Knowledge Engineering Meets Software Engineering

1. Knowledge Engineering Meets Software Engineering Hele-Mai Haav Institute of Cybernetics at TUT Software department EXCS Sept. 19 2008

2. Outline Knowledge-based systems Ontologies and their applications (Semantic) web services SE KE EXCS Sept. 19 2008

3. Knowledge-based Systems... ...for engineering computations (also knowledge-based SE) • Historical field of activities at software department of IoC • Systems with structural synthesis of programs capturing domain knowledge in form of computational models: PRIZ, ExpertPriz, NUT, etc (E. Tyugu et al) • Current system CoCoViLa supports visual specification of domain knowledge still using structural synthesis of programs (E. Tyugu, M. Harf, P. Grigorenko, R. Maigre, A. Ojamaa ) EXCS Sept. 19 2008

4. Ontologies and their Applications • Ontology: a shared conceptualization of a domain that is commonly agreed to by all parties, ‘a specification of a conceptualization’ (Gruber 1993) • Ontology: means to facilitate knowledge reuse by different applications, software systems and human resources. • Ontologies are highly expressive knowledge models  increase expressiveness and intelligence of a system EXCS Sept. 19 2008

5. Ontologies and their ApplicationsOntology Learning • Ontology learning using Formal Concept Analysis (FCA) (H-M. Haav) • Combining FCA and Horn logic for ontology extraction and representation (H-M. Haav) • Learning user browsing behavior ontology for recommender systems. • The knowledge acquired from users’ browsing behavior is used for learning profile ontology and formulating explicit user profiles in OWL-DL for recommender systems. The method exploits the automated reasoning capabilities provided by OWL-DL in order to automatically classify user profiles. (H-M. Haav, A. Kalja, T. Robal) • Ontology learning from relational databases (I. Astrova, A. Kalja) EXCS Sept. 19 2008

6. General schema of ontology learning using FCA Domain specific texts or data NLP based context extraction Set of rules describing initial ontology FCA and reduction Concept lattice based ontology expression Transformations Formal Context More rules and facts automatic Complete set of rules and facts representing ontology Expert manually Inference EXCS Sept. 19 2008

7. The process of user profile learning method EXCS Sept. 19 2008

8. Ontologies and their Applications Ontology Applications Smart ontology-based spatial data retrieval Partners: IoC (H-M. Haav), companies Regio, Girf new project 2008-2009, partially funded by Enterprise Estonia via ELIKO Competence Center in Electronics-, Info- and Communication Technologies Semantic interoperability of large scale IS: The Estonian public sector’s case study(H-M. Haav, A. Kalja, P. Küngas, M.Luts) Automatic transformation of OWL ontologies to relational databases (SQL) and storing them in relational databases (I. Astrova, A. Kalja) EXCS Sept. 19 2008

9. Semantic interoperability architecture for state information system in Estonia EXCS Sept. 19 2008

10. Modularity and layering of ontologies component in interoperability architecture EXCS Sept. 19 2008

11. (Sem)web services • Composition of web services using structural synthesis of programs and visual specifications (the CoCoViLa system) (E. Tyugu, P. Grigorenko, R. Maigre) • Web service composition using FOL theorem prover RqlGandalf. • RQL (Rule-based Systems for Creation of Web Services) project partially funded by Enterprise Estonia, 2004-2005. • Partners: Institute of Computer Science of TUT, Cell Networks, Sampo Assets Management). • T. Tammet, H-M. Haav, M. Kääramees, V. Kadarpik, K. Kindel • Annotation of web services using OWL ontologies and SAWSDL for support of semantic interoperability of state IS (H.-M. Haav, A. Kalja, P. Küngas, M. Luts) EXCS Sept. 19 2008

12. Web service composition with CoCoViLa • Automatic service composition tool has been developed in software development environment CoCoViLa that supportsautomatic synthesis of programs and generates Java code from visual and textual model specifications • User can define desired complex service that is synthesize automatically (if it is possible to construct the service).BPEL and WSDL descriptions of the complex service are thengenerated from Java code. • Tool has been tested on federated governmental information system. EXCS Sept. 19 2008

13. Web service composition in RQL A goal of the system is to automatically find a plan for service composition as an answer to the user request. The result of program synthesis is as a Python program corresponding to the required composite service. EXCS Sept. 19 2008

14. RQL • Provides a new conceptual and technological framework for using a rule language and a rule engine for capturing application semantics in modern web-based systems. • The approach enables to deal with two aspects of semantics in web-based systems: business rules and web service composition logic. EXCS Sept. 19 2008

15. Future plans • SE 2.0* • Domain centred problem solving • Domain semantics is the key to deal with next generation technologies * Dillon T. S, Chang E., Wongthongtham P., "Ontology-Based Software Engineering- Software Engineering 2.0," aswec, pp. 13-23,  19th Australian Conference on Software Engineering (aswec 2008), 2008 EXCS Sept. 19 2008

16. Ontology-based SE • Use of ontologies in different aspects of software engineering • Ontology Based Multi-Site Software Development • Ontology Mediated Information Access • Ontology and Semantic Web Services • Ontology based Multi Agent Systems EXCS Sept. 19 2008