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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.

References

1. Acosta, M., Zaveri, A., Simperl, E., Kontokostas, D., Auer, S., Lehmann, J.: Crowdsourcing linked data quality assessment. In: Alani, H., Kagal, L., Fokoue, A., Groth, P., Biemann, C., Parreira, J.X., Aroyo, L., Noy, N., Welty, Ch., Janowicz, K. (eds.) ISWC 2013, Part II. LNCS, vol. 8219, pp. 260–276. Springer, Heidelberg (2013)

2. Bizer, C., Jentzsch, A., Cyganiak, R.: State of the LOD cloud. Technical report, Freie Universit¨at Berlin (2011). lod-cloud.net/state/

3. Bizer, C., Schultz, A.: The R2R framework: publishing and discovering mappings on the web. In: Proceedings of the 1st International Workshop on Consuming Linked Data (COLD) (2010)

4. Bleiholder, J., Naumann, F.: Declarative data fusion – syntax, semantics, and implementation. In: Eder, J., Haav, H.-M., Kalja, A., Penjam, J. (eds.) ADBIS 2005. LNCS, vol. 3631, pp. 58–73. Springer, Heidelberg (2005)

5. Bleiholder, J., Naumann, F.: Data fusion. ACM Comput. Surv. 41(1), 1:1–1:41 (2009)

6. Bryl, V., Bizer, C.: Learning conflict resolution strategies for cross-language Wikipedia data fusion. In: 4th Workshop on Web Quality Workshop (WebQuality) at WWW 2014 (2014)

7. Heath, T., Bizer, C.: Linked data: evolving the web into a global data space. Synthesis Lectures on the Semantic Web: Theory and Technology. Morgan & Claypool Publishers, San Rafael (2011)

8. Isele, R., Bizer, C.: Learning expressive linkage rules using genetic programming. Proc. VLDB Endowment 5(11), 1638–1649 (2012)

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

10. Isele, R., Jentzsch, A., Bizer, C.: Silk server adding missing links while consuming linked data. In: Proceedings of the 1st International Workshop on Consuming Linked Data (COLD 2010), pp. 85–97 (2010)

11. Mendes, P.N., Mu¨hleisen, H., Bizer, C.: Sieve: linked data quality assessment and fusion. In: EDBT/ICDT Workshops, pp. 116–123 (2012)

12. Petrovski, P., Bryl, V., Bizer, C.: Integrating product data from websites offering Microdata markup. In: 4th Workshop on Data Extraction and Object Search (DEOS2014) at WWW 2014 (2014)

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. static.lod2.eu/Deliverables/D4.6.2.pdf

 
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