Razorbase Examples Part 2

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A demonstration of the benefits of Linked Data in a typical web browsing context

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  • Razorbase Examples Part 2

    1. 1. Razorbase Examples pt. 2 (Linked Data at Work) By Sherman Monroe
    2. 2. Razorbase • A browser for exploring the Linked Open Data cloud using OpenLink Facets API Live demo available at http://www.razorbase.com
    3. 3. Task 1: Find a friend
    4. 4. Results set
    5. 5. Find a friend • Found some things named Kingsley Idehen, surely our subject in this set
    6. 6. Find a friend • Found some things named Kingsley Idehen, surely our subject in this set • Now use the Alternative Ids button to pivot to his alternative identifications and profiles on the web
    7. 7. Task 2: Browse friend’s dataspaces • Let’s take a look at what our friend is up to on the web
    8. 8. This looks like some kind of music related profile
    9. 9. Here’s his LinkedIn profile, hmm… let’s look more
    10. 10. Looks like a Rating/Reviews site…
    11. 11. … let’s pull this profile
    12. 12. Subject page for Kingsley Idehen’s revyu.com profile
    13. 13. List of filters for this subject
    14. 14. View all Information available about subject
    15. 15. Browse friend’s dataspace: Sparse results • Only a few pieces of info for subject
    16. 16. Browse friend’s dataspace: Sparse results • Only a few pieces of info for subject • Let’s look at the Reverse Connections for subject
    17. 17. Browse friend’s dataspace • Reverse connections are connections to other things that go the opposite direction
    18. 18. Browse friend’s dataspace • Reverse connections are connections to other things that go the opposite direction • An example would be Blue a color of the sky
    19. 19. Browse friend’s dataspace • Reverse connections are connections to other things that go the opposite direction • An example would be Blue a color of the sky • We see here that the subject has reviews
    20. 20. Add information to the view
    21. 21. Add information to the view (same function)
    22. 22. Let’s scroll page right
    23. 23. New column added
    24. 24. Task 3: Lookup other mutual reviews • We have pulled a review the subject made about Facebook. Let’s pivot to what others have to say about Facebook.
    25. 25. Task 3: Lookup other mutual reviews • We have pulled a review the subject made about Facebook. Let’s pivot to what others have to say about Facebook. • Use the Mutual Connections button
    26. 26. Let’s scroll page left
    27. 27. Mutual Connections • The Mutual Connections have returned all reviewers who created this review, so it makes sense that our subject is the only result
    28. 28. Mutual Connections • The Mutual Connections have returned all reviewers who created this review, so it makes sense that our subject is the only result • The question is, how do we find other reviews about Facebook from here?
    29. 29. Mutual Connections • The Mutual Connections have returned all reviewers who created this review, so it makes sense that our subject is the only result • The question is, how do we find other reviews about Facebook from here? • Let’s see if the review itself has an explicit connection to Facebook
    30. 30. Mutual Connections • The Mutual Connections have returned all reviewers who created this review, so it makes sense that our subject is the only result • The question is, how do we find other reviews about Facebook from here? • Let’s see if the review itself has an explicit connection to Facebook • From there, we can pivot to other reviews
    31. 31. Let’s return to the reviews
    32. 32. Let’s return to the reviews (same function)
    33. 33. Mutual Connections • The primaryTopic information sounds useful
    34. 34. Mutual Connections • We now have the topics of the reviews
    35. 35. Mutual Connections • We now have the topics of the reviews • We see Facebook has its very own topic
    36. 36. Mutual Connections • We now have the topics of the reviews • We see Facebook has its very own topic • Let’s now pivot to reviews that are under the topic: Facebook
    37. 37. Let’s scroll page left
    38. 38. This column is pointing backward…
    39. 39. … to these reviews, which are filtered
    40. 40. Let’s scroll page left
    41. 41. What we want are all mutual reviews having this topic …
    42. 42. … regardless of their relationship to the subject
    43. 43. This isn’t about Facebook
    44. 44. Let’s add a filter on the primaryTopic information
    45. 45. Binds this value to the current subject (primaryTopic)
    46. 46. Now that the primaryTopic is bound to Facebook, let’s return to the reviews under this topic
    47. 47. Task 3: Explore mutual reviewers • Now we have all reviews about Facebook
    48. 48. Task 3: Explore mutual reviewers • Now we have all reviews about Facebook • Let’s pivot to the other reviews Facebook reviewers have made
    49. 49. Let’s pull all information about these reviews
    50. 50. Explore Mutual Reviewers • The query description explains the criteria and filters of your query in plain language
    51. 51. Explore Mutual Reviewers • Let’s pivot to the primaryTopic of these reviews
    52. 52. Browse Mutual Reviewers • I see here that revyu.com isn’t reusing URIs from other dataspaces to represent topics
    53. 53. Should be a more authoritative source, such as IMDB or DBPedia
    54. 54. Browse Mutual Reviewers • Instead, revyu.com is minting it’s own topic URIs
    55. 55. Browse Mutual Reviewers • Instead, revyu.com is minting it’s own topic URIs • Shame on revyu.com
    56. 56. Browse Mutual Reviewers • Instead, revyu.com is minting it’s own topic URIs • Shame on revyu.com • Watch what happens when you don’t reuse URIs used by others…
    57. 57. … users get sparse information about your subjects
    58. 58. Total information available: only 9
    59. 59. Browse Mutual Reviewers • Had revyu.com used a more authorative source for it’s topic URIs (e.g. IMDB or DBPedia), then the information page could be embellished with many more connections made by others who reuse those URIs
    60. 60. Conclusion
    61. 61. Conclusion • We began with a person as the subject, and ended with a list of reviews made by reviewers of Facebook, by pivoting sets and refining criteria for subjects in the query
    62. 62. Conclusion • We began with a person as the subject, and ended with a list of reviews made by reviewers of Facebook, by pivoting sets and refining criteria for subjects in the query • Set pivoting is possible thanks to Linked Data
    63. 63. Conclusion • We began with a person as the subject, and ended with a list of reviews made by reviewers of Facebook, by pivoting sets and refining criteria for subjects in the query • Set pivoting is possible thanks to Linked Data • The sources in this demo are independent members of a growing federation, all following the Principles of Linked Data
    64. 64. Principles of Linked Data
    65. 65. Principles of Linked Data • Use URIs as names for things
    66. 66. Principles of Linked Data • Use URIs as names for things
    67. 67. Principles of Linked Data • Use URIs as names for things • Use HTTP URIs
    68. 68. Principles of Linked Data • Use URIs as names for things • Use HTTP URIs
    69. 69. Principles of Linked Data • Use URIs as names for things • Use HTTP URIs • Provide useful information at the URI address
    70. 70. Principles of Linked Data • Use URIs as names for things • Use HTTP URIs • Provide useful information at the URI address
    71. 71. Principles of Linked Data • Use URIs as names for things • Use HTTP URIs • Provide useful information at the URI address • Reuse and make links to URIs used by others
    72. 72. Now go grow the data web!

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