«Combining formal and informal representations in information

Transcription

1 1 Trial lecture «Combining formal and informal representations in information systems development» Geir Solskinnsbakk kk November 16, 2012

2 2 Outline Introduction / Background Formal vs. Informal Ontologies in Information Systems Development Conclusion

3 3 Outline Introduction / Background Formal vs. Informal Ontologies in Information Systems Development Conclusion

4 4 Combining formal and informal representations in information systems development What does it mean to combine formal and informal representations? Formalize the informal? Throw away the informal? Let them coexist? Turn formal into informal? From informal to formal Formalize information / knowledge Level of formality is not well defined (fuzzy) Formalization may improve the informal representation

5 5 Formal vs. Informal Figure from [Uschold 2003]

6 6 What is a representation? Figures from: g p p g p p p g j p [Giese 2004]

7 7 Models Engineering: Models are important for understanding the problem [Selic 2003] Constructing bridge Models have been in wide use for years in IS Three levels of (information)models [Mylopoulos 1998] Physical (physical implementation, data types) Logical (mathematical abstraction, relational model) Conceptual (abstraction, expressiveness, ER model)

8 8 Models as communication Figure from [Krogstie 2012]

9 9 Information systems development Common phases in most methodologies Analysis Requirements Engineering Design Implemented systems

10 10 Outline Introduction / Background Formal vs. Informal Ontologies in Information Systems Development Conclusion

11 11 Formal vs. Informal Representations Formal: What is considered formal depends on who you ask Well defined semantics? Machine readable? Mathematical / logical specification? Informal Less well defined d semantics Natural language

12 12 Formal vs. Informal Representations Formal: What is considered formal depends on who you ask Well defined semantics Machine readable Mathematical / logical specification Informal No well defined d semantics Natural language Vienna Development Method (VDM) Data Flow Diagram (DFD)

13 13 Ontology spectrum

14 14 Why formal representations? Verification / consistency checking Contract t towards customer / subcontractor t Code generation Disambiguating communication between requirements engineer, designer, coder, tester Integration of artifacts throughout the lifecycle

15 15 Why informal representations? Customer communication Simple to construct/express t/ Iterative exploration of solution space Flexibility?

16 16 Formal and informal Communication Simplicity Flexibility Informal Formal Customer contract Disambiguation Code generation Verification

17 17 Formal and informal Communication Simplicity Flexibility Informal Formal Customer contract Disambiguation Code generation Verification

18 18 Outline Introduction / Background Formal vs. Informal Examples Ontologies in Information Systems Development Conclusion

19 19 From informal to formal Formalizing requirements engineering Start t with DFD Hierarchically decompose DFD Use VDM at each level to iteratively get the full VDM specification VDM Formal Predicate Logic & Set theory Formal proofs Authors argue for precise communication between developers [Fraser 1991]

20 20 From Informal to formal DFD Formalize [Fraser 1991] VDM

21 21 Formalizing Use cases [Giese 2004]

22 22 Extraction of process models Aquisition of as-is models consumes up to 60% of time for process management age e projects Extraction process: Sentence level analysis Text level analysis Process model generation [Friedrich 2011]

23 23 Informal and formal Challenges Going from informal to formal Precision in automation (e.g. 77% of the tested models in [Friedrich 2011] were correct) Keeping formal/informal f models living side-by-side in syncronization Opportunities Clarification of communication Improve the informal representation through formalization Allow more automation

24 24 Outline Introduction / Background Formal vs. Informal Ontologies in Information Systems Development Conclusion

25 25 Recent activities Semantic Web Standardization of formal representations Inspiration to SE and IS development Knowledge Based Engineering g (KBE) Ontology as part of the methodology Can KBE serve as inspiration for IS development?

26 26 Ontologies in IS development Ontology: A formal specification of a conceptualization [Gruber 1993] Defines concepts, relations, instances Provides a means for Shared knowledge Information exchange Reasoning Much focus on ontologies in IS development Inspired by Semantic Web community

27 27 KBE MOKA and CATIA Reduce time for routine design (80%) [Skarka 2007]

28 28 Ontologies in Development [Happel 2006a]

29 29 Ontology Driven Development Model Driven Architecture (MDA) Ontologies for: [Tetlow 2006] Unabiguous domain vocabularies Validation Consistency checking Model reasoning

30 30 Ontology Enabled Development Ontology at development time supporting development tasks Problem solving support Requirements specification Component reuse

31 31 Ontology Enabled Development Example: Component reuse [Happel 2006b]

