Semantic technologies at work

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highlights the use of semantic technologies to facilitate and empower semantic interoperability

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Semantic technologies at work

  1. 1. Semantic technologies at work: The interoperability perspective A talk by Yannis Kalfoglou at Wednesday, 22 nd August 2007
  2. 2. Overview <ul><li>Emergence ( and maturity of ) semantic technologies </li></ul><ul><ul><li>from the academic silos to industrial settings </li></ul></ul><ul><ul><li>Semantic Web and Web 2.0 drivers </li></ul></ul><ul><li>Interoperability as a key enabling technology </li></ul><ul><ul><li>business incentives </li></ul></ul><ul><ul><li>semantic interoperability </li></ul></ul><ul><ul><li>application areas </li></ul></ul><ul><li>Using semantic technologies for interoperability </li></ul><ul><ul><li>ontology mapping </li></ul></ul><ul><ul><ul><li>IF-Map method and tool </li></ul></ul></ul><ul><ul><ul><li>CROSI framework, API and CMS system </li></ul></ul></ul><ul><ul><li>progressive ontology coordination </li></ul></ul><ul><li>Exemplar scenarios and applications </li></ul><ul><ul><li>academic organisational structures alignment </li></ul></ul><ul><ul><ul><li>Enabling inter-organisational interoperability </li></ul></ul></ul><ul><ul><li>e-Government units alignment </li></ul></ul><ul><ul><ul><li>Enabling information exchange and collaborative processes </li></ul></ul></ul><ul><ul><li>bioinformatics terminologies alignment </li></ul></ul><ul><ul><ul><li>Enabling consensus building </li></ul></ul></ul><ul><ul><li>emergency response services terminology disambiguation </li></ul></ul><ul><ul><ul><li>Enactment of collaborative services and information discovery </li></ul></ul></ul><ul><li>Issues </li></ul><ul><ul><li>STs adoption </li></ul></ul><ul><ul><li>Interoperability in other domains (mobile web 2.0) </li></ul></ul>Semantic technologies Interoperability Using STs Experiences Issues 2/14
  3. 3. Semantic Technologies why do we need them? <ul><li>business drivers </li></ul><ul><ul><li>unprecedented exposure of information in digitised form  too much information available: “ infosmog ” </li></ul></ul><ul><ul><li>turn that information into usable knowledge </li></ul></ul><ul><ul><li>collaborative, inter-organisational business systems </li></ul></ul><ul><ul><li>globalisation of business processes – need for increased interoperability </li></ul></ul><ul><ul><li>empowerment of the individual </li></ul></ul><ul><ul><li>retention of knowledge </li></ul></ul><ul><ul><li>reduction of implementation time and cost </li></ul></ul><ul><li>societal drivers </li></ul><ul><ul><li>trends in employment: “up to 30% of EU’s working population will be directly employed in the production and diffusion of knowledge” [EU 2004] </li></ul></ul><ul><ul><li>knowledge based economy </li></ul></ul><ul><ul><li>ICTs affordable and available to everyone – participation is cheaper and global </li></ul></ul><ul><ul><li>(1.1bn web users, 17bn devices on the Internet by 2012 – [IDC 2005/6] ) </li></ul></ul><ul><li>technology triggers </li></ul><ul><ul><li>syntax based systems can’t cope with information explosion ( semantic heterogeneity ) </li></ul></ul><ul><ul><li>semantics can be codified and represented in computational form </li></ul></ul><ul><ul><li>maturity of highly distributed open-end environments, e.g., (Semantic) Web; and Web 2.0 approaches (social networking) </li></ul></ul>3/14 Semantic technologies Interoperability Using STs Experiences Issues
  4. 4. <ul><li>Emergence of “meaningful computing”: emphasis on codified representations of semantics </li></ul><ul><ul><li>represent meaning in computational forms; </li></ul></ul><ul><ul><li>enable automation and intelligent tasks; </li></ul></ul><ul><ul><li>better information management (search, discovery, integration); </li></ul></ul><ul><ul><li>enable re-use; </li></ul></ul><ul><ul><li>improved interoperability (semantic-based vs. syntax-based) </li></ul></ul><ul><li>Wide range of technologies: </li></ul><ul><ul><li>ontologies (OWL, KIF, Ontolingua, etc.) </li></ul></ul><ul><ul><li>data formats (RDF & RDF(S), ebXML ) </li></ul></ul><ul><ul><li>query languages (SPARQL) </li></ul></ul><ul><ul><li>APIs (HP Jena) </li></ul></ul><ul><ul><li>open standards (OG(eo)C, SUO, CL) </li></ul></ul><ul><ul><li>SOA </li></ul></ul><ul><ul><li>… </li></ul></ul><ul><li>Variety of application areas: </li></ul><ul><ul><li>knowledge representation & reasoning (ontologies) </li></ul></ul><ul><ul><li>semantic annotation (semantic tagging) </li></ul></ul><ul><ul><li>semantic querying (SPARQL, OWL-driven) </li></ul></ul><ul><ul><li>semantic interoperability and integration (ontology/schema mapping) </li></ul></ul><ul><ul><li>semantically enriched storage (RDF) </li></ul></ul>Semantic Technologies what are they? where do we apply them? 4/14 Semantic technologies Interoperability Using STs Experiences Issues
