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Pragmatic Approaches to the Semantic Web

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Mike Bergman offers his take on what approaches to the semantic Web are working, what are not, and what all of this might say about the semantic Web moving forward. Informed by Structured Dynamics' …

Mike Bergman offers his take on what approaches to the semantic Web are working, what are not, and what all of this might say about the semantic Web moving forward. Informed by Structured Dynamics' open source frameworks and client experiences, the main thesis is that the pragmatic contribution of semantic technologies resides more in mindsets, information models and architectures than in 'linked data' as currently practiced.

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  • 1. Pragmatic Approaches to the Semantic Web or, Why Aren’t We in Hyperland Yet? Michael K. Bergman
  • 2. Outline Intro to SD and Me Summary of Main Thesis A Wee Bit of History What is Not Working? Problems with Linked Data What is Working? Some Pragmatic Lessons SD’s Pragmatic Approach Conclusion and Q & A 2
  • 3. Structured Dynamics Founded 2008; predecessor Zitgist LLC; two principals Privately held, revenue funded Boutique semantic technology shop Services and consulting:  Semantic enterprise adoption  Ontology development and mapping  Tech transfer and training Development and software:  Open source OSF stack  Data conversion and migration  Client-specific development 3
  • 4. Current Products and OSF Stack the pivotal product; Web services middleware that provides distributed data access and federation Drupal-based structured data linkage to structWSF spreadsheet, JSON and XML authoring and conversion framework reference set of linking subjects and basis for domain vocabularies an ontology- and entity-driven information extraction and tagging system 4
  • 5. SD Locations 5
  • 6. Michael Bergman 6
  • 7. Summary of Main Thesis
  • 8. Main Arguments Not against linked data  Proponent and explicator since 2006 But, linked data burdensome, not pivotal to interoperability Interoperability requires:  Structured data (from any source)  Canonical data model (RDF)  (Relatively simple) ontologies for world views, schema  Curation 8
  • 9. A Wee Bit of History
  • 10. Key Historical Milestones 1945: Memex 1963: Hypertext 1990: Hyperland 2001: Semantic Web  Lack of uptake 2006: Linked Data 2010: Revisionist Linked Data 10
  • 11. Hyperland 11
  • 12. Linked Data “Linked Data is a set of best practices for publishing and deploying instance and class data using the RDF data model, naming the data objects using uniform resource identifiers (URIs), thereby exposing the data for access via the HTTP protocol, while emphasizing data interconnections, interrelationships and context useful to both humans and machine agents.” 12
  • 13. What is Not Working?
  • 14. Some Disappointments to Date Full semantic Web vision Widescale adoption of the semantic Web, linked data Lack of intelligent agents Many aspects of the practice of linked data 14
  • 15. Problems with Linked Data
  • 16. Problems with Linked Data Burdensome on publishers Naïve linkages:  Overuse of sameAs  Lack of accurate alignments (Often) poor data quality Wrong focus 16
  • 17. Some Conditions for Interoperability<Interoperability> <needsMapping> <Predicates> <Interoperability> <needsReference> <Nouns> 17
  • 18. Many Mappings Should be Approximate skos:broadMatch skos:related ore:similarTo umbel:isAbout vmf:isInVocabulary skos:closeMatch lvont:nearlySameAs umbel:isLike umbel:hasCharacteristic lvont:somewhatSameAs rdfs:seeAlso ore:describes map:narrowerThan skos:narrower map:broaderThan skos:broader dc:subject link:uri foaf:isPrimaryTopicOf 18
  • 19. What is Working?
  • 20. Successes Siri Bing (Powerset) Google + schema.org (Some) linked data 20
  • 21. Siri 21
  • 22. Bing (Powerset) 22
  • 23. Google Statistical NLP Structured results Initial schema (Metaweb) schema.org (with Yahoo, Bing and Yandex) 23
  • 24. Some Linked Data Some selected knowledge bases:  DBpedia  GeoNames  Freebase (Google) Biomedical community LOD-LAM community 24
  • 25. Some Pragmatic Lessons
  • 26. Some Lessons Learned Structure is good in any form Keep semantic technology in the background Open Web (FYN) likely to be disappointing Ontologies essential for alignments NLP an essential contributor to structure Metadata an essential contributor to characterization, use Linked data is a burden to publishers, places semantic emphasis on wrong part of chain 26
  • 27. Seven Pillars 27
  • 28. Preserving Existing Assets Relational databases (RDBMs) Distributed structured assets  spreadsheets  lightweight datastores Web pages and Web sites Existing documents and text Web databases and APIs Other databases (RDF, OO, etc.) 28
  • 29. irON Dataset Exchange Framework Simple authoring and dataset creation irON includes an abstract notation and vocabulary for instance records Notations for:  Instance records  Schema  Datasets and metadata  Linkages to other schema Serializations available for:  XML (irXML)  JSON (irJSON)  CSV/spreadsheets (commON) 29
  • 30. Three irON Serializations irXML irJSON commON 30
  • 31. Spreadsheet Correspondence to Triples 31
  • 32. More-or-less Interchangeable Formats 32
  • 33. SD’s Pragmatic Approach
  • 34. A Layered Approach 34
  • 35. OSF Stack 35
  • 36. Conclusion
  • 37. Summary If you can, do linked data; it is a GOOD THING In any event, expose your data:  Structured (use NLP for unstructured)  Metadata  Definitions  Relations (simple)  “Semsets” (synonyms, acronyms, spelling variants) Build vocabulary and ontology consortia Build trust and curation communities Semantics essential at the interoperability level, not necessarily publication or data transfer 37
  • 38. Take Aways James Hendler: “A little bit of semantics goes a long way” Leverage linked data, but broaden focus Consider adopting the semantic enterprise as the broader focus 38
  • 39. Further Information
  • 40. More Info and Links Open Semantic Framework (OSF) stack:  http://openstructs.org TechWiki (400 detailed OSF how-to articles):  http://techwiki.openstructs.org Key ontologies:  UMBEL: http://umbel.org  BIBO: http://bibliontology.org Blogs:  Mike Bergman: http://mkbergman.com  Fred Giasson: http://fgiasson.com/blog Structured Dynamics:  http://structureddynamics.com  http://citizen-dan.org (community indicator systems) 40

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