Cognitive support for semi-automatic ontology mapping.

摘要

Structured vocabularies are often used to annotate and classify data. These vocabularies represent a shared understanding about the terms used within a specific domain. People often rely on overlapping, but independently developed terminologies. This representational divergence becomes problematic when researchers wish to share, find, and compare their data with others. One approach to resolving this is to create a mapping across the vocabularies. Generating these mappings is a difficult, semi-automatic process, requiring human intervention. There has been little research investigating how to aid users with performing this task, despite the important role the user typically plays. Much of the research focus has been to explore techniques to automatically determine correspondences between terms. In this thesis, we explore the user-side of mapping, specifically investigating how to support the user's decision making process and exploration of mappings. We combine data gathered from theories of human inference and decision making, an observational case study, online survey, and interview study to propose a cognitive support framework for ontology mapping. The framework describes the user information needs and the process users follow during mapping. We also propose a number of design principles, which help guide the development of an ontology mapping tool called COGZ. We evaluate the tool and thus implicitly the framework through a case study and controlled user study. The work presented in this thesis also helps to draw attention to the importance of the user role during the mapping process. We must incorporate a "human in the loop", where the human is essential to the process of developing a mapping. Helping to establish and harness this symbiotic relationship between human processes and the tool's automated process will allow people to work more efficiently and effectively, and afford them the time to concentrate on difficult tasks that are not easily automated.