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

2. EXCS Sept. 19 20082 Outline KE SE Knowledge- based systems Ontologies and their applications (Semantic) web services

3. EXCS Sept. 19 20083 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 ) 

4. EXCS Sept. 19 20084 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

5. EXCS Sept. 19 20085 Ontologies and their Applications Ontology 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)

6. EXCS Sept. 19 20086 FCA and reduction Concept lattice based ontology expression Transformations Set of rules describing initial ontology More rules and facts Complete set of rules and facts representing ontology Inference Domain specific texts or data NLP based context extraction Formal Context General schema of ontology learning using FCA automatic Expert manually

7. EXCS Sept. 19 20087 The process of user profile learning method

8. EXCS Sept. 19 20088 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)

9. EXCS Sept. 19 20089 Semantic interoperability architecture for state information system in Estonia

10. EXCS Sept. 19 200810 Modularity and layering of ontologies component in interoperability architecture

11. EXCS Sept. 19 200811 (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)

12. EXCS Sept. 19 200812 Web service composition with CoCoViLa Automatic service composition tool has been developed in software development environment CoCoViLa that supports automatic 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 then generated from Java code. Tool has been tested on federated governmental information system.

13. EXCS Sept. 19 200813 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.

14. EXCS Sept. 19 200814 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.

15. EXCS Sept. 19 200815 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

16. EXCS Sept. 19 200816 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