Enhancing the Accessibility of Text Data in Decision Making for Capability-based Planning Using Ontology: A Perspective of Semantic Compliance

Abstract

Project introduction texts provide decision-makers with essential information for project portfolio planning. These free texts offer valuable information about how developing capabilities align with their strategic goals. Capability-based Planning (CBP) process is concerned with optimizing the project portfolio to realize the planning, engineering, and delivery of these capabilities. However, up to now, the research on enhancing accessibility to free text data in the CBP decision-making process through semantic modeling is limited, leading the CBP’s decision-makers to ignore the potential advantages of existing semantic modeling methods when dealing with many free texts. This paper aims to address this gap by introducing knowl­edge modeling and mining of project introduction text corpus, leveraging semantic technology to support CBP. First, we design an ontology of capability to describe the core concepts relevant to the CBP process. Subsequently, a semantic framework based on the RDF knowl­edge graph is proposed, enabling humans and machines to comprehend project description texts. To capture the semantic data essential for CBP, a motif structure is employed to model semantic expressions, ensuring their consistency with CBP concepts through compliance checks. Finally, the effectiveness of the proposed semantic framework is evaluated by querying the project’s knowl­edge graph after semantic normalization, providing an assessment of its potential in CBP applications.