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DOGMA, short for ''Developing Ontology-Grounded Methods and Applications'', is the name of research project in progress at Vrije Universiteit Brussel's STARLab, Semantics Technology and Applications Research Laboratory. It is an internally funded project, concerned with the more general aspects of extracting, storing, representing and browsing information.〔(【引用サイトリンク】 Welcome to VUB STARLab )〕 == Methodological Root == DOGMA, as a dialect of the (fact-based modeling ) approach, has its root in database semantics and model theory.〔Peter Spyns, Yan Tang and Robert Meersman, An Ontology Engineering Methodology for DOGMA, Journal of Applied Ontology, special issue on "Ontological Foundations for Conceptual Modeling", Giancarlo Guizzardi and Terry Halpin (eds.), Volume 3, Issue 1-2, p.13-39 (2008)〕 It adheres to the fact-based information management methodology towards Conceptualization and 100% principle of (ISO TR9007 ). The DOGMA methodological principles include: #Data independence: the meaning of data shall be decoupled from the data itself. #Interpretation independence: unary or binary fact types (i.e. lexons) shall be adhere to formal interpretation in order to store semantics; lexons themselves do not carry semantics 〔Meersman, R: Ontologies and databases: more than a fleeting resemblance. In A. d'Atri & M. Miskoff (eds.), OES/SEO 2001 Rome Workshop, Luiss Publications〕 #Multiple views on and uses of stored conceptualization. An ontology shall be scalable and extensible. #Language neutral. An ontology shall meet multilingual needs.〔Yan Tang Demey and Clifford Heath, Towards Verbalizing Multilingual N-ary Relations, in book “Towards the Multilingual Semantic Web”, Paul Buitlaar and Philipp Cimiano (eds.), ISBN 978-3-662-43584-7, Chapter 6, 2014〕 #Presentations independence: an ontology in DOGMA shall meet any kinds of users' needs of presentation. As an FBM dialect, DOGMA supports both graphical notations and textual presentation in a controlled language.〔FBM Working Draft, European Space Agency.〕 Semantic decision tables, for example, is a means to visualize processes in a DOGMA commitment. SDRule-L 〔Yan Tang and Robert Meersman, SDRule Markup Language: Towards Modeling and Interchanging Ontological Commitments for Semantic Decision Making, Chapter V. (Section I) in "Handbook of Research on Emerging Rule-Based Languages and Technologies: Open Solutions and Approaches", IGI Publishing, ISBN 1-60566-402-2, USA, 2009〕 is to visualize and publish ontology-based decision support models. #Concepts shall be validated by the stakeholders. #Informal textual definitions shall be provided in case the source of the ontology is missing or incomplete. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「DOGMA」の詳細全文を読む スポンサード リンク
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