Semantic Interoperability

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1 Ivan Herman Semantic Interoperability Olle Olsson Swedish W3C Office Swedish Institute of Computer Science (SICS) Stockholm Apr (2) Background Stockholm Apr 27, 2011 (2)

2 Trends: from small/closed to large/open (3) History of computer use (IT) Canned applications Software + data files Suites of applications (steps in a job) Carefully crafted application programs sharing data Databases Applications sharing local database Application environments Harmonized APIs in applications and for application control Networks Arms-length distance appl-to-appl and appl-to-data Internet Loose coupling to (semi-)independent appls/data Stockholm Apr 27, 2011 (3) Trends: from small/closed to large/open History of computer use (IT) Canned applications Software + data files Increased dependence Suites of applications (stepson in external a job) factors Carefully crafted application programs sharing data Increased dependence on shared resources Applications sharing local database Databases Application environments Harmonized APIs in applications and for application control Networks Arms-length distance appl-to-appl and appl-to-data Internet Loose coupling to (semi-)independent appls/data Stockholm Apr 27, 2011 (4) (4)

3 Interoperability spaces (5) Software interoperability Software-to-software interactions Data/information interoperability Combination of data sources Stockholm Apr 27, 2011 (5) Interoperability dimensions / 1 Interoperability across jurisdictions Within an authority domain Between authority domains Interoperation across space Application to data: shared data storage Application to application: passive data exchanged Data to data: combining data repositories Application to some space of applications: (grid, cloud) Stockholm Apr 27, 2011 (6) (6)

4 Interoperability dimensions / 2 (7) Interoperability across time Application to other version of application Application to old version of data Stockholm Apr 27, 2011 (7) (8) Drivers Stockholm Apr 27, 2011 (8)

5 Basic traditional drivers (9) Cost manage/maintain applications and data Time Time to create / adapt to new requirements Quality Provide needed functionality / data Quality assurance Proof for a certain level of quality Stockholm Apr 27, 2011 (9) Major trends Increased decentralisation of authority Increased interaction across administrative boundaries Increased speed of change Technology Business Less specific local development Off-the-shelf solutions Standards Shared solutions Stockholm Apr 27, 2011 (10) (10)

6 Political driver: PSI directive (11) Provide public data for independent re-use Level of agreement about provisioning? Cost to live up to agreement Provider? Re-user? Data/information evolves Work to adapt to changes? PSI solution vs. collaboration solutions Separate technology approaches? Who is the consumer of tomorrow? Stockholm Apr 27, 2011 (11) (12) Semantic Web Stockholm Apr 27, 2011 (12)

7 Technology Semantic Web (13) Web technology Formats (XML, WS-*, MathML, RDF, SVG,...) Protocols (HTTP, SOAP,...) Processing (XForms, DOM, Powder, Pipeline,...) Semantic Web Technologies Rich representation: RDF, RDFS, OWL, SKOS,... Processing support: OWL, RIF, SPARQL,... Stockholm Apr 27, 2011 (13) Technology Semantic Web Semantic web is about what? about meaning and automation Meaning-based automation Meaning -- pragmatic approach in Semantic Web: a program knows what it can do with data self-describing data No magic... instead well-founded engineering Stockholm Apr 27, 2011 (14) (14)

8 Semantic Web building blocks (15) Stockholm Apr 27, 2011 (15) RDF Resource Description Framework Basic data model a triple triple (s,p,o) : s -- subject p -- predicate o -- object Conceptually: s is related by p to o RDF is a general model for such triples machine readable formats like RDF/XML, Turtle, n3, RXR Stockholm Apr 27, 2011 (16) (16)

9 (17) RDF micro example dbpedia:resource/volkswagen_phaeton dbpedia:ontology/weight dbpedia:ontology/manufacturer dbpedia:resource/volkswagen dbpedia:resource/volkswagen_phaeton dbpedia:ontology/weight dbpedia:resource/volkswagen_phaeton dbpedia:ontology/manufacturer dbpedia:resource/volkswagen Stockholm Apr 27, 2011 (17) OWL Web Ontology Language Define ontologies (conceptual model,...) for data Built on top of RDF Basic components: instance entity class type property relationship Ontology enables: Checking consistency of instance graph Inferring implicit statements about instance graph Stockholm Apr 27, 2011 (18) (18)

10 SKOS Simple Knowledge Organisation System (19) Define simple ontologies (conceptual model,...) Targeting traditional modelling approaches Taxonomies, classification schemes, thesauri,... Built on top of RDF Compatible with modelling standards: NISO Z ; ISO 5964:1985 Stockholm Apr 27, 2011 (19) SPARQL RDF Query Language (20) Retrieve RDF data from RDF data graphs RDF graph as answer to query Syntax inspired by SQL Example: PREFIX foaf: <http://xmlns.com/foaf/0.1/> PREFIX skos: <http://www.w3.org/2004/02/skos/core#> PREFIX dbo: <http://dbpedia.org/ontology/> SELECT?manufacturer?name?car WHERE {?car skos:subject <http://dbpedia.org/resource/category:luxury_vehicles>.?car foaf:name?name.?car dbo:manufacturer?man.?man foaf:name?manufacturer } ORDER by?manufacturer?name Stockholm Apr 27, 2011 (20)

