One of the core visions of the Semantic Web is that data can be shared across the boundaries of applications and websites. A particular application of Semantic Web is Linked Data, which publishes data as Web Data in RDF format. It enables sharing and accessing data in a decentralised manner. This is has led to the rise of many Linked Data initiatives, with its most successful project Linked Open Data (LOD), which at this time numbers thousands of datasets, and with a magnitude of billions of triples. The LOD is still in its beginnings and apart from making data accessible across the Web, however, it has a long way to go to accomplish its original goal of uniformly accessing data across the Web and datasets. In this work we identify several challenges that hinder the fulfilment of the original goal of the Semantic Web, respectively the Linked Data initiative. The question is: How do we uniformly accessing all the resources published as part of the LOD independent of their source, data type, access mode or data structure? The main focus of this work will be at understanding and proposing approaches that tackle these challenges, towards a model for uniformly accessing and integrating data coming from different datasets with heterogeneous structures, i.e. RDF datasets or Web service APIs. In this context DORIS[1] system is proposed in order to enable a uniform access to Web services with the purpose of enriching a target knowledge base.
[1]: M. Koutraki, D. Vodislav, N. Preda. Deriving Intensional Descriptions for Web Services. In International Conference on Information and Knowledge Management (CIKM),2015, Melbourne, Australia.
(dans le cadre d'un recrutement post-Doc)
