making, choice forming, decisions </li></ul>
    30. 31. The ubiquitous tag
    31. 32. Pattern: linked-data tags <ul><li>re-usable identity -> re-usable tag
    32. 33. retain free-form tags </li><ul><li>but relate to shared vocabularies </li></ul><li>auto-tagging
    33. 34. semantic query </li></ul>
    34. 35. Triples: visible or invisible? vs.
    35. 36. Pattern: hide low-level structure <ul><li>users don't think in triples
    36. 37. visible objects should represent meaningful things
    37. 38. stick & bubble graphs: limited utility </li></ul>
    38. 39. Where am I? Where next?
    39. 40. Facets: here & next step filters where we are now? choices for the next facet search step
    40. 41. Pivoting: stepping to adjacent topic all presidents all presidents' spouses
    41. 42. Related items or an associated topic an alternate spelling “ discover”
    42. 43. Pattern: rich navigation <ul><li>explicit </li><ul><li>current location
    43. 44. history (and bookmarks)
    44. 45. choices for next step
    45. 46. collections of results
    46. 47. signifiers </li></ul><li>create actions from discovered data </li></ul>
    47. 48. Pattern: generate additional structure <ul><li>Vocabularies and ontologies provide opportunities to add structure </li><ul><li>synonyms
    48. 49. broader / narrower
    49. 50. meronyms </li></ul><li>change user's perspective </li></ul>
    50. 51. Pattern: follow a link <ul><li>allow user to view any link reference
    51. 52. display the content as usefully as possible </li></ul>
    52. 53. Design dilemma <ul><li>Flexible UX: </li><ul><li>open
    53. 54. user-directed
    54. 55. extensible </li></ul></ul><ul><li>Classic UX: </li><ul><li>constraints
    55. 56. simplicity
    56. 57. coherence </li></ul></ul>
    57. 58. Semantic UX redux <ul><li>Semantics: powerful techniques giving users </li><ul><li>flexibility
    58. 59. autonomy
    59. 60. maybe an end to ad hoc data juggling </li></ul><li>Needs a suitably hard problem </li><ul><li>complex
    60. 61. messy
    61. 62. open-ended
    62. 63. long-lived
    63. 64. … </li></ul></ul>
    64. 65. Conclusion <ul><li>Sampling of patterns for semantic UI's </li><ul><li>identities not tied to applications
    65. 66. rich navigation
    66. 67. visualise interrelationships
    67. 68. create actions from found data </li></ul><li>Let's find some interesting problems! </li></ul>
    68. 69. Acknowledgements <ul>I would like to thank the following for their kind permission to use content: <ul><li>photos (CC-by license) </li><ul><li>Flipchart – Tim Cayne s http://www.flickr.com/photos/timcaynes/637988053/
    69. 70. Dunes pattern – Mollivan Jon http://www.flickr.com/photos/mollivan_jon/347366159/
    70. 71. Wooden bench – MaretH. http://www.flickr.com/photos/maret1983/6057025004/
    71. 72. Tree climbing – drainhook http://www.flickr.com/photos/drainhook/4643191611/
    72. 73. Tug of war – Eric Skiff http://www.flickr.com/photos/ericskiff/517809478/
    73. 74. Headlington Shark – DaveyBot http://www.flickr.com/photos/davemorris/144525103/ </li></ul><li>app screenshots </li><ul><li>Oliver O'Brien (@oobr) – London Bike Share bikes.oobrien.com/
    74. 75. Talis – BIS research funding consulting.talis.com/case-study/bis-research-funding-explorer/
    75. 76. Marti Hearst (U. Berkeley) – Flamenco facet browser flamenco.berkeley.edu/
    76. 77. David Hyunh (Google) – Parallax browser www.freebase.com/labs/parallax/
    77. 78. Christina Scheutz (Serials Solutions) – AquaBrowser © aqua.queenslibrary.org/
    78. 79. Ian Davis (Talis) – LinkSailor linksailor.com </li></ul></ul></ul>
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