Evaluation of Heuristics for Product Data Models

Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 397)


Product Data Model (PDM) is an example of a data-centric approach to modelling information-intensive business processes, which offers flexibility and facilitates process optimization. It is declarative, and as such, there may be multiple workflow designs that can produce the end product. To this end, several heuristics have been proposed. The contributions of this work are twofold: (i) we propose new heuristics that capitalize on established techniques for optimizing data-intensive workflows; and (ii) we extensively evaluate the existing solutions. Our results shed light on the merits of each heuristic and show that our proposal can yield significant benefits in certain cases. We provide our implementation as an open-source product.


Data-centric processes Process optimization PDM 



The research work was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “First Call for H.F.R.I. Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant” (Project Number:1052, Project Name: DataflowOpt). We would like also to thank Dr. Georgia Kougka for her comments and help.


  1. 1.
    van der Aalst, W.M.P.: Re-engineering knock-out processes. Decis. Support Syst. 30(4), 451–468 (2001). CrossRefGoogle Scholar
  2. 2.
    Agrawal, K., Benoit, A., Dufossé, F., Robert, Y.: Mapping filtering streaming applications. Algorithmica 62(1–2), 258–308 (2012). Scholar
  3. 3.
    Buijs, J.C.A.M., van Dongen, B.F., van der Aalst, W.M.P.: Discovering and navigating a collection of process models using multiple quality dimensions. In: Lohmann, N., Song, M., Wohed, P. (eds.) BPM 2013. LNBIP, vol. 171, pp. 3–14. Springer, Cham (2014). Scholar
  4. 4.
    Buijs, J.C.A.M., van Dongen, B.F., van der Aalst, W.M.P.: Mining configurable process models from collections of event logs. In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 33–48. Springer, Heidelberg (2013). Scholar
  5. 5.
    Chawla, N., King, I., Sperduti, A.: User-guided discovery of declarative process models (2011)Google Scholar
  6. 6.
    Deshpande, A., Hellerstein, L.: Parallel pipelined filter ordering with precedence constraints. ACM Trans. Algorithms 8(4), 1–38 (2012)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Henriques, R., Rito Silva, A.: Object-centered process modeling: principles to model data-intensive systems. In: zur Muehlen, M., Su, J. (eds.) BPM 2010. LNBIP, vol. 66, pp. 683–694. Springer, Heidelberg (2011). Scholar
  8. 8.
    Kougka, G., Gounaris, A., Simitsis, A.: The many faces of data-centric workflow optimization: a survey. Int. J. Data Sci. Anal. 6(2), 81–107 (2018). Scholar
  9. 9.
    Kougka, G., Varvoutas, K., Gounaris, A., Tsakalidis, G., Vergidis, K.: On knowledge transfer from cost-based optimization of data-centric workflows to business process redesign. In: Hameurlain, A., Tjoa, A.M. (eds.) Transactions on Large-Scale Data- and Knowledge-Centered Systems XLIII. LNCS, vol. 12130, pp. 62–85. Springer, Heidelberg (2020). Scholar
  10. 10.
    Künzle, V., Reichert, M.: Philharmonicflows: towards a framework for object-aware process management. J. Softw. Maintain. 23(4), 205–244 (2011)CrossRefGoogle Scholar
  11. 11.
    Orlicky, J.A., Plossl, G.W., Wight, O.W.: Structuring the bill of material for MRP. In: Lewis, M., Slack, N. (eds.) Operations Management: Critical Perspectives on Business and Management, vol. 58. Taylor & Francis, New York (2003)Google Scholar
  12. 12.
    Pesic, M., Schonenberg, H., van der Aalst, W.M.P.: Declare: full support for loosely-structured processes. In: 11th IEEE International Enterprise Distributed Object Computing Conference (EDOC 2007), pp. 287–300 (2007)Google Scholar
  13. 13.
    Reijers, H.A., Limam, S., van der Aalst, W.M.P.: Product-based workflow design. J. Manag. Inf. Syst. 20(1), 229–262 (2003)CrossRefGoogle Scholar
  14. 14.
    Reijers, H.A., et al.: Evaluating data-centric process approaches: does the human factor factor in? Softw. Syst. Model. 16(3), 649–662 (2016). Scholar
  15. 15.
    Schunselaar, D.: Configurable process trees : elicitation, analysis, and enactment. Ph.D. thesis, Department of Mathematics and Computer Science, October 2016. ProefschriftGoogle Scholar
  16. 16.
    Simitsis, A., Wilkinson, K., Dayal, U., Castellanos, M.: Optimizing ETL workflows for fault-tolerance. In: 2010 IEEE 26th International Conference on Data Engineering (ICDE 2010), pp. 385–396 (2010)Google Scholar
  17. 17.
    Simitsis, A., Wilkinson, K., Castellanos, M., Dayal, U.: Optimizing analytic data flows for multiple execution engines. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 829–840 (2012)Google Scholar
  18. 18.
    Vanderfeesten, I.T.P., Reijers, H.A., van der Aalst, W.M.P.: Product-based workflow support. Inf. Syst. 36(2), 517–535 (2011)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of InformaticsAristotle University of ThessalonikiThessalonikiGreece

Personalised recommendations