StatSpace: A Unified Platform for Statistical Data Exploration

  • Ba-Lam DoEmail author
  • Peter Wetz
  • Elmar Kiesling
  • Peb Ruswono Aryan
  • Tuan-Dat Trinh
  • A Min Tjoa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10033)


In recent years, the amount of statistical data available on the web has been growing fast. Numerous organizations and governments publish data sets in a multitude of formats and encodings, using different scales, and providing access through a wide range of mechanisms. Due to such inconsistent publishing practices, integrated analysis of statistical data is challenging. StatSpace tackles this problem through semantic integration and provides uniform access to disparate statistical data. At present, it incorporates more than 1,800 data sets published by a variety of data providers including the World Bank, the European Union, and the European Environment Agency. StatSpace transparently lifts data from raw sources, maps geographical and temporal dimensions, aligns value ranges, and allows users to explore and integrate the previously isolated data sets. This paper introduces the constituent elements of the StatSpace architecture – i.e., a metadata repository, URI design patterns, and supporting services – and demonstrates the usefulness of the resulting Linked Data infrastructure by means of use case examples.


Statistical data Data integration Data exploration Service Metadata 


  1. 1.
    Becker, K., Tan, X., Jahangiri, S., Knoblock, C.A.: Finding, assessing, and integrating statistical sources for data mining. In: Proceedings of Know@LOD 2015. CEUR (2015)Google Scholar
  2. 2.
    Bizer, C., Heath, T., Berners-Lee, T.: Linked data - the story so far. Int. J. Semant. Web Inf. Syst. (IJSWIS) 5(3), 1–22 (2009)CrossRefGoogle Scholar
  3. 3.
    Capadisli, S., Auer, S., Ngonga Ngomo, A.C.: Linked SDMX data: path to high fidelity statistical linked data. Semantic Web 6(2), 105–112 (2015)Google Scholar
  4. 4.
    Cyganiak, R., Reynolds, D., Tennison, J.: The RDF data cube vocabulary (2014).
  5. 5.
    Dimou, A., Vander Sande, M., Colpaert, P., Verborgh, R., Mannens, E., Van de Walle, R.: RML: a generic language for integrated rdf mappings of heterogeneous data. In: Proceedings of Workshop on Linked Data on the Web (LDOW) (2014)Google Scholar
  6. 6.
    Do, B.L.: Technical report - documentation of uri design and mapping (2016).
  7. 7.
    Do, B.L., Aryan, P.R., Trinh, T.D., Wetz, P., Kiesling, E., Tjoa, A.M.: Toward a framework for statistical data integration. In: Proceedings of Workshop on Semantic Statistics (SemStats). CEUR (2015)Google Scholar
  8. 8.
    Do, B.L., Trinh, T.D., Aryan, P.R., Wetz, P., Kiesling, E., Tjoa, A.M.: Toward a statistical data integration environment: the role of semantic metadata. In: Proceedings of SEMANTICS Conference, pp. 25–32. ACM (2015)Google Scholar
  9. 9.
    Do, B.L., Trinh, T.D., Wetz, P., Anjomshoaa, A., Kiesling, E., Tjoa, A.M.: Widget-based exploration of linked statistical data spaces. In: Proceedings of Conference on Data Management Technologies and Applications (DATA). SciTePress (2014)Google Scholar
  10. 10.
    Kalampokis, E., Karamanou, A., Nikolov, A., Haase, P., Cyganiak, R., Roberts, B., Hermans, P., Tambouris, E., Tarabanis, K.: Creating and utilizing linked open statistical data for the development of advanced analytics services. In: Proceedings of Workshop on Semantic Statistics (SemStats). CEUR (2014)Google Scholar
