A Provenance Assisted Roadmap for Life Sciences Linked Open Data Cloud
A significant portion of Web of Data is composed of multiple datasets that add high value to biomedical research. These datasets have been exposed on the web as a part of the Life Sciences Linked Open Data (LSLOD) Cloud. Different initiatives have been proposed for navigating through these datasets with or without vocabulary reuse. The significance of provenance information regarding life sciences data is great as compared to any other domain. With the provenance information, user becomes aware regarding the source, size, format along with authorization and privilege associated with the data. Previously, we proposed an approach for the creation of an active Linked Life Sciences Data Roadmap, that catalogues and links concepts as well as properties from 137 public SPARQL endpoints. In this work we extend the Roadmap with the provenance information collected directly by querying datasets. We designed a set of queries and the results were catalouged. This extended Roadmap is useful for dynamically assembling queries for retrieving data along with the provenance from multiple SPARQL endpoints. We also demonstrate its use in conjunction with other tools for selective SPARQL querying and the visualization of the LSLOD cloud. We have evaluated the performance of our approach in terms of time taken and success rates of data retrieved.
KeywordsLinked Data (LD) Provenance SPARQL Life Sciences (LS) Semantic web Query federation
Unable to display preview. Download preview PDF.
- 5.Clark, K.G., Feigenbaum, L., Torres, E.: Sparql protocol for rdf. World Wide Web Consortium (W3C) Recommendation (2008)Google Scholar
- 9.Hartig, O.: Trustworthiness of data on the web. In: Proceedings of the STI Berlin & CSW PhD Workshop. Citeseer (2008)Google Scholar
- 10.Hasnain, A., Fox, R., Decker, S., Deus, H.F.: Cataloguing and linking life sciences LOD cloud. In: 1st International Workshop on Ontology Engineering in a Data-driven World Collocated with EKAW 2012 (2012)Google Scholar
- 11.Hasnain, A., et al.: Linked biomedical dataspace: lessons learned integrating data for drug discovery. In: Mika, P., et al. (eds.) ISWC 2014, Part I. LNCS, vol. 8796, pp. 114–130. Springer, Heidelberg (2014) Google Scholar
- 14.Lebo, T., Sahoo, S., McGuinness, D., Belhajjame, K., Cheney, J., Corsar, D., Garijo, D., Soiland-Reyes, S., Zednik, S., Zhao, J.: Prov-o: The prov ontology. W3C Recommendation, 30th April (2013)Google Scholar
- 15.Omitola, T., Zuo, L., Gutteridge, C., Millard, I.C., Glaser, H., Gibbins, N., Shadbolt, N.: Tracing the provenance of linked data using void. In: Proceedings of the International Conference on Web Intelligence, Mining and Semantics, p. 17. ACM (2011)Google Scholar
- 16.Paulheim, H., Hertling, S.: Discoverability of SPARQL endpoints in linked open data. In: ISWC (Posters & Demos), pp. 245–248 (2013)Google Scholar
- 17.Quackenbush, J.: Standardizing the standards. Molecular Systems Biology 2(1) (2006)Google Scholar
- 19.Zeginis, D., et al.: A collaborative methodology for developing a semantic model for interlinking Cancer Chemoprevention linked-data sources. Semantic Web (2013)Google Scholar