Ontology Technology applied to Catalogues

1. Ontology Technology applied to Catalogues Paul Kopp

2. About Descriptive Logics • Descriptive Logics is a formalism for representing knowledge • Knowledge concerns concepts, roles and individuals • An individual is in relationship with at least some concept • Example • “Aristotle” is an individual • “human being” is a concept • “is-a” is a relation • The individual “Aristotle” is in the relationship “is-a” with the concept “human being” • A concept is actually a set of individuals • Concepts may be built by applying operations to atomic concepts • Examples: restriction, intersection, union • A role is a relationship between two concepts • Example “hasChild” is a role expressing the relationship between the concepts “parent” and “child” • A role is actually a relationship between individuals • Constructions and Restrictions may apply to roles as well (ex.: intersection, “≥3hasChild”) Paul Kopp WGISS22 Annapolis

3. About Descriptive Logics (continued) • Knowledge Representation Systems based on Descriptive Logics • Descriptions • TBox (Terminology Box) • Contains the terminology given as concepts, roles and constructs on them • Ex.: (a) “satellite” “is-a” “space engine” • A TBox can contain complex descriptions, depending on the constructors that are available (i.e. on the definition of the Description Language) • ABox (Assertion Box) • Contains assertions about individuals in relationship with the terminology • Ex.: “SPOT5” “is-a” “Satellite” (SPOT5 is an individual) • Reasoning Services • From the TBox one infers properties of descriptions • Satisfiability, Subsumption, Equivalence, Disjointness • From the ABox, one infers properties of assertions w.r.t. the TBox • Consistency, Retrieval (find all individuals that are instances of a given concept), Realization (find the most appropriate concept for a given individual) • Complexity of reasoning is a major issue • Rich Description Languages entail complex reasoning (with possible untractability of some inferences like subsumption) Paul Kopp WGISS22 Annapolis

4. About Descriptive Logics (continued) • Comparison with other Knowledge Representation Formalisms • Conceptual Graphs (Sowa) • Semantic Data Models • Entity Relationship Model (Chen) • Conceptual Modelling • Unified Modelling Language (Rumbaugh) Specialists have been studying the correspondences between all these formalisms. Paul Kopp WGISS22 Annapolis

5. About ontologies • From ontos(Greek οντοσ = “which is real”)and logos(Greek λογος = “word”, “speech”) • Name given to knowledge representationswhere the main relationship is the “is-a” relationship • Ontologies are used to describe the concepts that prevail in a domain • Thesauri are very simple ontologies • Excerpt from the IDN keywords:ATMOSPHERE >ATMOSPHERIC WATER VAPOR >EVAPOTRANSPIRATION • Tools to create ontologies • Racer (http://www.racer-systems.com) • Stands for Renamed ABox and Concept Expression Reasoner • Protege (http://protege.stanford.edu) • SWOOP(http://www.mindswap.org/2004/SWOOP) • Reasoners • Pellet (http://www.mindswap.org/2003/pellet) • Racer Paul Kopp WGISS22 Annapolis

6. Ontologies and the W3C • Web Ontology Language (OWL) • Defined by the W3C • Specification of ontologies using the xml/RDF schema • Concept = class in OWL • Role = property in OWL • 3 levels of expressiveness • OWL-Lite (for simple ontologies like thesauri) • OWL-DL (for ordinary Descriptive Logics compliant ontologies) • OWL-Full (no computational guarantee) • SPARQL Query Language for RDF • Defined by the W3C • Specification of queries on ontologies specified with OWL • OWL and SPARQL implemented in several ontology tools (ex.: Protege) Paul Kopp WGISS22 Annapolis

7. Ontologies and Catalogues • Catalogue primary entries are metadata • Traditional metadata retrieval • Queries are applied to predefined “queryable” metadata elements (title, keyword, etc.) • Metadata satisfying the query are retrieved from the database and presented to the user (full or predefined “brief” or “short” content) • Another way to retrieve metadata? • Express metadata as ontologies • Link the metadata expressed as ontologies to a reasoner • Make the reasoner available to the catalogue user • The catalogue user may ask any question he wants to the catalogue Paul Kopp WGISS22 Annapolis

8. Experiment at CNES • Extension of the CNES ISO19115 Metadata Catalogue • Developed under the auspices of CNES R&D (project R-S06/OT-0005-013) • Metadata are inserted as ordinary xml files • Metadata may also (additionally) be inserted as ontologies (OWL-DL) • The catalogue user queries the catalogue as usual (keyword, time, location, etc.) • The catalogue user may ask for “more queries” • The catalogue system opens a reasoner (Pellet, through its Java API) • The user prepares a query from predefined SPARQL templates (the user just enters the values for the query variables) • SPARQL templates are prepared by the Catalogue Manager • Results from the “more queries” function are merged with the previous ones and presented to the user • End of development expected in 4Q06 Paul Kopp WGISS22 Annapolis

9. Thank you! Paul Kopp WGISS22 Annapolis