How to Do Things with Triples

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How to do things with triples
Keynote talk at ACM Hypertext 2012

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How to Do Things with Triples

  1. 1. WeST – Web Science & Technologies University of Koblenz Landau, GermanyHow to do things with triples? Steffen Staab
  2. 2. What is a triple?http://dbtune.org/musicbrainz/resource/artist/d87e52c5-bb8d-4da8-b941-9f4928627dc8 foaf:name ABBAWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  3. 3. What is Linked Data? The LOD CloudWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  4. 4. What is Linked Data? Linked Data Principles1. URIs as identifiers 2. http lookup 4. relations, also to other locationsWeST – Web Science & 3. RDF Steffen StaabTechnologies (triples) staab@uni-koblenz.de
  5. 5. What is Linked Data good for? Data integration is easy  Migrating different data sources to linked data is (relatively) easy Serendipitous use  Discover new information by following data links Data repurposing  Querying and aggregating data can give new insights ...WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  6. 6. Issue: From Data to UnderstandingWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  7. 7. LENA – A Fresnel application Fresnel Vocab by [Pietriga et al. ISWC-2006]WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  8. 8. State-of-the-Art: One App at a TimeShameless self-promotion: Semaplorer Billion Triples Challenge 1. Prize 2008 [Schenk et al., JoWS 2009]WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  9. 9. State-of-the-Art: One App at a TimeShameless self-promotion: LISA 1. Prize German Linked Open Gov Data Competition 2012WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  10. 10. What‘s between the two?One App at a Time Generic Frameworks+ Great to use + Can be applied on all data+ Like DB application - Data remains hard to- Brittle understand- Not really extensible - No process support - Noone wants to use themWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  11. 11. What may be a theory for doing things with triples? PRAGMATICSWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  12. 12. Austin: How to do things with wordsCore Hypothesis by Austin:Speech is not only passively describing a given reality, but it canchange the (social) reality it is describing through speech acts Summary from Wikipedia, 2012-06-09WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  13. 13. Why Do We Understand the Text Web?WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  14. 14. Austin: How to do things with words Phonic act / graphic act: ThetemperatureinMilwaukeeis100°F. Locutionary act: temperature(Milwaukee,100) Grice‘s maximsWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  15. 15. Grice‘s Maxims / Cooperative PrincipleInteracting agents mutually assume that: Quantity:  Be as informative as you possibly can,  give as much information as needed, not more. Quality: Criteria are  Be truthful competing and Pertinence: overlapping.  be relevant,  say things pertinent to the discussion Manner:  be clear, brief, orderly as one can  avoid obscurity and ambiguityWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  16. 16. Austin: How to do things with words Phonic act / graphic act: ThetemperatureinMilwaukeeis100°F. Locutionary act: temperature(Milwaukee,100) Grice‘s maxims Illocutionary act: Warn the conference attendees Perlocutionary act: Attendees stay in the shadow, etc…WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  17. 17. Austin: How to do things with wordsCore Hypothesis by Austin:Speech is not only passively describing a given reality, but it canchange the (social) reality it is describing through speech acts Summary from Wikipedia, 2012-06-09Hypothesis of this talk:Linked data is facts, but the idea of linked data is also re-purposing, ⟹ re-presenting, ⟹ re-narrating,to achieve an understandable dialogueWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  18. 18. Semantic Web / Linked Data Phonic act / graphic act: ThetemperatureinMilwaukeeis100°F. - various syntaxes - Locutionary act: temperature(Milwaukee,100) - RDF/OWL interpretation –WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  19. 19. Data is not TextQuantity: One triple vs big data➯ What is the right amount?Pertinence: Pertinence to dialogue➯ Does the discussion/interaction determine data selection?Manner: Data is not sequential➯ No implicit ordering contained in the data (e.g. birthdata before date of death)WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  20. 20. Semantic Web / Linked Data Phonic act / graphic act: Lead question: ThetemperatureinMilwaukeeis100°F. Semantic Web Does the - various syntaxes - have a pragmatics layer? Locutionary act: How would this look like? temperature(Milwaukee,100)  Quantity - RDF/OWL interpretation –  Quality  Pertinence  Manner Generic applications easily violate Grice‘s maxims!WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  21. 21. CONCEPTUAL NAVIGATION MODELWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  22. 22. Hypertextual Navigation (from D. Schwabe) What does it mean to click here? Semantics is clear, but Pragmatics? Context + Grice‘s Pertinence! [Bomfim & Schwabe, 2011]WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  23. 23. Hypertextual Navigation (from D. Schwabe)  Input: LOD + Navigation Model + other stuff  Navigation Model  A Context is a set of resources that share similar navigation opportunities. • Context:Navigation ⇔Class:Structure+Behavior  Navigation MetamodelWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  24. 