SIOC Post profile for "AI3:::Adaptive Information"
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foaf:primaryTopic: When Linked Data Rules Fail
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When Linked Data Rules Fail
type: Post
has container: weblog
has creator: Mike Bergman
maker: Mike Bergman
created: 2009-11-16T17:04:01Z
content: High Visibility Problems with NYT, data.gov Show Need for Better Practices When I say, "shot", what do you think of? A flu shot? A shot of whisky? A moon shot? A gun shot? What if I add the term "bank"? Do you now think of someone being shot in an armed robbery of a local bank or similar? And, now, what if I add a reference to say, The Hustler, or Minnesota Fats, or "Fast Eddie" Felson? Do you now see the connection to a pressure-packed banked pool shot in some smoky bar room? As humans we need context to make connections and remove ambiguity. For machines, with their limited reasoning and inference engines, context and accurate connections are even more important. Over the past few weeks we have seen announcements of two large and high-visibility linked data projects: One, a first release of references for articles concerning about 5,000 people from the New York Times at data.nytimes.com; and Two, a massive exposure of 5 billion triples from data.gov datasets provided by the Tetherless World Constellation (TWC) at Rennselaer Polytechnic Institute (RPI). On various grounds from licensing to data characterization and to creating linked data for its own sake, some prominent commentators have weighed in on what is good and what is not so good with these datasets. One of us, Mike, commented about a week ago that "we have now moved beyond 'proof of concept' to the need for actual useful data of trustworthy provenance and proper mapping and characterization. Recent efforts are a disappointment that no enterprise would or could rely upon." Reactions to that posting and continued discussion on various mailing lists warrant a more precise dissection of what is wrong and still needs to be done with these datasets [1]. Berners-Lee's Four Linked Data "Rules" It is useful, then, to return to first principles, namely the original four "rules" posed by Tim Berners-Lee in his design note on linked data [2]: Use URIs as names for things Use HTTP URIs so that people can look up those…
encoded: High Visibility Problems with NYT, data.gov Show Need for Better Practices When I say, “shot”, what do you think of? A flu shot? A shot of whisky? A moon shot? A gun shot? What if I add the term “bank”? Do you now think of someone being shot in an armed robbery of a local bank or similar? And, now, what if I add a reference to say, The Hustler, or Minnesota Fats, or “Fast Eddie” Felson? Do you now see the connection to a pressure-packed banked pool shot in some smoky bar room? As humans we need context to make connections and remove ambiguity. For machines, with their limited reasoning and inference engines, context and accurate connections are even more important. Over the past few weeks we have seen announcements of two large and high-visibility linked data projects: One, a first release of references for articles concerning about 5,000 people from the New York Times at data.nytimes.com; and Two, a massive exposure of 5 billion triples from data.gov datasets provided by the Tetherless World Constellation (TWC) at Rennselaer Polytechnic Institute (RPI). On various grounds from licensing to data characterization and to creating linked data for its own sake, some prominent commentators have weighed in on what is good and what is not so good with these datasets. One of us, Mike, commented about a week ago that “we have now moved beyond ‘proof of concept’ to the need for actual useful data of trustworthy provenance and proper mapping and characterization. Recent efforts are a disappointment that no enterprise would or could rely upon.” Reactions to that posting and continued discussion on various mailing lists warrant a more precise dissection of what is wrong and still needs to be done with these datasets [1]. Berners-Lee’s Four Linked Data “Rules” It is useful, then, to return to first principles, namely the original four “rules” posed by Tim Berners-Lee in his design note on linked data [2]: Use URIs as names for things Use HTTP URIs so that people can look up those…
topic: Linked Data
topic: Ontology Best Practices
topic: Semantic Web
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links to: www.adhd-mindbydesign.com
links to: The Hustler
links to: linked data
links to: data.nytimes.com
links to: data.gov
links to: Rennselaer Polytechnic Institute
links to: licensing
links to: data characterization
links to: own sake
links to: commented
links to: mailing lists
links to: [1]
links to: [2]
links to: Data-Gov Wiki
links to: [3]
links to: catalog
links to: #319
links to: Dataset 319
links to: Department of Labor
links to: LABOR-STAT
links to: index.rdf
links to: metadata
links to: technical documentation
links to: glossary page
links to: code
links to: NYT record
links to: newman paul per
links to: nyt:first_use
links to: this discussion
links to: SKOS
links to: concept
links to: foaf:primaryTopic
links to: nyt:associated_article_count
links to: nyt:last_use
links to: nyt:topicPage
links to: Freebase
links to: DBpedia
links to: entail
links to: infers
links to: [5]
links to: owl:Thing
links to: foaf:Agent
links to: foaf:Person
links to: dbpedia-owl:Actor
links to: JewishActors
links to: http://dbpedia.org/class/yago/PeopleFromCleveland,Ohio
links to: dbpedia-owl:Artist
links to: dbpedia-owl:Person
links to: Person100007846
links to: AmericanFilmDirectors
links to: YaleUniversityAlumni
links to: OhioUniversityAlumni
links to: opencyc:en/MaleHuman
links to: AmericanFilmActors

Mike Bergman
type: User

Mike Bergman
type: Person

data.nytimes.com
label: NYT dataset

data.gov
label: Tetherless World Constellation

commented
label: that posting

#319
label: dataset (#319)

Dataset 319
label: page

http://dbpedia.org/class/yago/PeopleFromWestport,Connecticut

opencyc:en/JewishPerson

opencyc:en/ActorInMovies

UMBEL

[4]

trough of disillusionment

some

Mike Bergman

Fred Giasson