Skip to main content

Bridging narrative scenario texts and formal policy modeling through conceptual policy modeling


Engaging stakeholders in policy making and supporting policy development with advanced information and communication technologies including policy simulation is currently high on the agenda of research. In order to involve stakeholders in providing their input to policy modeling via online means, simple techniques need to be employed such as scenario technique. Scenarios enable stakeholders to express their views in narrative text. At the other end of policy development, a frequently used approach to policy modeling is agent-based simulation. So far, effective support to transform narrative text input to formal simulation statements is not widely available. In this paper, we present a novel approach to support the transformation of narrative texts via conceptual modeling into formal simulation models. The approach also stores provenance information which is conveyed via annotations of texts to the conceptual model and further on to the simulation model. This way, traceability of information is provided, which contributes to better understanding and transparency, and therewith enables stakeholders and policy modelers to return to the sources that informed the conceptual and simulation model. In this paper, we present the consistent conceptual description (CCD) as conceptual modeling approach to bridge the gap between narrative texts and formal policy models. The CCD meta-model with the underlying vocabulary for describing policy contexts is detailed. A case study introduces the application of the approach in the Open Collaboration for Policy Modeling project.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15


  1. Open COllaboration for POlicy MOdeling,

  2. By policy, we refer to strategic areas of complex decision-making with various stakeholders having potentially diverging interests.

  3. Traceability is referred to as “the potential to relate data that is stored within artifacts [\(\ldots\)] along with the ability to examine this relationship” (Gotel et al. 2012, p. 4).

  4., last accessed 4/2/2013.

  5. See e.g.,,, last accessed 4/2/2013.

  6., last accessed 4/2/2013.

  7. An overview of DRAMS classes is provided in Lotzmann and Meyer (2011).

  8. QVT is a standard published in 2008 by the OMG (Object Management Group) (, last accessed 4/2/2013). Since 2011, version 1.1 is available (see, last accessed 4/2/2013).

  9. See

  10. See

  11. Names of companies are anonymized.

  12. (last accessed: 25th May, 2012).

  13. (last accessed 25th May, 2012).


  • Bicking M, Wimmer MA (2011) A Scenario-based approach towards open collaboration for policy modelling. In: Janssen M, Scholl HJ, Wimmer MA, Tan YH (eds) Elelectronic government: the 10th conference on electronic government (EGOV 2011), Springer, Berlin, no. 6846 in LNCS, pp 223–234

  • Budinsky F, Brodsky S, Merks E (2003) Eclipse modeling framework. Addison-Wesley, Boston

    Google Scholar 

  • Carroll J (1995) Scenario-based design: envisioning work and technology in system development. Wiley, London

    Google Scholar 

  • Cleland-Huang J, Gotel O, Zisman A (2012) Software and systems traceability. Springer, London

  • Doran J, Gilbert N (1994) Simulating societies: an introduction. In: Gilbert N, Doron J (eds) Simulating societies:the computer simulation of social phenomena, chap 1. UCL Press, London

    Google Scholar 

  • Fensel D, Hendler J, Lieberman H, Wahlster W (2003) Introduction. In: Fensel D, Hendler J, Lieberman H, Wahlster W (eds) Spinning the semantic web: bringing the World Wide Web to its full potential, chap 1. MIT Press, Cambridge, pp 1–25

    Google Scholar 

  • Gilbert N, Troitzsch KG (2005) Simulation for the social scientist, 2nd edn. Open University Press, New York

    Google Scholar 

  • Gómez-Sanz J, Pavón J (2003) Agent oriented software engineering with INGENIAS. In: Proceedings of the 3rd central and Eastern Europe conference on multiagent systems, Springer, LNCS, Citeseer, vol 2691, pp 394–403

  • Gotel O, Cleland-Huang J, Hayes JH, Zisman A, Egyed A, Grnbacher P, Dekhtyar A, Antoniol G, Maletic J, Mger P (2012) Traceability fundamentals. In: Cleland-Huang J, Gotel O (eds) Software and systems traceability. Springer, London

    Google Scholar 

  • Gruber T (2009) Ontology. In: Liu L, zsu MT (eds) Encyclopedia of database systems, Springer, London.

