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Dagstuhl-Seminar 22401

Computer Science Methods for Effective and Sustainable Simulation Studies

( 03. Oct – 07. Oct, 2022 )

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Bitte benutzen Sie folgende Kurz-Url zum Verlinken dieser Seite: https://www.dagstuhl.de/22401

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Dagstuhl Reports

As part of the mandatory documentation, participants are asked to submit their talk abstracts, working group results, etc. for publication in our series Dagstuhl Reports via the Dagstuhl Reports Submission System.

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Gemeinsame Dokumente


Programm

Summary

Motivation. Simulation becomes more and more important in application areas, establishing itself as the third way of science in addition to theory and (real) experiments. To answer research questions, simulation studies form increasingly intricate processes that intertwine the design and execution of various, often calculation-intensive simulation experiments, the generation and refinement of simulation models, and steps of analysis.

Schedule of the Dagstuhl Seminar Computer Science Methods for Effective and Sustainable Simulation Studies.
Figure 1 Schedule of the Dagstuhl Seminar Computer Science Methods for Effective and Sustainable Simulation Studies.

The Dagstuhl Seminar has been dedicated to addressing central methodological challenges in supporting the conduction of effective and sustainable simulation studies. Thereby, the seminar focused on problems and solutions related to improving:

  • Effectiveness: the usage of resources, including computing infrastructure and data, and the assistance of humans throughout a simulation study.
  • Sustainability: continuing a simulation study into the future through support for reusing or building upon its central products, such as simulation model, data, and processes as well as the software used.

The last decades have seen a wide range of methodological developments in computer science that are likely to be instrumental in achieving effective and sustainable simulation studies. However, those efforts are scattered across different computer science fields that include high-performance computing, (modeling) language design, operations research, visual analytics, workflows, provenance, and machine learning, as well as modeling and simulation. The seminar brought participants with diverse computer science backgrounds together to enhance the methodological basis for conducting simulation studies.

Organization and results. Being one day shorter than typical seminars, the seminar started on Tuesday with a short round of introduction and continued with collecting ideas about achievements and challenges of modeling and simulation from the participants on 2 pinboards (see Figure 1). 3 talks and partly extensive discussions followed, one focusing on modeling and model-based approaches applied to simulation studies, one on high-performance computing for simulation, and one on analysis and experiment designs. In the late afternoon, the information gathered on the pinboards was revisited. In the end 3 working groups formed to work towards state-of-the-art and open-challenges papers on the following topics:

  • Intelligent Modeling and Simulation Lifecycle
  • Policy by simulation: seeing is believing for interactive model co-creation and effective intervention
  • Context, composition, automation, and communication: towards sustainable simulation studies

Among the application fields as diverse as cell biological systems, traffic systems, or computer networks, one application dominated the discussions, i.e., Covid 19 simulation. The Covid pandemic showed the importance of modeling and simulation studies being conducted in an efficient, reliable manner, and, accordingly, of comprehensive, intelligent computer support for these studies, it revealed limitations, including those referring to communicating effectively modeling and simulation studies and their results to decision-makers. The results of the working groups are included as short summaries in this report. Wednesday afternoon, the participants presented their current research work and ideas in a series of lightning talks whose abstracts are also included in the report. However, most of the time was dedicated to the working groups. Plenary sessions on Thursday and finally on Friday allowed the participants to catch up with ideas and the progress made in the different working groups.

Copyright Adelinde M. Uhrmacher, Wentong Cai, Christopher Carothers, and David M. Nicol

Motivation

Simulation becomes more and more important in application areas, establishing itself as the third way of science in addition to theory and (real) experiment. To answer research questions, simulation studies form increasingly intricate processes that intertwine the design and execution of various, often calculation-intensive simulation experiments, the generation and refinement of simulation models, and steps of analysis.