32 32 Ontology Based Architecture Example: Business rules Separates business logic from application logic (hence we already have a model of the business as Object Models) OWL ontology as part of the model [Ghali 2012] Translating OWL axioms into business rules Increases the understanding of the domain Increases the expressiveness of the model(s)

33 33 Ontology Enabled Architectures Example: Semantic Web Services OWL-S Profile Process model Grounding Enable semantic discovery, composition, etc. of web services Allows to integrate web services more intelligently [Martin 2004]

34 34 Outline Introduction / Background Formal vs. Informal Ontologies in Information Systems Development Conclusion

35 35 Combining formal and informal representations Challenges Automation Keeping formal/informal representation in synchronization Opportunities Integration Communication Automation Reliability

36 36 Ontology-Driven Information Systems ODIS: Ontology is a central piece in development and end product Visions [Uschold 2008] Elements of an application are represented in a uniform way Applications are manifest as giant networks of semantic agents that represent the models The semantic agents are fully version controlled and stored in a transactional database There is no code generation step, the models are already executing as they are being built Virtually no handwritten code for normal development Virtually all functionality is specified in a visual environment by creating and linking pre-coded semantic agents No computer science background is required to develop applications

37 37 Conclusions Synergies can be obtained by combining formal and informal Communication Integration Reliability Future directions Much focus on Model Driven Development points in the general direction of Uscholds visions Automation of IS development

38 38 Tank you for your attention!

39 39 References [Fraser 1991] Fraser, M., Kumar, K., Vaishnavi, V.K.: Informal and Formal Requirements Specification Languages: Bridging the Gap. IEEE Transactions on Software Engineering 17(5), 1991 [Friedrich 2011] Friedrich, F., Mendling, J., Puhlman, F.: Process Model Generation from Natural Language Text. CAiSE 2011, LNCS 6741, Springer, pp , 2011 [Ghali 2012] Ghale, A.E., Chniti, A., Citeu, H.: Bringing OWL Ontologies to the Business Rules Users. Proceedings of RuleML 2012, LNCS 7438, Springer, [Giese 2004] Giese, M. and Heldal, R.: From Informal to Formal Specifications in UML. <<UML>> 2004 The Unified Modeling Language. Modeling Languages and Applications. LNCS Volume 3273, Springer, 2004, pp [Gruber 1993] Gruber, T.: A translation approach to portable ontology specifications. Knowledge Acquisition, 5(2): , [Happel 2006a] Happer, H., Seedorf, S.: Applications of Ontologies in Software Engineering. 2nd International Workshop on Semantic Web Enabled Software Engineering (SWESE 2006), held at the 5th International Semantic Web Conference (ISWC 2006). [Happel 2006b] Happel, H., Korthaus, A., Seedorf, S., Tomczyk, P.: KOntoR: An Ontology-enabled ogy ed Approach to Software Reuse. Proceedings of the 18th Conference on Software Engineering and Knowledge Engineering (SEKE), 2006 [Krogstie 2012] Krogstie, J: Model-Based Development and Evolution of Information Systems, Springer, [Martin 2005] Martin, D., Paolucci, M., McIlraith, S., Burstein, M., McDermott, D., McGuinness, D., Parsia, B., Payne, T., Sabou, M., Solanki, M., Srinivasan, N., Sycara, K.: Bringing Semantics to Web Services: The OWL-S Approach. SWSWPC 2004, LNCS 3387, Springer, 2005 [Mylopoulos 1998] Mylopoulos, J.: Information Modeling in the Time of the Revolution. Information Systems 23(3-4), June [Selic 2003] Selic, B.: The Pragmatics of Model-Driven Development, IEEE Software, vol. 20, no. 5, 2003, pp [Skarka 2007] Skarka, W.: Application of MOKA methodology in generative model creation using CATIA. Engineering Applications of Artificial Intelligence 20, pp , [Tetlow 2006] Eds: Tetlow, P. Pan, J., Oberle, D., Wallace, E., Uschold, M., Kendall, E.: Ontology Driven Architectures and Potential Uses of the Semantic Web in Systems and Software Engineering, W3C Working Draft, 2006 [Uschold 2003] Uschold, M.: Where are the semantics in the semantic web? Ai Mag. 24(3):25-36, 2003 [Uschold 2008] Uscold, M.: Ontology-Driven Information Systems: Past, Present and Future. Invited paper to Formal Ontology in Information Systems, IOS Press, 2008.