Conceptual Models in Simulation Studies: Making it Explicit
Abstract
Conceptual models play an important role in conducting simulation studies. A formal or at least explicit specification of conceptual models is key for effectively exploiting them during simulation studies and thereafter, for interpreting and reusing the simulation results. However, the perception of conceptual models varies strongly and with it possible means for specification. A broad definition of the conceptual model, i.e., as a loose collection of early-stage products of the simulation study, holds the potential to unify existing definitions, but also poses specific challenges for specification. To approach these challenges, without claiming to be exhaustive, we identify a set of products, which includes research question, data, and requirements, and define relations and properties of these products. Based on a cell biological case study and a prototypical implementation, we show how the formal structuring of the conceptual model assists in building a simulation model.
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Each entity and activity in the final set has already been mentioned for provenance, modeling or documentation purposes, or experiment design of simulation studies, but they have not all been used together.
“Each entity and activity has already been mentioned for provenance, modeling or documentation purposes, or experiment design of simulation studies [1, 3–5, 8, 20, 21, 60–63], but they have not all been used together.”
From Relating simulation studies by provenance—Developing a family of Wnt signaling models (2021) · cites this paper as [3]
Cites
Exact stochastic simulation of coupled chemical reactions
Gillespie, D. T. (1977) · The Journal of Physical Chemistry · doi:10.1021/j100540a008 · Cited by 9,969 · see citing works
Jupyter Notebooks – a publishing format for reproducible computational workflows
Kluyver, T. A., Ragan-Kelley, B., Fernando, P., Granger, B., Bussonnier, M., Frederic, J., Kelley, K., Hamrick, J. B., Grout, J., Corlay, S., et al. (2016) · IOS Press eBooks · doi:10.3233/978-1-61499-649-1-87 · Cited by 3,191 · see citing works
Verification and validation of simulation models
Sargent, R. G. (2012) · Journal of Simulation · doi:10.1057/jos.2012.20 · Cited by 1,747 · see citing works
Taverna: a tool for the composition and enactment of bioinformatics workflows
Oinn, T., Addis, M., Ferris, J., Marvin, D. J., Senger, M., Greenwood, R. M., Carver, T. J., Glover, K., Pocock, M., Wipat, A., et al. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth361 · Cited by 1,599 · see citing works
Monitoring Temporal Properties of Continuous Signals
Maler, O., & Ničković, D. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-30206-3_12 · Cited by 1,270 · see citing works
Grimm, V., Railsback, S. F., Vincenot, C. E., Berger, U., Gallagher, C. A., Deangelis, D. L., Edmonds, B., Ge, J., Giske, J., Groeneveld, J., et al. (2020) · Journal of Artificial Societies and Social Simulation · doi:10.18564/jasss.4259 · Cited by 905 · see citing works
The Roles of APC and Axin Derived from Experimental and Theoretical Analysis of the Wnt Pathway
Lee, E., Salic, A., Krüger, R., Heinrich, R., & Kirschner, M. W. (2003) · PLoS Biology · doi:10.1371/journal.pbio.0000010 · Cited by 708 · see citing works
NetLogo: A simple environment for modeling complexity
Tisue, S., & Wilensky, U. J. (2014) · Cited by 526 · see citing works
Conceptual modelling for simulation Part I: definition and requirements
Robinson, S. (2008) · Journal of the Operational Research Society · doi:10.1057/palgrave.jors.2602368 · Cited by 482 · see citing works
(1991) · Mathematics and Computers in Simulation · doi:10.1016/0378-4754(91)90131-l · Cited by 406 · see citing works
Cellier, F. E. (1991) · Springer eBooks · doi:10.1007/978-1-4757-3922-0 · Cited by 405 · see citing works
Krötzsch, M., Vrandečić, D., & Völkel, M. (2006) · Lecture notes in computer science · doi:10.1007/11926078_68 · Cited by 378 · see citing works
