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7 Conclusion

In this chapter we have presented the tools for vocabulary mapping, data interlinking, quality assessment and fusion, developed in the context of the LOD2 project. Specifically, R2R supports vocabulary mappings, Silk and LODRefine facilitate the process of creating and evaluating the quality of links among datasest, Sieve assists its users in assessing the data quality and resolving value conflicts. Additionally, Silk and Sieve has been extended to address interlinking and fusion issues specific to CJK (Chinese, Japanese and Korean) languages.

The presented tools are open source and make part of the Linked Data stack (see Chap. 6). The tools have been extensively evaluated, for the details the reader is referred to the respective sections, cited articles and tools' webpages. These tools have been applied within LOD2 project, e.g. in a media publishing, enterprise and public procurement use cases, for the details see Chaps. 7, 8 and 10 of the present book, respectively.

Open Access. This chapter is distributed under the terms of the Creative Commons Attribution Noncommercial License, which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.


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9. Isele, R., Bizer, C.: Active learning of expressive linkage rules using genetic programming. J. Web Semant. 23, 2–15 (2013)

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13. Verlic, M.: Release of documentation and software infrastructure for using Google Refine along with Amazon Mechanical Turk, 2013. LOD2 project delivarable D4.6.2.

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