  5. 5. <ul><li>Semantic Web </li></ul><ul><ul><li>(towards) an infrastructure made up of representation languages, communication protocols, access controls & authentication services for coordinated sharing of knowledge across particular domain-oriented applications </li></ul></ul><ul><ul><li>(vision) turning the web into a globally distributed knowledge base where software agents will assist in most, if not all, tasks of information management </li></ul></ul><ul><li>Web 2.0 </li></ul><ul><ul><li>enabling technologies for mass participation in social networking activities on the Web </li></ul></ul><ul><ul><li>range of supporting technologies (AJAX, wikis, tagging, bloging, etc.) </li></ul></ul><ul><ul><li>no centralised control, no agreed vocabularies, “wisdom of the clouds” (collective intelligence) </li></ul></ul><ul><li>Semantic technologies are a core component for both </li></ul>Semantic Technologies The Semantic Web and Web 2.0 impact 5/14 Semantic technologies Interoperability Using STs Experiences Issues
  6. 6. Interoperability a key enabling technology <ul><li>business incentives </li></ul><ul><ul><li>disparate and open-ended environments for applications </li></ul></ul><ul><ul><li>complex tasks and cross sector applications </li></ul></ul><ul><ul><li>Inevitably, heterogeneity inherited in the system </li></ul></ul><ul><ul><ul><li>variety of protocols, domains, languages, processes, interpretations </li></ul></ul></ul><ul><ul><li>preserve the meaning of concepts used in everyday transactions of information sharing </li></ul></ul><ul><ul><ul><li>a key enabler for automated collaborative tasks </li></ul></ul></ul><ul><li>semantic interoperability </li></ul><ul><ul><li>syntax alone is not sufficient to capture the subtle differences in meaning </li></ul></ul><ul><ul><li>semantics allow to express meaning in structured computational forms </li></ul></ul><ul><ul><li>use these forms, alongside syntactic based approaches, to enable semantic interoperability </li></ul></ul><ul><li>application areas ( non-exhaustive list ) </li></ul><ul><ul><li>database schema integration ( construct global views ) </li></ul></ul><ul><ul><li>data warehouses ( data format transformations ) </li></ul></ul><ul><ul><li>e-commerce ( message exchange ) </li></ul></ul><ul><ul><li>semantic query processing ( query terms disambiguation ) </li></ul></ul><ul><ul><li>ontology integration/merging ( construct top-level/global ontologies ) </li></ul></ul><ul><ul><li>ontology alignment/mapping (concepts’ alignment) </li></ul></ul><ul><ul><li>SW agents interoperability ( agents vocabulary alignment ) </li></ul></ul>6/14 Semantic technologies  Interoperability Using STs Experiences Issues
  7. 7. Using STs for interoperability ontology mapping – IF-Map <ul><li>aligns the vocabularies of two ontologies that share the same domain of discourse in such a way that the mathematical structure of ontological signatures and their intended interpretations – as specified by ontological axioms, are respected. </li></ul><ul><ul><li>Structure preserving mechanisms – morphisms </li></ul></ul><ul><ul><li>establish a collection of binary relations between the vocabularies </li></ul></ul>7/14 Semantic technologies  Interoperability  Using STs Experiences Issues <ul><li>Information flow based ontology mapping </li></ul><ul><li>A theory of information flow for distributed systems </li></ul><ul><li>Each component is modelled by means of an IF classification </li></ul><ul><li>Connections between components are modelled by infomorphisms: </li></ul><ul><li>IF-Map </li></ul><ul><li>A method and a system that implements the idea of Information flow based ontology mapping </li></ul><ul><li>Ontologies are represented as IF classifications (tokens to types) </li></ul><ul><li>Customised parsers to extract features from the ontology (tokens, types) Java front end, API, output in RDF </li></ul>
