Developing simulation models - from conceptual to executable model and back - an artifact-based workflow approach

Developing a model for simulation is an art and a science. The question is how this process can be suitably supported. Integrating workflows into simulation systems promises user guidance, documentation and reproducibility of this process. However, the highly interactive, partly concurrent, partly optional nature of the modeling process challenges traditional activity-based workflow approaches. This is intensified by its multiple inter-dependencies and the need for an easy extension. We will illuminate this based on a modeling example from cell biology. To support the required flexibility, we propose an artifact-based workflow approach instead. Conceptual model, formal model and different data and information sources are specified declaratively as artifacts. The life cycle of an artifact is defined by stages, guards, milestones, and sentries, following the Guard-Stages-Milestone (GSM) approach. It is shown that the declarative specification provides a better fit for the process of developing a model.

[1]  Robert G. Sargent,et al.  Verifying and validating simulation models , 1996, Proceedings Winter Simulation Conference.

[2]  Richard E. Nance,et al.  The Simulation Project Life-Cycle: Models and Realities , 2006, Proceedings of the 2006 Winter Simulation Conference.

[3]  Frank Leymann,et al.  Conventional Workflow Technology for Scientific Simulation , 2011, Guide to e-Science.

[4]  Wolfgang Kreutzer,et al.  System simulation programming styles and languages , 1986 .

[5]  Osman Balci,et al.  Verification, validation, and accreditation , 1998, 1998 Winter Simulation Conference. Proceedings (Cat. No.98CH36274).

[6]  Robert E. Shannon,et al.  Introduction to the art and science of simulation , 1998, 1998 Winter Simulation Conference. Proceedings (Cat. No.98CH36274).

[7]  Adelinde M. Uhrmacher,et al.  SESSL , 2014, ACM Trans. Model. Comput. Simul..

[8]  John Ryan,et al.  Process Modelling Support for the Conceptual Modelling Phase of a Simulation Project , 2006, Proceedings of the 2006 Winter Simulation Conference.

[9]  G. Nigel Gilbert,et al.  Simulation for the social scientist , 1999 .

[10]  Carole A. Goble,et al.  myExperiment: Defining the Social Virtual Research Environment , 2008, 2008 IEEE Fourth International Conference on eScience.

[11]  Stewart Robinson,et al.  Choosing the right model: Conceptual modeling for simulation , 2011, Proceedings of the 2011 Winter Simulation Conference (WSC).

[12]  L. Felipe Perrone,et al.  SAFE: Simulation automation framework for experiments , 2012, Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC).

[13]  Krzysztof Pawlikowski,et al.  On credibility of simulation studies of telecommunication networks , 2002, IEEE Commun. Mag..

[14]  Dimka Karastoyanova,et al.  Bridging the Gap between Business and Scientific Workflows: Humans in the Loop of Scientific Workflows , 2010, 2010 IEEE Sixth International Conference on e-Science.

[15]  Stefan Leye,et al.  Template and Frame Based Experiment Workflows in Modeling and Simulation Software with WORMS , 2012, 2012 IEEE Eighth World Congress on Services.

[16]  Richard Hull,et al.  Business artifacts with guard-stage-milestone lifecycles: managing artifact interactions with conditions and events , 2011, DEBS '11.

[17]  Manfred Reichert,et al.  The ADEPT project: a decade of research and development for robust and flexible process support , 2009, Computer Science - Research and Development.

[18]  Anil Nigam,et al.  Business artifacts: An approach to operational specification , 2003, IBM Syst. J..

[19]  Wil vanderAalst,et al.  Workflow Management: Models, Methods, and Systems , 2004 .

[20]  J. D. Johannes,et al.  Systems Simulation: The Art and Science , 1975, IEEE Transactions on Systems, Man, and Cybernetics.

[21]  Adelinde M. Uhrmacher,et al.  Using workflows in M&S software , 2010, Proceedings of the 2010 Winter Simulation Conference.

[22]  Jerry Banks,et al.  A framework for specifying a discrete-event simulation conceptual model , 2013, J. Simulation.

[23]  Adelinde M. Uhrmacher,et al.  WORMS- A framework to support workflows in M&S , 2011, Proceedings of the 2011 Winter Simulation Conference (WSC).

[24]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[25]  Santhosh Kumaran,et al.  Artifact-centered operational modeling: Lessons from customer engagements , 2007, IBM Syst. J..

[26]  Carole A. Goble,et al.  Taverna: a tool for building and running workflows of services , 2006, Nucleic Acids Res..

[27]  Wil M. P. van der Aalst,et al.  DECLARE: Full Support for Loosely-Structured Processes , 2007, 11th IEEE International Enterprise Distributed Object Computing Conference (EDOC 2007).

[28]  Moshe Y. Vardi,et al.  Verification , 1917, Handbook of Automata Theory.

[29]  P. Cochat,et al.  Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.

[30]  Andreas D. Lattner Towards Automation of Simulation Studies , 2013, KI - Künstliche Intelligenz.

[31]  Sigrid Wenzel,et al.  Verification and validation activities within a new procedure model for V&V in production and logistics simulation , 2009, Proceedings of the 2009 Winter Simulation Conference (WSC).

[32]  Richard Hull,et al.  Business Artifacts: A Data-centric Approach to Modeling Business Operations and Processes , 2009, IEEE Data Eng. Bull..

[33]  Mathias John,et al.  Integrating diverse reaction types into stochastic models — A signaling pathway case study in the Imperative π-Calculus , 2009, Proceedings of the 2009 Winter Simulation Conference (WSC).

[34]  Adelinde M. Uhrmacher,et al.  Selecting Simulation Algorithm Portfolios by Genetic Algorithms , 2010, 2010 IEEE Workshop on Principles of Advanced and Distributed Simulation.

[35]  Dimka Karastoyanova,et al.  BPEL4Pegasus: Combining Business and Scientific Workflows , 2010, ICSOC.

[36]  Oliver Kopp,et al.  Quality of data driven simulation workflows , 2012, 2012 IEEE 8th International Conference on E-Science.

[37]  Matthias Stein,et al.  SYCAMORE - a systems biology computational analysis and modeling research environment , 2008, Bioinform..

[38]  Jacky L. Snoep,et al.  BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems , 2005, Nucleic Acids Res..

[39]  Richard E. Nance The Conical Methodology: A Framework for Simulation Model Development , 1987 .

[40]  Gerald T. Mackulak,et al.  The Science of Simulation Modeling , 1994 .