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Towards a PROV Ontology for Simulation Models

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11017))

Abstract

Simulation models and data are the primary products of simulation studies. Although the provenance of simulation data and the support of single simulation experiments have received a lot of attention, this is not the case for simulation models. The question of how a simulation model has been generated requires to integrate diverse simulation experiments and entities at different levels of abstractions within and across entire simulation studies. Based on a concrete simulation model, we will use the PROV Data Model (PROV-DM) and illuminate the benefits of the PROV-DM approach to identify and relate entities and activities that contributed to the generation of a simulation model, thereby taking first steps in defining a PROV-DM ontology for simulation models.

The research was funded by the DFG (German Research Foundation) UH 66/18 “GrEASE” and by DFG CRC 1270 “Elaine”.

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Correspondence to Andreas Ruscheinski .

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Ruscheinski, A., Gjorgevikj, D., Dombrowsky, M., Budde, K., Uhrmacher, A.M. (2018). Towards a PROV Ontology for Simulation Models. In: Belhajjame, K., Gehani, A., Alper, P. (eds) Provenance and Annotation of Data and Processes. IPAW 2018. Lecture Notes in Computer Science(), vol 11017. Springer, Cham. https://doi.org/10.1007/978-3-319-98379-0_17

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  • DOI: https://doi.org/10.1007/978-3-319-98379-0_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-98378-3

  • Online ISBN: 978-3-319-98379-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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