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Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory

By Arash Shaban-Nejad, Olga Ormandjieva, Mohamad Kassab and Volker Haarslev

Abstract

Requirement volatility is an issue in software engineering in general, and in Web-based clinical applications in particular, which often originates from an incomplete knowledge of the domain of interest. With advances in the health science, many features and functionalities need to be added to, or removed from, existing software applications in the biomedical domain. At the same time, the increasing complexity of biomedical systems makes them more difficult to understand, and consequently it is more difficult to define their requirements, which contributes considerably to their volatility. In this paper, we present a novel agent-based approach for analyzing and managing volatile and dynamic requirements in an ontology-driven laboratory information management system (LIMS) designed for Web-based case reporting in medical mycology. The proposed framework is empowered with ontologies and formalized using category theory to provide a deep and common understanding of the functional and nonfunctional requirement hierarchies and their interrelations, and to trace the effects of a change on the conceptual framework

Topics: Research Article
Publisher: Hindawi Publishing Corporation
OAI identifier: oai:pubmedcentral.nih.gov:2662492
Provided by: PubMed Central
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    Citations

    1. (2001). A formal foundation for object-oriented software evolution,” in
    2. (2006). A framework for ontology evolution in collaborative environments,”
    3. (1993). A matrix for the development of a strategic laboratory information management system,”
    4. (2005). a p o b i a n c o ,C .I .C h e s ˜
    5. (1993). A translation approach to portable ontology specifications,”
    6. (1990). Abstract and Concrete Categories: The Joy of Cats,
    7. (1994). An analysis of the requirements traceability problem,”
    8. (2003). Architectures for negotiating agents,”
    9. (2006). Automating proofs in category theory,”
    10. (2006). C.J.O.BakerandR.Witte,“Mutationmining—aprospector’s tale,” Information Systems Frontiers,
    11. (2007). Categorical representation of evolving structure of an ontology for clinical fungus,”
    12. Categories for Software Engineering,
    13. (2004). Concept-centric approach to software evolution,”
    14. (1994). Coping with changing controlled vocabularies,”
    15. Dynamic structure theory: a structural approach to social and biological systems,”
    16. (1986). e, “Elements of categorical reasoning: products and coproducts and some other (Co-) limits,”
    17. (2001). Electronic laboratory reporting: barriers, solutions and findings,”
    18. Evolving categories: consistent framework for representation of data and algorithms,”
    19. (2007). Facilitating project management by capturing requirements quality and volatility information,”
    20. Gene Expression Data-MGED,
    21. (2002). Gene expression informatics,” PharmaGenomics,
    22. Gene Expression Markup Language,
    23. (1945). General theory of natural equivalences,”
    24. (2000). Implementing LIMS: a “how-to” guide,”
    25. (2008). Incremental biomedical ontology change management through learning agents,”
    26. (2004). Intelligent Agents: Theory and Applications,
    27. (2001). Introduction to Automata Theory, Languages, and Computation,
    28. (2006). Kr¨ o t z s c h ,J .E u z e n a t ,a n dP .H i t z l e r , “Formalizing ontology alignment and its operations with category theory,”
    29. Minimum Information about a Microarray Experiment,
    30. (2007). Modelling multi-agent interaction protocols using categories enriched over pointed sets,”
    31. (1997). Object Oriented Design Measurement,J o h n
    32. (1998). On argumentation-based negotiation,”
    33. (2006). Ontologies and worlds in category theory: implications for neural systems,”
    34. (1998). Requirements Engineering: Processes and Techniques,
    35. (1999). Requirements volatility and defect density,”
    36. (2006). Revisiting ontology-based requirements engineering in the age of the semantic web,”
    37. (2006). Semantic web infrastructure for fungal enzyme biotechnologists,” Web Semantics: Science,
    38. (1999). Shortliffe ,a n dM .A .M u s e n , “Representation of change in controlled medical terminologies,”
    39. (1996). The language of general systems logical theory: a categorical view,”
    40. (2006). The memory evolutive systems as a model of Rosen’s organisms-(metabolic,
    41. (1958). The representation of biological systems from the standpoint of the theory of categories,”
    42. (2005). u r t za n dB .J .C a m e r o n ,“ E l e c t r o n i cl a b o r a t o r yr e p o r t i n g for the infectious diseases physician and clinical microbiologist,” Clinical Infectious Diseases,
    43. (2003). V.HaarslevandR.M¨ oller,“Descriptionlogicsforthesemantic web: racer as a basis for building agent systems,”
    44. (1998). V.WielsandS.Easterbrook,“Managementofevolvingspecifi-cations using category theory,”
    45. (2003). W i e g e r s ,Software Requirements,
    46. (2005). What is ontology merging?—a category-theoretical perspective using pushouts,”
    47. (2007). When is one thing equal to some other thing?”

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