  8. 8. Using STs for interoperability ontology mapping - CROSI 8/14 <ul><li>Too many disparate ontology alignment and semantic integration systems </li></ul><ul><li>Complementary functionalities, lack of consensus, lack of a principled process for alignment </li></ul><ul><li>CROSI ( C apturing R epresenting and O perationalising S emantic I ntegration) – HP funded project </li></ul><ul><li>a state-of-the-art survey of semantic integration (SI) technologies </li></ul><ul><ul><li>a principled characterisation of SI systems </li></ul></ul><ul><ul><li>a modular architecture for developing ontology mapping systems </li></ul></ul><ul><ul><li>A fully functional, proof-of-concept prototype system (CMS) for ontology mapping </li></ul></ul><ul><ul><ul><li>Structure and semantics based </li></ul></ul></ul><ul><ul><ul><li>Multiple matchers approach </li></ul></ul></ul><ul><ul><ul><li>Aggregating alignments and tuning algorithms (via API or command line prompt) </li></ul></ul></ul>Semantic technologies  Interoperability  Using STs Experiences Issues
  9. 9. Using STs for interoperability progressive ontology coordination <ul><li>Ontology coordination: progressively sharing information on instances from a common domain of discourse and how these are classified under distinct agents’ ontologies </li></ul><ul><li>Two agents A1 and A2 want to interoperate on the SW, their knowledge is represented according to their own conceptualisations – explicitly modelled as ontologies which are not open for inspection, learning each others’ ontologies can only be based on interaction </li></ul><ul><ul><li>Exchange instance classification information </li></ul></ul><ul><ul><li>A1 and A2 will have distinct set of instances </li></ul></ul><ul><ul><li>A priori knowledge of a common domain of instances necessary </li></ul></ul><ul><ul><li>Ontology coordination focuses on alignment at the type-level </li></ul></ul><ul><ul><li>IF approach advocates token-level connection in order to determine semantic integration at the type-level </li></ul></ul><ul><li>Token connection as a result of instances passing between agents </li></ul><ul><li>Ontology coordination can hardly be absolute , but depends on </li></ul><ul><ul><li>the way ontologies are used ( populated ontologies ) </li></ul></ul><ul><ul><li>the particular understanding of semantics ( our choice of types/tokens ) </li></ul></ul><ul><ul><li>how ontologies are linked together via connected tokens ( semantic integration guaranteed on connected tokens ) </li></ul></ul>9/14 Semantic technologies  Interoperability  Using STs Experiences Issues
  10. 10. Scenarios and applications Aligning academic organisational structures <ul><li>5 university computer science departments organisational structures </li></ul><ul><ul><li>differences in conceptualisation of similar tasks, roles, concepts </li></ul></ul><ul><li>use of IF-Map methodology and system </li></ul>10/14 Semantic technologies  Interoperability  Using STs  Experiences Issues <ul><li>Alignment of concepts and relations </li></ul><ul><ul><li>Dependant on type checking </li></ul></ul><ul><ul><li>Classified instances </li></ul></ul><ul><ul><li>Kick-off heuristics to fix the initial map </li></ul></ul>
  11. 11. Scenarios and applications e-Government: ministerial units alignment 11/14 Semantic technologies  Interoperability  Using STs  Experiences Issues e-Gov scenario of UK and US software agents trying to align ministerial units from 4 ministries/departments: UKFCO, UKHO, USDoJ, USDoS use taxonomy and ministry/dept. structure but also responsibility and how these are allocated within the ministry/dept. Use IF technology to represent the structure and infer dependencies in the lattice: Use initial partial alignment of UK to US responsibilities (tokens) and IF classifications and IF-Map mechanism to infer the type level alignment:
  12. 12. Scenarios and applications Bioinformatics: terminology alignment 12/14 Bioinformatics alignment scenario Part of the annual ontology alignment contest (sponsored by OAEI) FMA  Foundational Model of Anatomy large reference .owl ontology ~31MB, 73k classes, ~100 relations OpenGALEN  open source version of a healthcare ontology anatomy part, (compact .owl ontology, ~4MB, ~25 classes, ~30 relations) <ul><li>Use of CROSI CMS system </li></ul><ul><li>Structure and linguistic matchers </li></ul><ul><li>Adjustments to handle the size of FMA </li></ul>Semantic technologies  Interoperability  Using STs  Experiences Issues