  11. 11.
    Kalampokis, E., Roberts, B., Karamanou, A., Tambouris, E., Tarabanis, K.: Challenges on developing tools for exploiting linked open data cubes. In: Proceedings of Workshop on Semantic Statistics (SemStats). CEUR (2015)Google Scholar
  12. 12.
    Kämpgen, B., Stadtmüller, S., Harth, A.: Querying the Global Cube: integration of multidimensional datasets from the web. In: Janowicz, K., Schlobach, S., Lambrix, P., Hyvönen, E. (eds.) EKAW 2014. LNCS, vol. 8876, pp. 250–265. Springer, Heidelberg (2014)Google Scholar
  13. 13.
    Kelly, D., Gyllstrom, K., Bailey, E.W.: A comparison of query and term suggestion features for interactive searching. In: Proceedings of ACM SIGIR Conference on Research and development in information retrieval, pp. 371–378. ACM (2009)Google Scholar
  14. 14.
    Meroño-Peñuela, A.: LSD Dimensions: use and reuse of linked statistical data. In: Lambrix, P., Hyvönen, E., Blomqvist, E., Presutti, V., Qi, G., Sattler, U., Ding, Y., Ghidini, C. (eds.) EKWA 2014 Satellite Events. LNCS, vol. 8982, pp. 159–163. Springer, Heidelberg (2015)Google Scholar
  15. 15.
    Mutlu, B., Hoefler, P., Tschinkel, G., Veas, E., Sabol, V., Stegmaier, F., Granitzer, M.: Suggesting visualisations for published data. In: Proceedings of Conference on Information Visualization Theory and Applications (IVAPP), pp. 267–275. IEEE (2014)Google Scholar
  16. 16.
    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
  17. 17.
    Phillips, A.W.: The relation between unemployment and the rate of change of money wage rates in the United Kingdom, 1861–19571. Economica 25(100), 283–299 (1958)Google Scholar
  18. 18.
    Ruback, L., Manso, S., Salas, P.E.R., Pesce, M., Ortiga, S., Casanova, M.A.: A mediator for statistical linked data. In: Proceedings of Annual ACM Symposium on Applied Computing, pp. 339–341. ACM (2013)Google Scholar
  19. 19.
    Sabou, M., Arsal, I., Braşoveanu, A.M.: TourMISLOD: a tourism linked data set. Semant. Web 4(3), 271–276 (2013)Google Scholar
  20. 20.
    Salas, P.E.R., Martin, M., Da Mota, F.M., Auer, S., Breitman, K., Casanova, M.A.: Publishing statistical data on the web. In: Proceedings of International Conference on Semantic Computing (ICSC), pp. 285–292. IEEE (2012)Google Scholar
  21. 21.
    Schlegel, K., Stegmaier, F., Bayerl, S., Granitzer, M., Kosch, H.: Balloon fusion: SPARQL rewriting based on unified co-reference information. In: Proceedings of International Workshop on Data Engineering Meets the Semantic Web, pp. 254–259. IEEE (2014)Google Scholar
  22. 22.
    Schmachtenberg, M., Bizer, C., Paulheim, H.: Adoption of the linked data best practices in different topical domains. In: Mika, P., Tudorache, T., Bernstein, A., Welty, C., Knoblock, C., Vrandečić, D., Groth, P., Noy, N., Janowicz, K., Goble, C. (eds.) ISWC 2014, Part I. LNCS, vol. 8796, pp. 245–260. Springer, Heidelberg (2014)Google Scholar
  23. 23.
    Trinh, T.D., Wetz, P., Do, B.L., Anjomshoaa, A., Kiesling, E., Tjoa, A.M.: Open linked widgets mashup platform. In: Proceedings of the AI Mashup Challenge 2014. CEUR (2014)Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Ba-Lam Do
    • 1
    Email author
  • Peter Wetz
    • 1
  • Elmar Kiesling
    • 1
  • Peb Ruswono Aryan
    • 1
  • Tuan-Dat Trinh
    • 1
  • A Min Tjoa
    • 1
  1. 1.TU WienViennaAustria

Personalised recommendations