[Back]

F. Ekaputra:
"Knowledge Change Management and Analysis in Engineering";
in: "Semantic Web for Intelligent Engineering Applications", Springer International Publishing Switzerland, Switzerland, 2016, ISBN: 978-3-319-41488-1, 159 - 178.

Knowledge is changing rapidly within the engineering process of
Cyber-Physical Production Systems (CPPS) characterized by the collaborative
work of engineers from diverse engineering disciplines. Such rapid changes lead
to the need for management and analysis of knowledge changes in order to preserve
knowledge consistency. Knowledge change management and analysis
(KCMA) in Multi-Disciplinary Engineering (MDEng) environments is a challenging
task since it involves heterogeneous, versioned, and linked data in a missioncritical
fashion, where failure to provide correct data could be costly. Although,
there are several available solutions for addressing general issues of KCMA, from
fields as diverse as Model Based Engineering (model co-evolution), Databases
(database schema evolution), and Semantic Web Technology (ontology versioning),
solving KCMA in engineering remains a challenging task. In this chapter, we
investigate issues related to KCMA in MDEng environments. We provide a definition
of this task and some of its challenges and we overview technologies that
can be potentially used for solving KCMA tasks from the three research fields
mentioned above. We then define a technology agnostic solution approach inspired
by the Ontology-Based Information Integration approach from Semantic
Web research as a first step towards a complete KCMA solution and provide an
indication of how this solution concept could be implemented using state of the art
Semantic Web technologies.

knowledge change management and analysis, ontology evolution, ontology versioning, ontology-based information integration, change detection, change validation, change propagation, multi-disciplinary engineering

http://dx.doi.org/10.1007/978-3-319-41490-4