Razorbase Examples Part 2

Razorbase Examples pt. 2(Linked Data at Work)

By Sherman Monroe

Razorbase

• A browser for exploring the Linked Open Data cloud using OpenLink Facets API

Live demo available at http://www.razorbase.com

Task 1: Find a friend

Results set

Find a friend

• Found some things named Kingsley Idehen, surely our subject in this set

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

Task 2: Browse friend’s dataspaces

• Let’s take a look at what our friend is up to on the web

This looks like some kind of music related profile

Here’s his LinkedIn profile, hmm… let’s look more

Looks like a Rating/Reviews site…

… let’s pull this profile

Subject page for Kingsley Idehen’s revyu.com profile

List of filters for this subject

View all Information available about subject

Browse friend’s dataspace: Sparse results

• Only a few pieces of info for subject

Browse friend’s dataspace: Sparse results

• Only a few pieces of info for subject• Let’s look at the Reverse Connections for

subject

Browse friend’s dataspace

• Reverse connections are connections to other things that go the opposite direction

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

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

Add information to the view

Add information to the view (same function)

Let’s scroll page right

New column added

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.

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

Let’s scroll page left

Mutual Connections

• The Mutual Connections have returned all reviewers who created this review, so it makes sense that our subject is the only result

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?

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

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

Let’s return to the reviews

Let’s return to the reviews (same function)

Mutual Connections

• The primaryTopic information sounds useful

Mutual Connections

• We now have the topics of the reviews

Mutual Connections

• We now have the topics of the reviews• We see Facebook has its very own topic

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

Let’s scroll page left

This column is pointing backward…

… to these reviews, which are filtered

Let’s scroll page left

What we want are all mutual reviews having this topic …

… regardless of their relationship to the subject

This isn’t about Facebook

Let’s add a filter on the primaryTopic information

Binds this value to the current subject (primaryTopic)

Now that the primaryTopic is bound to Facebook,let’s return to the reviews under this topic

Task 3: Explore mutual reviewers

• Now we have all reviews about Facebook

Task 3: Explore mutual reviewers

• Now we have all reviews about Facebook• Let’s pivot to the other reviews Facebook

reviewers have made

Let’s pull all information about these reviews

Explore Mutual Reviewers

• The query description explains the criteria and filters of your query in plain language

Explore Mutual Reviewers

• Let’s pivot to the primaryTopic of these reviews

Browse Mutual Reviewers

• I see here that revyu.com isn’t reusing URIs from other dataspaces to represent topics

Should be a more authoritative source,such as IMDB or DBPedia

Browse Mutual Reviewers

• Instead, revyu.com is minting it’s own topic URIs

Browse Mutual Reviewers

• Instead, revyu.com is minting it’s own topic URIs

• Shame on revyu.com

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…

… users get sparse information about your subjects

Total information available: only 9

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

Conclusion

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

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

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

Principles of Linked Data

Principles of Linked Data

• Use URIs as names for things

Principles of Linked Data

• Use URIs as names for things

Principles of Linked Data

• Use URIs as names for things• Use HTTP URIs

Principles of Linked Data

• Use URIs as names for things• Use HTTP URIs

Principles of Linked Data

• Use URIs as names for things• Use HTTP URIs• Provide useful information at the URI address

Principles of Linked Data

• Use URIs as names for things• Use HTTP URIs• Provide useful information at the URI address

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

Now go grow the data web!