Quality Assurance in Collaboratively Created Web Vocabularies

Abstract

In recent years, controlled vocabularies have become available on the Web using SKOS, i.e. they are linked to each other in order to be used in an interoperable way. Well-crafted controlled vocabularies are beneficial for, e.g., search and retrieval systems that provide functionalities like search term completion, query expansion or the ability for inter-domain queries. Some of these vocabularies are created collaboratively by experts, holding expertise in different domains. In order to support vocabulary contributors to create high quality vocabularies, we propose a method that semi-automatically ensures vocabulary quality in collaborative authoring processes. The proposed approach tackles this issue by (i) defining a set of criteria that serve as a metrics to measure vocabulary quality and (ii) introducing a method to continually assess and improve this quality. As a result of our approach, the developed vocabularies are expected to better fit the intentions of the contributors and are more useful for reuse and adoption on the Web of Data.

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.