Developing Environment Tools for Collaborative Ontology Evolution

Abstract

In an era where data is considered the new oil, the lack of meaning and well-defined data structure will lead to interoperability and usability problems. Ontologies are a representation paradigm to capture and represent the knowledge of a universe of discourse and structure it in a machine-comprehensible format. However, developing ontologies can be a time-consuming, expensive process and requires a significant investment, which is challenging to make by a single person or organization. An effective approach to tackling this problem is building ontologies collaboratively where all interested stakeholders are involved. It includes identifying the main terms and concepts by finding a consensus among stakeholders while defining a shared terminology and formalizing it for the intended domain. The process of jointly building ontologies in distributed environments, which we refer to as collaborative ontology development, aims to accomplish shared objectives and extensive coordination of activities. Ontologies are instrumental in this process by providing formal specifications of shared semantics. In this "complex" and dynamic setting, a collaborative change process model requires more powerful engineering, argumentation, and negotiation methodologies. In fact, the main challenge for stakeholders is to work collaboratively on a shared objective constructively and efficiently while avoiding misunderstandings, uncertainty, and ambiguity. The involved stakeholders, which may be geographically distributed, should easily express and integrate their diverse views and ideas without risking losing the original intention. Researchers have presented methodologies and platforms to allow ontology construction in various scenarios. However, there is still little understanding of and support for the evolutionary aspects of ontologies. This is particularly crucial in distributed and collaborative settings such as the Semantic Web, where ontologies naturally co-evolve with their communities of use. Software Engineering offers many techniques and tools for teams' collaboration, teams' management, feedback management, versioning, merging, and evolving software artifacts. Many of these techniques can be reused in an ontology engineering setting. Scrum/Nexus/Spotify are Frameworks that enable iterative and incremental product development. This thesis leverages these frameworks and maps them to the collaborative, inter-organizational domain ontology building and evolution. Besides, we adopted software measurement criteria as a candidate evaluation framework for ontology quality assessment. Another challenge exists as to how humans can see, imagine and understand the knowledge captured in different domains. The knowledge experts and teams need to analyze the quality of ontologies generated in collaborative environments quickly. They must have tools that provide