Exploring the Potential for Mapping Schema.org Microdata and the Web of Linked Data

Abstract

In recent years the exposure of Linked Open Data (LOD) has become widespread, with an increasing number of datasets available and enabling new opportunities for interlinking. In parallel, microdata in several forms has also proliferated mainly as a means to improve the effectiveness of search engines. Concretely, Schema.org consists of a vocabulary for microdata that enriches the information on pages, helping search engines to provide better results. In this paper we explore the potential of mapping Schema.org and the Web of Linked Data. First, mappings between Schema.org terms and terms in Linked Open Vocabularies (LOV) are extracted. Then we use these mappings to obtain an analysis, aimed at gaining insights about the potential impact of this vocabulary in the Web of Linked Data. The results show that is easier to find a mapping between classes than between properties, but the occurrences of these are many more in LOD. © Springer International Publishing Switzerland 2013.