Authors:
Estefanía Serral
;
Olga Kovalenko
;
Thomas Moser
and
Stefan Biffl
Affiliation:
Vienna University of Technology, Austria
Keyword(s):
Multidisciplinary Projects, Data Integration, Ontologies, Querying Across Disciplines.
Related
Ontology
Subjects/Areas/Topics:
Languages, Tools and Architectures
;
Methodologies, Processes and Platforms
;
Model Transformation
;
Model Transformations and Generative Approaches
;
Model-Driven Software Development
;
Models
;
Paradigm Trends
;
Reasoning about Models
;
Software Engineering
Abstract:
Multidisciplinary projects typically rely on the contributions of various disciplines using heterogeneous engineering tools. This paper focuses on the challenge of querying across different disciplines, which may be influenced by the selection of a proper instance data storage architecture for storing the heterogeneous tool data. Specifically, we have identified three different architectures: ontology file stores, triple stores and relational database stores. This paper systematically compares these architectures using an industrial case study and analyses their selection according to important requirements such as performance and maintainability.