11 Integration via SPARQL (21) Stockholm Apr 27, 2011 (21) (22) Approaches to interoperation Stockholm Apr 27, 2011 (22)

12 What can it mean? (23) Semantic Interoperability increased independence among communicating parties integrating resources developed using different vocabularies and perspectives on data transmit data and exchange information while allowing each system to process information independently allow two independent programs to derive same conclusions from same data Stockholm Apr 27, 2011 (23) Some interoperability types Content-centric interoperability Programs request data, and receive it as if from a data store State-less Procedural interoperability Programs interact with each other via structured dialogue State-full Delegation-based interoperability Programs request processing to be done by other programs State-less cf. DB-engines! Stockholm Apr 27, 2011 (24) (24)

13 (25) Models Domain models Describes some domain, with respect to: Terms Entities (instances) Properties, relations,... Types (classes) Properties, relations,... Data models Describes stored/communicated data about a domain Syntax Structure Values Stockholm Apr 27, 2011 (25) Data standards Data standards Documented data formats Covering some slice of a domain Committee managed Describing Format of stored representation? Format of exchanged data? Support for extensions/adaptations? Stockholm Apr 27, 2011 (26) (26)

14 Terminological models (27) Terminological models Defining terms, meanings Defining relations between terms Restricted formalism cover common needs Relationships to data? Use in software? Stockholm Apr 27, 2011 (27) Ontology models A model of a domain Cover aspects on instances/facts Cover generic aspects of the domain Represented in standardised formats RDF, OWL, SKOS Designed for use in software In general domain-independent tools (cf. DB engines) In specific application software Stockholm Apr 27, 2011 (28) (28)

15 (29) Models Terminological models Focussed on terms (words, names) Relationships between terms Conceptual models Focussed on structure (entities) Properties and relationships (on and between entities) Ontological models (semantic models) Focussed on statements (about types) Properties and relationships Interdependencies, constraints, invariants,... Stockholm Apr 27, 2011 (29) (30) Semantic Model Spectrum Conceptual Model RDF/S XTM Extended ER Thesaurus ER Relational Model, XML weak semantics Semantic Interoperability Has Narrower Meaning Than Structural Interoperability DB Schemas, XML Schema Taxonomy Is Subclass of Is Sub-Classification of Syntactic Interoperability Stockholm Apr 27, 2011 (30) Source: Obrst The Ontology Spectrum and Semantics Models, 2006 strong semantics Modal Logic First Order Logic Logical Theory Is Disjoint Subclass of with transitivity Description Logic property DAML+OIL, OWL UML

16 (31) Example Stockholm Apr 27, 2011 (31) Linked Open Data Initiative Web of data: Many open datasets on the web Interoperable when accessible as RDF Examples: Wikipedia ( text ) ==> dbpedia (RDF); Scientific data sets (experimental data) Public sector information (geodata, census data, statistics,...) Different aims and coverage But semantically interrelated Increasingly so over time! Stockholm Apr 27, 2011 (32) (32)

17 Linked Open Data (33) Linked Open Data (LOD) objective: expose open datasets via RDF set RDF links among the data items from different datasets a typical example is to set an owl:sameas between two items in different datasets that refer to the same thing set up query endpoints (usually SPARQL) Altogether billions of triples, millions of links The seed for a general Web of Data Stockholm Apr 27, 2011 (33) Linked Open Data Technologies: URIs (specifically, of the dereferenceable variety) HTTP Resource Description Framework (RDF) Serialization formats (RDFa, RDF/XML, N3, Turtle, and others) Stockholm Apr 27, 2011 (34) (34)

18 The LOD cloud, March 2008 (35) Stockholm Apr 27, 2011 (35) The LOD cloud, September 2008 Stockholm Apr 27, 2011 (36) (36)

19 The LOD cloud, March 2009 (37) Stockholm Apr 27, 2011 (37) The LOD cloud, July 2009 Stockholm Apr 27, 2011 (38) (38)

20 The LOD cloud, March 2011 (39) Stockholm Apr 27, 2011 (39) Linked Open Data Stockholm Apr 27, 2011 (40) (40)

21 (41) Models and data and programs Stockholm Apr 27, 2011 (41) (42) Models and data / 1 Model Essence (ontology,...) Describes Domain State DB Stockholm Apr 27, 2011 (42)

22 (43) Models and data / 2 Model Essence (ontology,...) Describes Application Domain State DB Stockholm Apr 27, 2011 (43) (44) Models and data / 3 Essence Model-a Model-a Model-a (ontology,...) (ontology,...) (ontology,...) Application Domain Domain Domain-1 State DB-x DB-x DB-x Stockholm Apr 27, 2011 (44)

23 (45) Conclusion Stockholm Apr 27, 2011 (45) Semantic interoperability Rich semantics Basic technologies in place RDF, OWL, SPARQL,... Support tools emerging Methodology emerging Challenges: Ontology construction Ontology alignment Manual work specific competence But: re-use conceptual models, taxonomies, etc Tool-supported approaches are explored All modelling is difficult Stockholm Apr 27, 2011 (46) (46)

24 (47) ---end--- Stockholm Apr 27, 2011 (47)

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