Call for Papers (PDF)

Workshop Background and Goals

Nowadays, Workflow Management Systems (WfMS) are widely used in all human activities, ranging from classical ones (management of supply chain, postal tracking delivery etc.) to very dynamic ones (health-care, emergency management, etc.). Every aspect of a business process involves a certain amount of knowledge, that can depend both on the complexity of the domain of interest and on the modeling language used to represent the process itself. Some processes behave in a way that is well understood, predictable and repeatable: the tasks are discrete and the control flow is straightforward. Recent discussions illustrate the increasing demand in the solutions for knowledge-intensive processes. A knowledge-intensive process is one in which the people\agents performing such process are involved in a fair degree of uncertainty. This is due to the high number of tasks to be represented and to their unpredictable nature, or to a difficulty to model the whole knowledge of the domain of interest at design time. In realistic environments, for example, actors lack important knowledge at execution time or this knowledge can become obsolete during the process progressing. Even if each actor (at some point) has a perfect knowledge of the world, it could not be certain of its beliefs at later time points, since tasks by other actors may change the world without those changes being perceived. Typically, a knowledge-intensive process can not be modeled sufficiently by classical, static process models and workflows. There is still a lack of maturity in some respect, i.e., a lack of a semantic associated to the models or an easy way to reason about such semantic.

The main focus of this workshop is to discuss about how the use of techniques that came from different fields, such as Artificial Intelligence (AI), Knowledge Representation (KR), Business Process Management (BPM), Service Oriented Computing (SOC), etc., can be used jointly for improving the modeling and the enactment phase of a knowledge-intensive process. The purpose is to devise interesting approaches that can still achieve the goals of understanding, visibility and control of these emergent processes.

Topics of the Workshop

The KiBP workshop is focused on the design, evaluation and comparison of process improvement techniques, tools and methods, in which aspects of knowledge representation, reasoning, creation, organization, retrieval, transfer, refinement, reuse, revision, and feedback play a key role. We invite contributions on the following aspects of knowledge representation and modeling for processes (not exclusive):

  • Modeling languages, notations and methods for knowledge representation and management in business processes
  • Variability and adaptability of business process models for knowledge-intensive tasks through automatic techniques
  • Resource management for knowledge-intensive business process modeling and support
  • User-oriented aspects of knowledge-intensive business processes
  • Verification and validation of knowledge-intensive business processes
  • Dynamic configuration; modeling by knowledge reuse
  • Knowledge-intensive business process support architectures and platforms
  • Machine learning for business process mining and monitoring
  • Artifact-centric business processes
  • Case studies, empirical evaluations and experimentations

Format of the Workshop

The workshop will consist of presentations of the accepted papers and an additional keynote speaker. Papers should be submitted in advance and will be reviewed by at least three members of the program committee. All accepted papers will be published, potentially in revised form, as CEUR Workshop Proceedings. Best papers will be invited to submit an extended version for a forthcoming (i.e., Spring 2013) issue of JoDS - Journal on Data Semantics. At least one author for each accepted paper should register for the workshop and plan to present the paper.