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Artifact-Based Workflows for Supporting Simulation Studies

delete2020-06-01
delete10
PRE
AI
A
Andreas Ruscheinski *
T
Tom Warnke
A
Adelinde M. Uhrmacher
DOI:10.1109/TKDE.2019.2899840delete
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摘要

摘要

En 中文
Valid models are central for credible simulation studies. If those models do not exist, they need to be developed. In fact, entire simulation studies are often aimed at developing valid models. Thereby, successive model refinement and execution of diverse simulation experiments are closely intertwined. Whereas software-based support for individual simulation experiments exists, the intricate interdependencies and the diversity of tasks that govern simulation studies have prevented a more comprehensive support. To achieve the required flexibility while adhering to the constraints that apply between individual tasks, we adopt a declarative, artifact-based workflow approach. Therefore, central products of these simulation studies are identified and specified as artifacts: the conceptual model (with a focus on formally defined requirements), the simulation model, and the experiment. Each artifact is characterized by stages the artifact moves through to reach certain milestones and which are guarded by conditions. Thereby, the relations and constraints between artifacts become explicit. This is instrumental to check and ensure the consistency between conceptual model and simulation model, to automatically execute simulation experiments to probe the specified requirements, and to develop plans to provide goal-directed guidance to the user. We demonstrate the approach by using it to repeat an existing simulation study.
Keyword:
Data models
Analytical models
Computational modeling
Mathematical model
Adaptation models
Biological system modeling
Context modeling
Modeling and simulation life cycle
simulation study
artifact-based workflows
planning
user support
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期刊

IEEE Transactions on Knowledge and Data Engineering 封面图
IEEE Transactions on Knowledge and Data Engineering
IF:
10.4
论文数:
6.8K
被引数:
3.2W

机构

U
University of Rostock
学者数:
9.5K
论文数: 7.6K
被引数: 11
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