A Survey of Statistical Model Checking
Agha, G., & Palmskog, K. (2018) · ACM Transactions on Modeling and Computer Simulation · doi:10.1145/3158668 · Cited by 292 · see citing works
Strengthening the reporting of empirical simulation studies: Introducing the STRESS guidelines
Monks, T., Currie, C. S. M., Onggo, B. S., Robinson, S., Kunc, M., & Taylor, S. J. E. (2019) · Journal of Simulation · doi:10.1080/17477778.2018.1442155 · Cited by 248 · see citing works
Conceptual modelling for simulation Part II: a framework for conceptual modelling
Robinson, S. (2007) · Journal of the Operational Research Society · doi:10.1057/palgrave.jors.2602369 · Cited by 198 · see citing works
A life cycle for modeling and simulation
Balci, O. (2012) · SIMULATION · doi:10.1177/0037549712438469 · Cited by 159 · see citing works
Rule-based multi-level modeling of cell biological systems
Maus, C., Rybacki, S., & Uhrmacher, A. M. (2011) · BMC Systems Biology · doi:10.1186/1752-0509-5-166 · Cited by 150 · see citing works
Self-citationConceptual modeling: Definition, purpose and benefits
Robinson, S., Arbez, G., Birta, L. G., Tolk, A., & Wagner, G. (2015) · Winter Simulation Conference · doi:10.1109/wsc.2015.7408386 · Cited by 103 · see citing works
Ideas About Simulation Conceptual Model Development
Pace, D. K. (2000) · Johns Hopkins APL technical digest · Cited by 99 · see citing works
The Conical Methodology and the evolution of simulation model development
Nance, R. E. (1994) · Annals of Operations Research · doi:10.1007/bf02136825 · Cited by 99 · see citing works
Sakane, H., Yamamoto, H., & Kikuchi, A. (2010) · Journal of Cell Science · doi:10.1242/jcs.058008 · Cited by 98 · see citing works
Research Challenges in Modeling and Simulation for Engineering Complex Systems
Fujimoto, R., Bock, C., Chen, W., Page, E., & Panchal, J. (2017) · Simulation Foundations, Methods and Applications · doi:10.1007/978-3-319-58544-4 · Cited by 88 · see citing works
Conceptual modelling of web information systems
Schewe, K., & Thalheim, B. (2004) · Data & Knowledge Engineering · doi:10.1016/j.datak.2004.08.005 · Cited by 86 · see citing works
Work Smarter, Not Harder: A Tutorial on Designing and Conducting Simulation Experiments
Sanchez, S. M., Sánchez, P. J., & Wan, H. (2020) · Winter Simulation Conference · doi:10.1109/wsc48552.2020.9384057 · Cited by 82 · see citing works
Handbook of Conceptual Modeling: Theory, Practice, and Research Challenges
Embley, D. W., & Thalheim, B. (2011) · doi:10.1007/978-3-642-15865-0 · Cited by 75 · see citing works
Ewald, R., & Uhrmacher, A. (2014) · ACM Transactions on Modeling and Computer Simulation · doi:10.1145/2567895 · Cited by 75 · see citing works
Self-citationHaack, F., Lemcke, H., Ewald, R., Rharass, T., & Uhrmacher, A. M. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004106 · Cited by 66 · see citing works
Self-citationTowards a Theory of Conceptual Modelling
Thalheim, B. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-04947-7_7 · Cited by 64 · see citing works
DEVS framework for modelling, simulation, analysis, and design of hybrid systems
Zeigler, B. P., Song, H.-S., Kim, T. G., & Praehofer, H. (1995) · Lecture notes in computer science · doi:10.1007/3-540-60472-3_27 · Cited by 61 · see citing works
Achieving reusability and composability with a simulation conceptual model
Balcı, O., Arthur, J. D., & Ormsby, W. F. (2011) · Journal of Simulation · doi:10.1057/jos.2011.7 · Cited by 58 · see citing works
Simulation modeling methodology: principles and etiology of decision support
Page, E. H., & Nance, R. E. (1995) · VTechWorks (Virginia Tech) · Cited by 52 · see citing works
Conceptual modeling: Definition, purpose and benefits
Robinson, S., Arbez, G., Birta, L. G., Tolk, A., & Wagner, G. (2016) · Newcastle University ePrints (Newcastle Univesity) · doi:10.25405/ncl.34455192 · Cited by 45 · see citing works
Spatial modeling in cell biology at multiple levels
