Searching among the existing 500 and more vocabularies was never easier than today with the Linked Open Vocabularies (LOV) curated directory list. The LOV search provides one central point to explore the vocabulary terms space. However, it can be still cumbersome for non-experts or semantic annotation experts to discover the appropriate terms for the description of given website content. In this direction, the proposed approach is the cornerstone part of a methodology that aims to facilitate the selection of the highest ranked terms from the abundance of the registered vocabularies based on a keyword search. Moreover, it introduces for the first time the role of the contributors' background, which is retrieved from the LOV repository, in the ranking of the vocabularies. With this addition, we aim to address the issue of very low scores for the newly published vocabularies.
Ioannis Stavrakantonakis is a Ph.D. candidate at the Semantic Technology Institute (STI) of Innsbruck at the University of Innsbruck. His research interests in the broad area of Semantic Web technologies include linked open data, vocabularies discovery, modeling, social web and recommendation systems. He is currently finalising his Ph.D. thesis under the title "Approach to leverage Websites to APIs through Semantics", which has been awarded with a Netidee scholarship by the Internet Foundation Austria. Apart from the research part, he has a few years of experience as Software Engineer in the industry and currently working as a Senior Software Engineer at the technology center of the travel metasearch engine KAYAK in Berlin.
