Rule driven workflow enactment


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Rule driven workflow enactment. Adriaan van Os, Tim Verwaart. ESUG 2005, Brussels

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Rule driven workflow enactment

  1. 1. Rule driven workflow enactment Adriaan van Os Tim Verwaart Brussels, August 18th, 2005 13th European Smalltalk User Group Joint Event
  2. 2. Subject • Last year we presented Artis: a system for model driven development and deployment • In Artis, workflow is driven by the information need • Data models and business rules can be used to specify the information need • In this presentation we explain how we realized workflow enactment by comparing database content with business rules
  3. 3. Workflow enactment Rule violation entered into workload for responsible employee Enact procedure
  4. 4. Information need What? When?
  5. 5. In our case: farming
  6. 6. Regional offices
  7. 7. Information need drives workflow Central Database What? When? Workload
  8. 8. Information need can be represented as a data structure model, for instance (attributes not shown): Holding Payment Asset owns has made payed for Demo: an artis data model (context)
  9. 9. Data model is not sufficient to define the information need • We do not need to know all attribute values in all cases • We want the data to satisfy integrity constraints • We need the information in time
  10. 10. Attach rules to each attribute Demo: RIA rule formulation and representation
  11. 11. Act in case of rule violations
  12. 12. Keeper determines workload Relevant? Complete and consistent? Current? Who is responsible? rules facts responsibility Data repository
  13. 13. Keeper algorithm • for each entity in some designated population as a starting point: – for each attribute: • determine responsible employee and add rule violation to the workload: –if the attribute is relevant and the value is not current –or if the attribute is relevant and the value is current but does not satisfy the integrity constraint
  14. 14. Two remarks 1. Attributes may be multi-valued (have a collection of entities as value). In that case, execute the keeper algorithm for all entities in the collection too. 2. Evaluation of actuality rules requires a temporal data representation. We represent the value of facts not as a simple value but as a pair of value and validity time. Demo: data representation (viewer)
  15. 15. Who is responsible? • We record responsibility for entities in the repository as an entity-employee-association • No need to designate responsibility for each entity. The keeper traces back to the entity in the population it used as starting point. Entity Employee responsibility Collection
  16. 16. What shoud she do? • The workflow is described in procedures • We record applicability of procedures as an association of procedure and rule Procedure Rule applicability • We use this knowledge to “enact” workflow: enter first task of procedure into responsible employees to-do list Demo: workload (Mole) and start
  17. 17. Conclusion • Workflow can be enacted by comparing database content with business rules • This can only be generically achieved by applying a temporal data model • We need knowledge about: –responsibility (of persons) –applicability (of procedures)
  18. 18. Questions? rules facts responsibility Data repository
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