24. Hypertextual Navigation (from D. Schwabe) foaf:Document AllDocuments DocumentsAlpha DocumentsByPerson byPerson Hitting a link of type foaf:Person „Organization“ byDocument means different AllPersons PersonsAlpha things in different contexts! swc:AcademicEvent Here is one! byOrganiza on EventsByUserProgram byUserProgram AllEvents EventsAlphaWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  25. 25. PROGRAMMING WITH LINKEDDATA =INTERACTING WITH LINKED DATA [Schegelmann et al 2012]WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  26. 26. Mapping Linked Data and OO ProgrammingLinked Data Object orientation Meaning/Semantics  Meaning/Semantics  Concept  Classes  Properties  Attributes/Methods  Instances  Objects  Pragmatics  Classes • Visible and used by whom? • Orchestration of method calls Responsibility-drivenWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  27. 27. Why is Linked Data Programming Tricky?Developing Core Ontologies Software: Core Ontology of Software (COS) Services: Core Ontology of Software Components (COSC) Multimedia: Core Ontology of Multimedia (COMM) Events: Core Ontology of Events (F) Desktop: Core Semantic Inf. Mgmt. Ontology (COSIMO)Main Criteria: Reusability  Plugability Main Drawback: Programmability WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  28. 28. What Jeopardizes Programmability?Challenges on (RDF) knowledge representation N-ary relations (denormalization) Aspect on relationships („Tim has high temp, but falling“) Roles as additional objects (lifetime different from rigid object) Different roles being played in different contexts (descriptions and situations) Solution [Schegelmann et al 2012]: –Different ontology patterns to the rescue –Easy to use APIs http://www.w3.org/TR/swbp-n-aryRelations/WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  29. 29. Pattern for Image Tagging [Scherp&Saathoff, WWW-2010] [Troncy et al 2007]WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  30. 30. Ontology API Model for Image TaggingWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  31. 31. Automatically Generated Ontology APIWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  32. 32. Comparing the two structuresWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  33. 33. OntoMDE Workflow Model of Ontologies (MoOn) Adding declarative layer: Structuring the ontologies into semantic units Ontology API Model (OAM) Adding declarative layer: Structuring pragmatic units specifying how entities are to be used togetherWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  34. 34. RANKINGWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  35. 35. More data here … Which links to follow? Where to go next? What information is there? What are the „good“ links … … leading to „good“ resources? More data here …WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  36. 36. Relevance Ranking for Linked Data Apply Web Ranking, e.g. HITS, PageRank, … Who is loved/hated most? TripleRankWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  37. 37. Linked Data as Tensor Transformation to 3-D-Tensor Then: [Franz et al, 2009] PARAFAC analysis [Nickel et al, 2012]WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  38. 38. Evaluation  16 test persons  Faceted browsing scenario  What are the most interesting, most related, most useful resources (objects)?  10 queriesWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  39. 39. Evaluation: Results  1387 answers, overall inter-rater agreement: 0.7 (0 ≤ agreement ≤ 1)8 TR 7.594 TR7 BL654 Doubled recall BL 3.948 TR3 without loss of precision! 3.251 TR 2.413 BL2 1.626 BL 1.20710 Total Results Positives Negatives WeST – Web Science & Steffen Staab Technologies staab@uni-koblenz.de
  40. 40. CONCLUSIONWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  41. 41. Metamodels Patterns Pragmatics Rankings ... Semantics SyntaxWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  42. 42. Issue: From Data to Understanding Cognition Storytelling Pragmatics Ontology Patterns Conceptual Modeling Metamodels ... Quantity Pertinence MannerWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  43. 43. Hypertext CommunityLinking people Linking resources Make linked data understandable! Linking data Linking storiesWeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  44. 44. THANK YOU!WeST – Web Science & Steffen StaabTechnologies staab@uni-koblenz.de
  45. 45. LiteratureJ. L. Austin. How to do things with words. Oxford University Press, 1962/1975.M. H. de S. Bomfim, Daniel Schwabe. Design and Implementation of Linked Data ApplicationsUsing SHDM and Synth. Int. Conf. Web Engineering 2011, pp. 121-136.T. Franz, A. Schultz, S. Sizov, S. Staab: TripleRank: Ranking Semantic Web Data by TensorDecomposition. International Semantic Web Conference 2009: 213-228Chierchia, Gennaro.; McConnell-Ginet, Sally: Meaning and Grammar : An Introduction toSemantics. MIT Press, 1990.Maximilian Nickel, Volker Tresp, Hans-Peter Kriegel: Factorizing YAGO: scalable machinelearning for linked data. WWW 2012: 271-280E. Pietriga, C. Bizer, D. Karger, R. Lee: Fresnel: A Browser-Independent Presentation Vocabularyfor RDF. International Semantic Web Conference 2006, Springer 158-171.S. Schenk, C. Saathoff, S. Staab, A. Scherp. SemaPlorer – Interactive Semantic Exploration ofData and Media based on a Federated Cloud Infrastructure. In Journal of Web Semantics,Elsevier, 7(4), 2009.C. Saathoff, A. Scherp: Unlocking the semantics of multimedia presentations in the web with themultimedia metadata ontology. WWW 2010: 831-840R. Troncy, O. Celma, S. Little, R. García and C. Tsinaraki. MPEG-7 based MultimediaOntologies: Interoperability Support or Interoperability Issue? In Workshop on MultimediaAnnotation and Retrieval enabled by Shared Ontologies (MAReSO07), Genova, Italy, December5, 2007. http://www.eurecom.fr/~troncy/Publications/Troncy-mareso07.pdf WeST – Web Science & Steffen Staab Technologies staab@uni-koblenz.de

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