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Visual Analysis of Statistical Data on Maps Using Linked Open Data

  • Petar Ristoski
  • Heiko Paulheim
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9341)

Abstract

When analyzing statistical data, one of the most basic and at the same time widely used techniques is analyzing correlations. As shown in previous works, Linked Open Data is a rich resource for discovering such correlations. In this demo, we show how statistical analysis and visualization on maps can be combined to facilitate a deeper understanding of the statistical findings.

Keywords

Linked Open Data Visualization Correlations Statistical data 

Notes

Acknowledgements

The work presented in this paper has been partly funded by the German Research Foundation (DFG) under grant number PA 2373/1-1 (Mine@LOD).

References

  1. 1.
    Klímek, J., Helmich, J., Neasky, M.: Application of the linked data visualization model on real world data from the Czech LOD cloud. In: 6th International Workshop on the Linked Data on the Web (LDOW 2014) (2014)Google Scholar
  2. 2.
    Mutlu, B., Hoefler, P., Tschinkel, G., Veas, E.E., Sabol, V., Stegmaier, F., Granitzer, M.: Suggesting visualisations for published data. In: Proceedings of IVAPP, pp. 267–275 (2014)Google Scholar
  3. 3.
    Paulheim, H.: Generating possible interpretations for statistics from linked open data. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, O., Presutti, V. (eds.) ESWC 2012. LNCS, vol. 7295, pp. 560–574. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  4. 4.
    Peña, O., Aguilera, U., López-de Ipiña, D.: Linked open data visualization revisited: a survey. Under Review at Semant. Web J. (2015)Google Scholar
  5. 5.
    Ristoski, P., Bizer, C., Paulheim, H.: Mining the web of linked data with rapidminer. In: Semantic Web Challenge at ISWC (2014)Google Scholar
  6. 6.
    Ristoski, P., Paulheim, H.: Analyzing statistics with background knowledge from linked open data. In: Workshop on Semantic Statistics (2013)Google Scholar
  7. 7.
    Schmachtenberg, M., Bizer, C., Paulheim, H.: Adoption of the linked data best practices in different topical domains. In: Mika, P., et al. (eds.) ISWC 2014, Part I. LNCS, vol. 8796, pp. 245–260. Springer, Heidelberg (2014) Google Scholar
  8. 8.
    Tilahun, B., Kauppinen, T., Keßler, C., Fritz, F.: Design and development of a linked open data-based health information representation and visualization system: potentials and preliminary evaluation. JMIR Med. Inf. 2(2), 196–208 (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

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Authors and Affiliations

  1. 1.University of Mannheim, Research Group Data and Web Science B6 26MannheimGermany

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