Supporting Task Constraints and Dependencies in Knowledge-intensive Processes

Lang, André (2018) Supporting Task Constraints and Dependencies in Knowledge-intensive Processes. Masters thesis, Ulm University.

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Knowledge-intensive processes are widely found in modern societies and important to many fields of work. Driven by knowledge gained only during their execution, this type of process brings along challenges like a gradually emerging structure, uncertainty and frequent changes. Through contribution and communication the knowledge workers involved in the process shape and improve it while advancing towards a common goal. One very important part of the knowledge are the dependencies that naturally exist between the tasks on which these workers perform. With the latter often being spatially divided, expressing the dependencies existing for their jobs is a determining factor for success. Relying on insufficient software systems or, even worse, on paperbased solutions for coordination proves to be error-prone and lacks reliance in practical scenarios. Adequate aid in form of information systems, specifically designed for knowledge-intensive processes and their accompanying challenges, and operated on by the knowledge workers themselves, is needed. The work on such systems is a still ongoing endeavor and in need of concepts and solutions.
This work presents a concept for the support of constraints to express task dependencies in knowledge-intensive processes. With the focus on the unique challenges coming with the latter, the concept puts great emphasis on providing guidance instead of strict ruling, adaptability to frequent changes and usability in practical scenarios. A rule-based, declarative approach is laid out for applying the concept, designed to be ready for extension, to various systems alongside other, already existing functionality. Based on it, a catalog of constraints is given, with clear semantic meanings and effects, tailored towards the use in knowledge-intensive processes. A proof-of-concept prototype for it was implemented for the process-aware Support for Collaborative Knowledge Workers (proCollab) system, an example of an adequate and sophisticated solution.

Item Type: Thesis (Masters)
Subjects: DBIS Research > Master and Phd-Thesis
Divisions: Faculty of Engineering, Electronics and Computer Science > Institute of Databases and Informations Systems > DBIS Research and Teaching > DBIS Research > Master and Phd-Thesis
Depositing User: Nicolas Mundbrod
Date Deposited: 20 Aug 2018 11:41
Last Modified: 20 Aug 2018 11:41

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