Publishing CSV Data as Linked Data on the Web

Abstract

The majority of datasets on Open Government Data (OGD) portals are stored in comma-separated values (CSV) file. Publishing CSV data as a Linked Open Data (LOD) on the Web is an active field of research. However, there are very few effective applications have been developed with this purpose. Linked Data refer many ways for connecting and publishing structured data to data consumers, but available datasets are in CSV format. Therefore, publishing the CSV model on the webpage, it is needed to change CSV in RDF file format. Many methods and tools have been proposed for data mapping and publishing, however, most of them are not followed by the W3C recommendations rules. The contribution and goal of this paper are to develop a Semantic approach that can effectively convert CSV data into RDF data with rich semantics and release RDF data on the web using LOD principles. We utilize Semantic Web resources and W3C recommendation rules in automatic data publishing method, which enables distributed system for scalability. We apply the proposed method to existing CSVW Implementation Report-W3C and U.S Government’s application (data.gov). Our experimental results indicate that the proposed approach successfully converts CSV to RDF data and publish those RDF as LOD on the Web, with adequate performance on any sized datasets.