The TONES Consortium: Free University of Bozen-Bolzano Università di Roma “La Sapienza” The University of Manchester Technische Universität Dresden Hamburg University of Technology R. Möller Information Access and Ontology Processing Hamburg University of Technology

R. Möller2Information Access and Ontology Processing Ontology-based Tasks (1) Information Access Query validation Query generalization Query refinement Intensional Navigation Answering queries with synthetic concepts („summarize data patterns“)

R. Möller3Information Access and Ontology Processing Ontology-based Tasks (2) Discovery and Negotiation about Services Formalization possibilities Satisfiability of the conjunction of supply and demand descriptions Subsumption (plug-in) Entailment of non-disjointness

R. Möller4Information Access and Ontology Processing Ontology-based Tasks (3) Media interpretation Abduction Configuration

R. Möller5Information Access and Ontology Processing Scenario Terminological knowledge Tboxes (“Ontology”, e.g., OWL, RDFS/FA) Knowledge about individuals and their relations Aboxes (“Data descriptions”, e.g., RDF) Information Access Instance retrieval What’s different from database retrieval?

R. Möller6Information Access and Ontology Processing Andrea‘s Example However, applications based on bulk data  E. Franconi (retrieve (?x) (?x (some supervised (and top-manager (some office-mate area-manager))))))

R. Möller7Information Access and Ontology Processing Constraints (in-knowledge-base traffic-lights) (define-concrete-domain-attribute color :type string) (define-concept colorful-object (or (string= color "red") (string= color "green"))) (define-concept traffic-light (and (a color) colorful-object)) (instance traffic-light-1 traffic-light) (instance traffic-light-2 traffic-light) (instance traffic-light-3 traffic-light) (instance traffic-light-4 traffic-light) (constrained traffic-light-1 ?color-traffic-light-1 color) (constrained traffic-light-2 ?color-traffic-light-2 color) (constrained traffic-light-3 ?color-traffic-light-3 color) (constrained traffic-light-4 ?color-traffic-light-4 color) (constraints (string= ?color-traffic-light-1 ?color-traffic-light-3)) (constraints (string= ?color-traffic-light-2 ?color-traffic-light-4)) (constraints (string<> ?color-traffic-light-1 ?color-traffic-light-2)) (constraints (string<> ?color-traffic-light-2 "red"))

R. Möller8Information Access and Ontology Processing Constraints: Queries (abox-consistent?) (constraint-entailed? (string= ?color-traffic-light-2 "green")) (constraint-entailed? (string= ?color-traffic-light-4 "green")) (constraint-entailed? (string= ?color-traffic-light-1 "red")) (constraint-entailed? (string= ?color-traffic-light-3 "red"))

R. Möller9Information Access and Ontology Processing Thesis Ever more expressivity irresistible Expressivity required... but for some parts only DL reasoners... must be good for bulk data (data description scalability) Large parts of Aboxes deterministic must be expressive for special parts (expressivity scalability)

R. Möller10Information Access and Ontology Processing Approaches Layered (Tbox + DB) DLDB, DL-Lite, Inst. Store, LAS  Fast w.r.t. retrieval — Expressivity restricted Integrated (Tbox + Abox)  Expressivity — Speed: improvement advantageous

R. Möller11Information Access and Ontology Processing Investigation Optimization strategies for instance retrieval “Deterministic” KBs chosen for the investigation Only if we get this part right, we will be able to support application builders Assumption: Abox realization too expensive Query language: nRQL

R. Möller12Information Access and Ontology Processing LUBM Lehigh University Benchmark [Heflin et al.] Tbox for the investigation (OWL) Abox (RDF/OWL) Queries

R. Möller13Information Access and Ontology Processing Epistemic Conjunctive Queries (retrieve (?x) (?x (some supervised (and top-manager (some office-mate area-manager)))))) (retrieve (?x) (and (?x ?y supervised) (?y top-manager) (?y ?z office-mate) (?z area-manager)))