DING! Dataset Ranking using Formal Descriptions
Toupikov, Nickolai Umbrich, Jürgen Delbru, Renaud Hausenblas, Michael Tummarello, Giovanni
Toupikov, Nickolai
Umbrich, Jürgen
Delbru, Renaud
Hausenblas, Michael
Tummarello, Giovanni
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2009
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Workshop paper
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Nickolai Toupikov, Jürgen Umbrich , Renaud Delbru, Michael Hausenblas, Giovanni Tummarello "DING! Dataset Ranking using Formal Descriptions", Linked Data on the Web Workshop (LDOW 09), in conjunction with 18th International World Wide Web Conference (WWW 09), 2009.
Abstract
Considering that thousands if not millions of linked datasets will be published soon, we motivate in this paper the need for an efficient and effective way to rank interlinked datasets based on formal descriptions of their characteristics. We propose DING (from Dataset RankING) as a new approach to rank linked datasets using information provided by the voiD vocabulary. DING is a domain-independent link anal- ysis that measures the popularity of datasets by considering the cardinality and types of the relationships. We propose also a methodology to automatically assign weights to link types. We evaluate the proposed ranking algorithm against other well known ones, such as PageRank or HITS, using synthetic voiD descriptions. Early results show that DING performs better than the standardWeb ranking algorithms.
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Attribution-NonCommercial-NoDerivs 3.0 Ireland