A Semantic Approach to Deploying Product-Service Systems:

Robert Andrei Buchmann and Dimitris Karagiannis

Conceptual modeling is commonly employed for two classes of goals: (1) as input for run-time functionality (e.g., code generation) and (2) as support for design-time analysis (e.g., in business process management). An inherent trade-off manifests between such goals, as different levels of abstraction and semantic detail is needed. This has led to a multitude of modeling languages that are conceptually redundant (i.e., they share significant parts of their metamodels) and a dilemma of selecting the most adequate language for each goal. This article advocates the substitution of the selection dilemma with an approach where the modeling method is agilely tailored for the semantic variability required to cover both run-time and design-time concerns. The semantic space enabled by such a method is exposed to model-driven systems as RDF knowledge graphs, whereas the method evolution is managed with the Agile Modeling Method Engineering framework. The argument is grounded in the application area of Product-Service Systems, illustrated by a project-based modeling method.

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Robert Andrei Buchmann, Dimitris Karagiannis: A Semantic Approach to Deploying Product-Service Systems:. In: International Journal of Information System Modeling and Design, vol. 8, no. 1, pp. 24–42, 2017, ISSN: 1947-8186, 1947-8194.

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@article{buchmann_semantic_2017,
title = {A Semantic Approach to Deploying Product-Service Systems:},
author = {Robert Andrei Buchmann and Dimitris Karagiannis},
url = {http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJISMD.2017010102},
doi = {10.4018/IJISMD.2017010102},
issn = {1947-8186, 1947-8194},
year  = {2017},
date = {2017-01-01},
urldate = {2020-11-24},
journal = {International Journal of Information System Modeling and Design},
volume = {8},
number = {1},
pages = {24–42},
abstract = {Conceptual modeling is commonly employed for two classes of goals: (1) as input for run-time functionality (e.g., code generation) and (2) as support for design-time analysis (e.g., in business process management). An inherent trade-off manifests between such goals, as different levels of abstraction and semantic detail is needed. This has led to a multitude of modeling languages that are conceptually redundant (i.e., they share significant parts of their metamodels) and a dilemma of selecting the most adequate language for each goal. This article advocates the substitution of the selection dilemma with an approach where the modeling method is agilely tailored for the semantic variability required to cover both run-time and design-time concerns. The semantic space enabled by such a method is exposed to model-driven systems as RDF knowledge graphs, whereas the method evolution is managed with the Agile Modeling Method Engineering framework. The argument is grounded in the application area of Product-Service Systems, illustrated by a project-based modeling method.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}