Programming the Semantic Web
The Semantic Web changes the way we deal with data, because assumptions about the nature of the data that we deal with differ substantially from the ones in established database approaches. Semantic Web data is (i) provided by different people in an ad-hoc manner, (ii) distributed, (iii) semi-structured, (iv) (more or less) typed, (v) supposed to be used serendipitously. In fact, these are highly relevant assumptions and challenges, since they are frequently encountered in all kind of data-centric challenges also in cases where Semantic Web standards are not in use. However, they are only partially accounted for in existing programming approaches for Semantic Web data including (i) semantic search, (ii) graph programming, and (iii) traditional database programming approaches.
The main hypothesis of this talk is that we have not yet developed the right kind of programming paradigms to deal with the proper nature of Semantic Web data, because none of the mentioned approaches fully considers its characteristics. Thus, we want to outline empirical investigations of Semantic Web data and recent developments towards Semantic Web programming that target the reduction of the impedance mismatches between data engineering and programming approaches.
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- 1.Alexander, K., Cyganiak, R., Hausenblas, M., Zhao, J.: Describing linked datasets with the void vocabulary, http://www.w3.org/TR/void/ (last visited August 30, 2011)
- 2.Gottron, T., Scherp, A., Krayer, B., Peters, A.: LODatio: Using a Schema-Based Index to Support Users in Finding Relevant Sources of Linked Data. In: K-CAP 2013: Proceedings of the Conference on Knowledge Capture, pp. 105–108 (2013)Google Scholar
- 3.Gottron, T., Scherp, A., Scheglmann, S.: Providing alternative declarative descriptions for entity sets using parallel concept lattices. In: Presutti, V., d’Amato, C., Gandon, F. (eds.) ESWC 2014. LNCS, vol. 8465, pp. 362–376. Springer, Heidelberg (2014)Google Scholar
- 4.Konrath, M., Gottron, T., Staab, S., Scherp, A.: SchemEX—Efficient Construction of a Data Catalogue by Stream-based Indexing of Linked Data. Web Semantics: Science, Services and Agents on the World Wide Web 16(5), 52–58 (2011)Google Scholar
- 5.Völker, J., Niepert, M.: Statistical schema induction. In: Antoniou, G., Grobelnik, M., Simperl, E., Parsia, B., Plexousakis, D., De Leenheer, P., Pan, J. (eds.) ESWC 2011, Part I. LNCS, vol. 6643, pp. 124–138. Springer, Heidelberg (2011)Google Scholar