The Dagstuhl Seminar will be dedicated towards addressing central methodological challenges in supporting the conduction of effective and sustainable simulation studies. Thereby, the seminar will focus on problems and solutions related to improving:

  • Effectiveness: the usage of resources, including computing infrastructure and data, and the assistance of humans throughout a simulation study.
  • Sustainability: continuing a simulation study into the future through support for reusing or building upon its central products, such as simulation model, data, and processes as well as the software used.

The last decades have seen a wide range of methodological developments in computer science that are likely to be instrumental in achieving effective and sustainable simulation studies. However, those efforts are scattered across different computer science fields that include high performance computing, (modeling) language design, operations research, visual analytics, workflows, provenance, machine learning, as well as modeling and simulation.

The seminar aims to bring participants with diverse computer science backgrounds together to enhance the methodological basis for conducting simulation studies. The researchers' expertise in developing methods and applying them in application fields as diverse as cell biological systems, traffic systems, or computer networks, will allow to identify and relate core problems and solutions in conducting simulation studies across specific application fields. As results of the seminar, we expect having identified central challenges relating to effective and sustainable simulation studies, analyzed the state of the art, and gathered potential contributions from the various computer science areas. The seminar hopes to spawn new research directions and collaborations to advance the field of modeling and simulation.

Copyright Wentong Cai, Christopher Carothers, and Adelinde M. Uhrmacher

Teilnehmer
Vor Ort
  • Philipp Andelfinger (Universität Rostock, DE) [dblp]
  • Luca Bortolussi (University of Trieste, IT) [dblp]
  • Wentong Cai (Nanyang TU - Singapore, SG) [dblp]
  • Rodrigo Castro (University of Buenos Aires, AR) [dblp]
  • Joachim Denil (University of Antwerp, BE)
  • Jérôme Feret (ENS - Paris, FR) [dblp]
  • Peter Frazier (Cornell University - Ithaca, US) [dblp]
  • Reiner Hähnle (TU Darmstadt, DE) [dblp]
  • Dong (Kevin) Jin (University of Arkansas - Fayetteville, US)
  • Franziska Klügl (University of Örebro, SE) [dblp]
  • Till Köster (Universität Rostock, DE) [dblp]
  • Michael Lees (University of Amsterdam, NL)
  • Jason Liu (Florida International University - Miami, US) [dblp]
  • Margaret Loper (Georgia Institute of Technology - Atlanta, US)
  • Fabian Lorig (Malmö University, SE) [dblp]
  • Bertram Ludäscher (University of Illinois at Urbana-Champaign, US) [dblp]
  • Kresimir Matkovic (VRVis - Wien, AT) [dblp]
  • Laura Nenzi (University of Trieste, IT) [dblp]
  • Alessandro Pellegrini (University of Rome "Tor Vergata", IT) [dblp]
  • Niki Popper (Technische Universität Wien, AT)
  • Caitlin Ross (Kitware - Clifton Park, US) [dblp]
  • Cristina Ruiz-Martin (Carleton University - Ottawa, CA) [dblp]
  • Bernhard Rumpe (RWTH Aachen, DE) [dblp]
  • Susan Sanchez (Naval Postgrad. School - Monterey, US) [dblp]
  • Peter Sloot (University of Amsterdam, NL)
  • Claudia Szabo (University of Adelaide, AU) [dblp]
  • Wen Jun Tan (Nanyang TU - Singapore, SG)
  • Adelinde M. Uhrmacher (Universität Rostock, DE) [dblp]
  • Gabriel A. Wainer (Carleton University - Ottawa, CA) [dblp]
  • Pia Wilsdorf (Universität Rostock, DE) [dblp]
  • Verena Wolf (Universität des Saarlandes - Saarbrücken, DE) [dblp]
Remote:
  • Christopher Carothers (Rensselaer Polytechnic Institute - Troy, US) [dblp]
  • David M. Nicol (University of Illinois - Urbana Champaign, US) [dblp]
  • Nadja Schlungbaum (Universität Rostock, DE)

Klassifikation
  • Computational Engineering / Finance / and Science

Schlagworte
  • Modeling
  • Simulation