Organizational project knowledge is not being captured, consolidated, and organized, making it difficult to learn from past projects, expose the knowledge of the most experienced people, or share experience across geographic project locations. The lack of an ontology for representing this comprehensive project store inhibits its creation and the development of tools to operate on it.
Process-orientation links organizational resources or artifacts with process phases and workflow. A process-orientation in knowledge management can be used to add contextual metadata to knowledge artifacts. Context can be used to improve information retrieval precision.
Therefore, the study proposed a process-oriented ontology to improve the transfer of software engineering project knowledge.
Four questions guided the research:
What knowledge about projects should be captured? Are all project artifacts necessary and are they all equally valuable?
How can process-orientation be applied to a software engineering project knowledge ontology?
Are current knowledge representation languages appropriate for the task?
Can software development project knowledge, as represented by this ontology, be captured and retrieved effectively in a KMS?
Literature research and an empirical laboratory study answered all of the questions:
Four areas of project knowledge are particularly valuable in terms of their impact on project success; requirements, revisions, risks, and resolutions. These areas also cover a meaningful breadth of software engineering project knowledge.
A process abstraction was created that breaks a project down into eleven phases. These phases were the basis for a class definition that was added as a peer class to the knowledge artifacts.
Using Protégé, the Process-Oriented Ontology for Software Engineering (POSE) was successfully implemented in OWL-DL.
Project knowledge from a software organization was used to construct two knowledgebases: one using Google Desktop and the other using Protégé and POSE. Results demonstrated that software engineering project knowledge, as represented by POSE, can be effectively captured and retrieved.
POSE-enhanced search was superior to keyword search. Google was comparable in broad text search. But the benefits of metadata and semantics proved to have significant advantages for ontologies. Process-orientation was also validated as a contributor to improved classification and retrieval.
| Identifer | oai:union.ndltd.org:nova.edu/oai:nsuworks.nova.edu:gscis_etd-1301 |
| Date | 01 January 2009 |
| Creators | Sherman, Steven Jay |
| Publisher | NSUWorks |
| Source Sets | Nova Southeastern University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | CEC Theses and Dissertations |
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