Advertisement
Published in:
2014 | OriginalPaper | Chapter
Semantic Monitoring and Compensation in Socio-technical Processes
Authors : Yingzhi Gou, Aditya Ghose, Chee-Fon Chang, Hoa Khanh Dam, Andrew Miller
Published in: Advances in Conceptual Modeling
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Socio-technical processes are becoming increasingly important, with the growing recognition of the computational limits of full automation, the growth in popularity of crowd sourcing, the complexity and openness of modern organizations etc. A key challenge in managing socio-technical processes is dealing with the flexible, and sometimes dynamic, nature of the execution of human-mediated tasks. It is well-recognized that human execution does not always conform to predetermined coordination models, and is often error-prone. This paper addresses the problem of semantically monitoring the execution of socio-technical processes to check for non-conformance, and the problem of recovering from (or compensating for) non-conformance. This paper proposes a semantic solution to the problem, by leveraging semantically annotated process models to detect non-conformance, and using the same semantic annotations to identify compensatory human-mediated tasks.