  13. 13. Scenarios and applications e-Response: term disambiguation and service enactment 13/14 <ul><li>Application of STs in an emergency response scenario </li></ul><ul><ul><li>aim to facilitate planners to make sense of a complex situation as it unfolds in real time </li></ul></ul><ul><ul><li>used a simulator and realistic scenario </li></ul></ul><ul><ul><li>focussed on real world resources and emergency services </li></ul></ul><ul><li>Technologies for: semantically enriched storage; semantic annotation, information extraction, sense making GUI, planning and scheduling, resource binding, communities of interest identification, service invocation and term disambiguation (modified CROSI CMS) </li></ul>Semantic technologies  Interoperability  Using STs  Experiences Issues
  14. 14. <ul><li>Semantic technologies adoption </li></ul><ul><ul><li>“ start small with the big picture in mind” </li></ul></ul><ul><ul><li>(from lightweight semantic hypertext markup – microformats - to fully fledged ontologies) </li></ul></ul><ul><ul><li>Prepare for a major shift in business models </li></ul></ul><ul><ul><li>Long term investment </li></ul></ul><ul><ul><li>Keep it simple (semantics) </li></ul></ul><ul><ul><ul><li>Irreconcilable arguments among engineers at design time </li></ul></ul></ul><ul><ul><ul><li>Inappropriate interpretations and usage at deployment time </li></ul></ul></ul><ul><ul><ul><li>Hard to maintain – not stable over time – obsolete knowledge </li></ul></ul></ul><ul><li>Interoperability as a means to enable intelligent tasks in a variety of domains </li></ul><ul><ul><li>mobile web 2.0 trends (web 2.0 + mobile web) </li></ul></ul><ul><ul><li>more people with mobiles than PCs </li></ul></ul><ul><ul><li>Social networking (web 2.0) on the Web (single network) using a common driver (mobile device) </li></ul></ul><ul><ul><li>Global audience, global services, single marketplace </li></ul></ul><ul><li>Web access for “internet of things” </li></ul><ul><ul><li>Universal content, ubiquitous computing </li></ul></ul><ul><ul><li>Interoperability needs between: </li></ul></ul><ul><ul><ul><li>Global services, universal content, to enable social networking and ubiquitous computing </li></ul></ul></ul>Issues technology & socio-political 14/14 Semantic technologies  Interoperability  Using STs  Experiences  Issues
  15. 15. Semantic technologies at work The interoperability aspect A talk delivered by Yannis Kalfoglou at Wednesday, 22 nd August 2007 Thank you for listening
  16. 16. A principled way of characterising semantic integration systems
  17. 17. Accessing CMS Command line input Web-based GUI Programmatic access
  18. 18. Versatile output Single matcher output SKOS output Combinations of matchers
  19. 19. <ul><li>h the distance between “Word” and Root </li></ul><ul><li>h’ the distance between “Word’” and Root </li></ul><ul><li>H the distance between common subsumer of “Word” and “Word’” and Root </li></ul><ul><li>Similarity between “Word” and “Word’” is computed as </li></ul><ul><li>2H/(h+h’) </li></ul>Structure algorithm P1’(C’, B’) P2’ P3’ P1(C, B) P2 P3 f (name similarity, domain similarity, range similarity ) Canonical Name C=> A.B.D.C C’=> A’.B’.D’.E’.C’ Compute the similarity between C and C’ as well as the respective similarity between every pair of super classes of C and C’ Penalise the similarity between C and C’ with those of their super classes Root Common Subsumer Word’ Word H h’ h H G Domain of P1 H’ G’ I’ Domain of P1’ A B D Range of P1 E A’ B’ D’ E’ Range of P1’ F’ C’ A’ B’ D’ E’ A B C D
  20. 20. Agents exchange instances coordinated channel, so far… Complete coordination and IF theory on semantic relations:
  21. 21. <ul><li>W3C Mobile Web Initiative </li></ul><ul><ul><li>Best Practices – online checker </li></ul></ul><ul><ul><li>mobileOK conformance mark – machine testable </li></ul></ul><ul><li>dot mobi </li></ul><ul><ul><li>mTLD (top level domain for mobiles – ICANN) </li></ul></ul>Standards, early adopters, trends <ul><li>Early adopters </li></ul><ul><ul><li>Orange – Pikeo, bubbletop, Soundtribes </li></ul></ul><ul><ul><li>Vodafone – Betavine </li></ul></ul><ul><ul><li>NeoMedia/Qode, radar.net, ShoZu, TellMe </li></ul></ul><ul><ul><li>BBC + CNN mobile  web 2.0 features – UGC </li></ul></ul><ul><li>Trends </li></ul><ul><ul><li>think beyond numbers (mobile device not only a phone – URIs, tags, etc.) </li></ul></ul><ul><ul><li>Pushing out too much content leads to microcontent </li></ul></ul>

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