Linked data fusion in ODCleanstore
Jan Michelfeit, Tomáš Knap · 2012
Abstract. As part of LOD2 project and OpenData.cz initiative, we are developing an ODCleanStore framework enabling management of Linked Data. In this paper, we focus on the query-time data fusion in ODCleanStore, which provides data consumers with integrated views on Linked Data; the fused data (1) has solved conflicts according to the preferred conflict resolution policies and (2) is accompanied with provenance and quality scores, so that the consumers can judge the usefulness and trustworthiness of the data for their task at hand. The advent of Linked Data [1] accelerates the evolution of the Web into an exponentially growing information space (see the linked open data cloud 1) where the unprecedented volume of data will offer information consumers a level of information integration and aggregation agility that has up to now not been possible. Consumers can now “mashup ” and readily integrate information for use in a myriad of alternative end uses. Indiscriminate addition of information can, however, come with inherent problems, such as the provision of poor quality, inaccurate, irrelevant or fraudulent information. All will come with an associate cost of the data integration which will ultimately affect data consumer’s benefit and linked data applications usage and uptake. To overcome these issues, as part of the OpenData.cz initiative and LOD2 project 2, we are developing the ODCleanStore (ODCS) framework 3 (1) enabling management of Linked Data – data cleaning, linking, transformation, and quality assessment – and (2) providing data consumers with a possibility to consume integrated data, which reduces the costs of the web application development. The overall picture of ODCS is depicted in Figure 1. ODCS processes RDF data feeds (collections of RDF quads, one data feed = one named graph 4) in the staging area; feeds can be uploaded to the staging area by any third-party