Guardado en:
| Autores principales: | , , , , , , , , , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2023
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2310.05649 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866929290359078912 |
|---|---|
| author | Uhrmacher, Adelinde Frazier, Peter Hähnle, Reiner Klügl, Franziska Lorig, Fabian Ludäscher, Bertram Nenzi, Laura Ruiz-Martin, Cristina Rumpe, Bernhard Szabo, Claudia Wainer, Gabriel A. Wilsdorf, Pia |
| author_facet | Uhrmacher, Adelinde Frazier, Peter Hähnle, Reiner Klügl, Franziska Lorig, Fabian Ludäscher, Bertram Nenzi, Laura Ruiz-Martin, Cristina Rumpe, Bernhard Szabo, Claudia Wainer, Gabriel A. Wilsdorf, Pia |
| contents | Simulation has become, in many application areas, a sine-qua-non. Most recently, COVID-19 has underlined the importance of simulation studies and limitations in current practices and methods. We identify four goals of methodological work for addressing these limitations. The first is to provide better support for capturing, representing, and evaluating the context of simulation studies, including research questions, assumptions, requirements, and activities contributing to a simulation study. In addition, the composition of simulation models and other simulation studies' products must be supported beyond syntactical coherence, including aspects of semantics and purpose, enabling their effective reuse. A higher degree of automating simulation studies will contribute to more systematic, standardized simulation studies and their efficiency. Finally, it is essential to invest increased effort into effectively communicating results and the processes involved in simulation studies to enable their use in research and decision-making. These goals are not pursued independently of each other, but they will benefit from and sometimes even rely on advances in other subfields. In the present paper, we explore the basis and interdependencies evident in current research and practice and delineate future research directions based on these considerations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_05649 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Context, Composition, Automation, and Communication -- The C2AC Roadmap for Modeling and Simulation Uhrmacher, Adelinde Frazier, Peter Hähnle, Reiner Klügl, Franziska Lorig, Fabian Ludäscher, Bertram Nenzi, Laura Ruiz-Martin, Cristina Rumpe, Bernhard Szabo, Claudia Wainer, Gabriel A. Wilsdorf, Pia Computational Engineering, Finance, and Science I.6 Simulation has become, in many application areas, a sine-qua-non. Most recently, COVID-19 has underlined the importance of simulation studies and limitations in current practices and methods. We identify four goals of methodological work for addressing these limitations. The first is to provide better support for capturing, representing, and evaluating the context of simulation studies, including research questions, assumptions, requirements, and activities contributing to a simulation study. In addition, the composition of simulation models and other simulation studies' products must be supported beyond syntactical coherence, including aspects of semantics and purpose, enabling their effective reuse. A higher degree of automating simulation studies will contribute to more systematic, standardized simulation studies and their efficiency. Finally, it is essential to invest increased effort into effectively communicating results and the processes involved in simulation studies to enable their use in research and decision-making. These goals are not pursued independently of each other, but they will benefit from and sometimes even rely on advances in other subfields. In the present paper, we explore the basis and interdependencies evident in current research and practice and delineate future research directions based on these considerations. |
| title | Context, Composition, Automation, and Communication -- The C2AC Roadmap for Modeling and Simulation |
| topic | Computational Engineering, Finance, and Science I.6 |
| url | https://arxiv.org/abs/2310.05649 |