A Bottom-Up Approach for Licences Classification and Selection
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Licences are a crucial aspect of the information publishing process in the web of (linked) data. Recent work on modeling of policies with semantic web languages (RDF, ODRL) gives the opportunity to formally describe licences and reason upon them. However, choosing the right licence is still challenging. Particularly, understanding the number of features - permissions, prohibitions and obligations - constitute a steep learning process for the data provider, who has to check them individually and compare the licences in order to pick the one that better fits her needs. The objective of the work presented in this paper is to reduce the effort required for licence selection. We argue that an ontology of licences, organized by their relevant features, can help providing support to the user. Developing an ontology with a bottom-up approach based on Formal Concept Analysis, we show how the process of licence selection can be simplified significantly and reduced to answering an average of three/five key questions.
KeywordsRDF Licences and linked data Formal Concept Analysis
- 1.Steyskal, S., Polleres, A.: Defining expressive access policies for linked data using the ODRL ontology 2.0. In: Sack, H., et al. (eds.) Proceedings of the 10th International Conference on Semantic Systems (SEMANTiCS 2014). ACM, New York (2014)Google Scholar
- 2.Rodríguez-Doncel, V., Villata, S., Gómez-Pérez, A.: A dataset of RDF licenses. In: Hoekstra, H. (ed.) Legal Knowledge and Information Systems. JURIX 2014: The Twenty-Seventh Annual Conference. IOS Press, Amsterdam (2014)Google Scholar
- 4.Cardellino, C., Villata, S., Gandon, F., et al.: Licentia: a tool for supporting users in data licensing on the web of data. In: Horridge, M., Rospocher, M., van Ossenbruggen, J. (eds.) Proceedings of the ISWC 2014 Posters Demonstrations Track, a Track within the 13th International Semantic Web Conference (ISWC 2014), Riva del Garda, Italy, 21 October 2014Google Scholar
- 8.Li, X., Murata, T.: A knowledge-based recommendation model utilizing formal concept analysis and association. In: 2010 the 2nd International Conference on Computer and Automation Engineering (ICCAE), vol. 4, pp. 221–226. IEEE (2010)Google Scholar
- 10.Obitko, M., Snasel, V., Smid, J., Snasel, V.: Ontology design with formal concept analysis. In: CLA, vol. 110 (2004)Google Scholar
- 12.d’Aquin, M., Adamou, A., Daga, E., et al.: Dealing with diversity in a smart-city datahub. In: Omitola, T., Breslin, J., Barnaghi, P. (eds.) Proceedings of the Fifth Workshop on Semantics for Smarter Cities, a Workshop at the 13th International Semantic Web Conference (ISWC 2014), Riva del Garda, Italy, 19 October 2014. CEUR-WS.orgGoogle Scholar
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