HP Labs and the semantic web

1. HP Labs and the semantic web Dave Reynolds HP Laboratories

2. Outline Ф0 – motivation Ф1 – helping to lay the foundations Ф2 – applications and deriving value Rule based infernece support in Jena2

3. Motivation Creating opportunities Semantic web has the potential to transform how information systems are developed • broad applicability • web style – decentralized, integration, network effect, serendipity good fit for HP • open standards, open systems • heterogeneity => • help make it ‘happen’ • discover the valuable applications and exploitation paths as we go Rule based infernece support in Jena2

4. Ф1 Help to make it happen • Standards (key foundations) • committed participation: • RDF Core: (HP co-chair) • WebOnt • DAWG • SWBP Tools and Platforms – Building Blocks • Jena Semantic Web Framework • Joseki – Jena’s RDF Server • contribs and spin-offs – e.g. Brownsauce Rule based infernece support in Jena2

5. Applications RDQL Other QL Ontology API (RDFS/DAML/OWL…) XML ARP n-triples n-triples The RDF API N3 N3 Inference Writers Readers Stores BDB Mem RDB Jena semantic web framework • Open source • BSD Style License • Enabled widespread use: • Commercial and academic • Experimental and mainstream • Community Effect • RDF API • ONT API • Parsers and serializers • Query RDQL • Storage – RDBMS backends • Inference (rules, RDFS, OWL, DIG) Rule based infernece support in Jena2

6. Joseki – Jena’s RDF server • Publication and Remote Access to RDF • Access By Query • Coarse Grain, not triple by triple. • Returns matching subgraphs • Webbness • Implementation of NETAPI (member submission) • HTTP/URI HP implementation in Jena • SOAP/HTTP/WSDL implementation by Ontopia • Plugin Architecture: • Query Languages • Data Providers RDQL Example: SELECT * WHERE (?x ?y ?z) GET http://host/model?lang=RDQL\&query=SELECT%20*%20WHERE\%20(%3fx%20%3fy%20%3fz) HTTP 1.1 Returns matching sub-graph. Web Access Query Inference* Base Data * RDFS/OWL closures Rule based infernece support in Jena2

7. Ф2 Applications • no killer app • explore broad range of applications • reinforce the ones that take root • look for opportunities to link them, serendipity Rule based infernece support in Jena2

8. Applications -1 • External demonstrators - SWAD-E • semantic blogging • information portals • Content Management • SIMILE Joint (HP/MIT/W3C-SWAD research project) • Digital Library Metadata • Addressing issues of multiple schema (ontology), alignment, and versioning. • … Rule based infernece support in Jena2

9. Applications -2 • Knowledge management • informal, personal/workgroup (snippet manager) • KM document linking and classification common features • information held and managed at the leaves • but aggregated for search and browsing • ontologies/vocabularies as first class citizens • single infrastructure spans range – link across the applications • Data integration • product catalogue example • database integration • connections to knowledge management Rule based infernece support in Jena2

10. Applications - 3 • Semantic Web Services • EU Semantic Web enabled Web Services • inc. Innsbruck, FZI/Karlesruhe, DERI Galway, British Telecom • Enterprise Application Integration – working with internal partners. • Supply chain integration • Customer facing marketplace Web Service • Mobile Services, Ubiquitous Computing and B2C Rule based infernece support in Jena2

11. Summary messages • the foundations (standards and tools) are there • not finished but good enough to get on with applications • diversity of applications • biggest benefits will come from connecting them“better together” http://www.hpl.hp.com/semweb Rule based infernece support in Jena2