  • Hassan S, Fuentes-Fernández R, Galán J, López-Paredes A, Pavón J (2009) Reducing the modeling gap: on the use of metamodels in agent-based simulation. In: 6th conference of the european social simulation association (ESSA 2009), pp 1–13

  • Hesse W, Mayr HC (2008) Modellierung in der Softwaretechnik: eine Bestandsaufnahme. Informatik-Spektrum 31(5):377–393

    Article  Google Scholar 

  • Iba T, Matsuzawa Y, Aoyama N (2004) From conceptual models to simulation models: model driven development of agent-based simulations. In: 9th workshop on economics and heterogeneous interacting agents, Citeseer

  • Lotzmann U, Meyer R (2011) DRAMS—a declarative rule-based agent modelling system. In: Burczynski T, Kolodziej J, Byrski A, Carvalho M (eds) Proceedings of 25th European conference on modelling and simulation, European Council for Modelling and Simulation

  • Lotzmann U, Wimmer MA (2012) Provenance and traceability in agent-based policy simulation. In: Klumpp M (ed) ESM’2012 The European simulation and modelling conference: modelling and simulation 2012, Eurosis, pp 203–207

  • Ludewig J (2003) Models in software engineering: an introduction. Softw Syst Model 2:5–14

    Article  Google Scholar 

  • Mahr B (2009) Die Informatik und die Logik der Modelle. Informatik-Spektrum 32(3):228–249. doi:10.1007/s00287-009-0340-y

    Article  Google Scholar 

  • Müller JP (2010) A framework for integrated modeling using a knowledge-driven approach. In: Swayne DA, Yang W, Voinov AA, Rizzoli A, Filatova T (eds) Proceedings of international environmental modelling and software society (iEMSs) 2010,

  • Okuyama F, Bordini R, da Rocha Costa A (2005) ELMS: an environment description language for multi-agent simulation. Environments for Multi-Agent Systems, pp 91–108

  • Pavón J, Gómez-Sanz J, Fuentes R (2006) Model driven development of multi-agent systems. In: Rensink A, Warmer J (eds) Model driven architecture foundations and applications, Lecture Notes in Computer Science, vol 4066, Springer, Berlin, pp 284–298

  • Scherer S, Wimmer MA (2012) E-participation and enterprise architecture frameworks: an analysis. Inform Polity 17(2),

  • Schütte R (1998) Grundsätze orgnungsgemässer Referenzmodellierung, Neue betriebswirtschaftliche Forschung, vol 233. Gabler, Wiesbaden

  • Stachowiak H (1973) Allgemeine Modelltheorie. Springer, Berlin

    Book  Google Scholar 

  • Troitzsch KG (1990) Modellbildung und Simulation in den Sozialwissenschaften. Westdeutscher Verlag, Opladen

    Book  Google Scholar 

  • Wimmer MA (2011) Open government in policy development: from collaborative scenario texts to formal policy models. In: Natarajan R, Ojo A (eds) Distributed computing and internet technology ICDCIT 2011, Springer, Berlin, no. 6536 in LNCS, pp 76–91

  • Wimmer MA, Furdik K, Bicking M, Mach M, Sabol T, Butka P (2012a) Open collaboration in policy development: concept and architecture to integrate scenario development and formal policy modelling. In: Charalabidis Y, Koussouris S (eds) Empowering open and collaborative governance. Springer, Berlin, pp 199–219

    Chapter  Google Scholar 

  • Wimmer MA, Scherer S, Moss S, Bicking M (2012b) Method and tools to support Stakeholder engagement in policy development: The OCOPOMO Project. Int J Electron Govern Res 8(3):98–119,

  • Winter A (2000) Referenz-Meta-schema für visuelle Modellierungssprachen. Deutscher Universitäts-Verlag, Aaker

    Google Scholar 

Download references


OCOPOMO is co-funded by the European Commission within FP 7, contract No. 248128. The authors acknowledge the contributions of and express their gratitude to the OCOPOMO project partners for the numerous discussions on the CCD meta model and CCD software, especially Scott Moss, Klaus Troitzsch and Ulf Lotzmann. The authors express also their gratitude to Björn Lilge who analyzed and implemented the transformation process in his bachelor thesis under the supervision of the authors. The authors are grateful to reviewers for their helpful suggestions. The content of this paper represents the view of the authors, respectively. The European Commission cannot be made liable for any content.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Sabrina Scherer.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Scherer, S., Wimmer, M.A. & Markisic, S. Bridging narrative scenario texts and formal policy modeling through conceptual policy modeling. Artif Intell Law 21, 455–484 (2013).

Download citation

  • Published:

  • Issue Date:

  • DOI: