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Relational Contexts and Conceptual Model Clustering
- Source :
- Lecture Notes in Business Information Processing ISBN: 9783030634780, PoEM, Lecture Notes in Business Information Processing, 13th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modeling (PoEM 2020), 13th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modeling (PoEM 2020), Nov 2020, Riga, Latvia. pp.211-227, ⟨10.1007/978-3-030-63479-7_15⟩, The practice of enterprise modeling, 13th IFIP Working Conference, PoEM 2020
- Publication Year :
- 2020
- Publisher :
- Springer International Publishing, 2020.
-
Abstract
- Part 5:Enterprise Ontologies; International audience; In recent years, there has been a growing interest in the use of reference conceptual models to capture information about complex and sensitive business domains (e.g., finance, healthcare, space). These models play a fundamental role in different types of critical semantic interoperability tasks. Therefore, it is essential that domain experts are able to understand and reason with their content. In other words, it is important for these reference conceptual models to be cognitively tractable. This paper contributes to this goal by proposing a model clustering technique that leverages the rich semantics of ontology-driven conceptual models (ODCM). In particular, the technique employs the notion of Relational Context to guide automated model breakdown. Such Relational Contexts capture all the information needed for understanding entities “qua players of roles” in the scope of an objectified (reified) relationship (relator).
- Subjects :
- Scope (project management)
Computer science
media_common.quotation_subject
02 engineering and technology
Space (commercial competition)
Semantic interoperability
Complexity management in conceptual modeling
Semantics
Data science
Domain (software engineering)
Business and Economics
Conceptual model clustering
020204 information systems
0202 electrical engineering, electronic engineering, information engineering
Relational context
Conceptual model
[INFO]Computer Science [cs]
020201 artificial intelligence & image processing
Cluster analysis
media_common
Subjects
Details
- ISBN :
- 978-3-030-63478-0
978-3-030-63479-7 - ISSN :
- 18651348 and 18651356
- ISBNs :
- 9783030634780 and 9783030634797
- Database :
- OpenAIRE
- Journal :
- Lecture Notes in Business Information Processing ISBN: 9783030634780, PoEM, Lecture Notes in Business Information Processing, 13th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modeling (PoEM 2020), 13th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modeling (PoEM 2020), Nov 2020, Riga, Latvia. pp.211-227, ⟨10.1007/978-3-030-63479-7_15⟩, The practice of enterprise modeling, 13th IFIP Working Conference, PoEM 2020
- Accession number :
- edsair.doi.dedup.....7f4a1beb1d3d53d42d20bec776bd41b9
- Full Text :
- https://doi.org/10.1007/978-3-030-63479-7_15