Bittig, A. T., & Uhrmacher, A. M. (2010) · Winter Simulation Conference · doi:10.1109/wsc.2010.5679125 · Cited by 33 · see citing works
Self-citationON REPRODUCIBILITY AND TRACEABILITY OF SIMULATIONS
Laroque, C., Himmelspach, J., Pasupathy, R., Rose, O., Uhrmacher, A. M., Dalle, O., & Antipolis, S. (2014) · Cited by 32 · see citing works
Self-citationProvenance in modeling and simulation studies — Bridging gaps
Ruscheinski, A., & Uhrmacher, A. (2017) · 2017 Winter Simulation Conference (WSC) · doi:10.1109/wsc.2017.8247839 · Cited by 31 · see citing works
Self-citationFishwick, P. A. (1995) · Winter Simulation Conference · doi:10.1145/224401.224464 · Cited by 29 · see citing works
Multiscale computing for science and engineering in the era of exascale performance
Hoekstra, A. G., Bastien Chopard, B., Coster, D., Zwart, S. P., & Coveney, P. V. (2019) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2018.0144 · Cited by 25 · see citing works
Elucidating the Sources of β-Catenin Dynamics in Human Neural Progenitor Cells
Mazemondet, O., John, M., Leye, S., Rolfs, A., & Uhrmacher, A. M. (2012) · PLoS ONE · doi:10.1371/journal.pone.0042792 · Cited by 25 · see citing works
Self-citationArtifact-Based Workflows for Supporting Simulation Studies
Ruscheinski, A., Warnke, T., & Uhrmacher, A. M. (2019) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2019.2899840 · Cited by 23 · see citing works
Self-citationWORK SMARTER, NOT HARDER: A TUTORIAL ON DESIGNING AND CONDUCTING SIMULATION EXPERIMENTS
Sanchez, S. M., Sánchez, P. J., & Wan, H. (2018) · Winter Simulation Conference · doi:10.1109/wsc.2018.8632311 · Cited by 21 · see citing works
Model transformation from BPMN to DEVS in the MDD4MS framework
Çetinkaya, D., Verbraeck, A., & Seck, M. (2012) · doi:10.5555/2346616.2346644 · Cited by 19 · see citing works
Peng, D., Warnke, T., Haack, F., & Uhrmacher, A. M. (2017) · SIMULATION · doi:10.1177/0037549717704314 · Cited by 14 · see citing works
Self-citationGENERATING SIMULATION EXPERIMENTS BASED ON MODEL DOCUMENTATIONS AND TEMPLATES
Ruscheinski, A., Budde, K., Warnke, T., Wilsdorf, P., Hiller, B. C., Dombrowsky, M., & Uhrmacher, A. M. (2018) · Winter Simulation Conference · doi:10.1109/wsc.2018.8632515 · Cited by 11 · see citing works
Self-citationConceptual simulation modeling with Onto-UML advanced tutorial
Guizzardi, G., & Wagner, G. (2012) · Winter Simulation Conference · doi:10.1109/wsc.2012.6465133 · Cited by 11 · see citing works
Hypothesis-Driven Simulation Studies
Lorig, F. (2019) · Springer eBooks · doi:10.1007/978-3-658-27588-4 · Cited by 10 · see citing works
Fishwick, P. A. (2005) · Winter Simulation Conference · doi:10.1109/wsc.1995.478725 · Cited by 5 · see citing works
Lorig, F. (2019) · CERN Document Server (European Organization for Nuclear Research) · Cited by 4 · see citing works
Epistemological categories of systems: An overview and mathematical formulation
Klir, G. J., & Rozehnal, I. (1990) · Lecture notes in computer science · doi:10.1007/3-540-52215-8_2 · Cited by 2 · see citing works
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- Authors
- Wilsdorf, P., Haack, F., & Uhrmacher, A. M.
- Affiliations
- University of Rostock (DE)
- Venue
- 2020 Winter Simulation Conference (WSC)
- Publisher
- IEEE
- Published
- 2020-12-14
- Pages
- 2353-2364
- ISSN
- 0891-7736 (ISSN-L)
- OpenAlex
- W3150912884
- Cited by
- 15
- References
- 52
- Citations by year
- 2025: 3 · 2024: 3 · 2023: 1 · 2022: 4 · 2021: 3 · 2020: 1
- FWCI
- 3.05
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- Winter Simulation Conference (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Simulation Techniques and Applications
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Modeling and Simulation Systems
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Keywords
- conceptual model, simulation study, research questions, simulated data, requirements, model reuse
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