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Querying the Global Cube: Integration of Multidimensional Datasets from the Web

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8876))

Abstract

National statistical indicators such as the Gross Domestic Product per Capita are published on the Web by various organisations such as Eurostat, the World Bank and the International Monetary Fund. Uniform access to such statistics will allow for elaborate analysis and visualisations. Though many datasets are also available as Linked Data, heterogeneities remain since publishers use several identifiers for common dimensions and differing levels of detail, units, and formulas. For queries over the Global Cube, i.e., the integration of available datasets modelled in the RDF Data Cube Vocabulary, we extend the well-known Drill-Across operation over data cubes to consider implicit overlaps between datasets in Linked Data. To evaluate more complex mappings we define the Convert-Cube operation over values from a single dataset. We generalise the two operations for arbitrary combinations of multiple datasets with the Merge-Cubes operation and show the feasibility of the analytical operations for integrating government statistics.

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References

  1. Abelló, A., Samos, J., Saltor, F.: Implementing Operations to Navigate Semantic Star Schemas. In: Proceedings of DOLAP. ACM Press (2003)

    Google Scholar 

  2. Calvanese, D., De Giacomo, G., Lenzerini, M., Nardi, D., Rosati, R.: Data Integration in Data Warehousing. International Journal of Cooperative Information Systems 10, 237–271 (2001)

    Article  Google Scholar 

  3. Capadisli, S., Auer, S., Riedl, R.: Linked Statistical Data Analysis. Semantic Web Challenge 2013 (2013)

    Google Scholar 

  4. Diamantini, C., Potena, D., Storti, E.: A Logic-Based Formalization of KPIs for Virtual Enterprises. Advanced Information Systems, 274–285 (2013)

    Google Scholar 

  5. Etcheverry, L., Vaisman, A.A.: Enhancing OLAP Analysis with Web Cubes. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, O., Presutti, V. (eds.) ESWC 2012. LNCS, vol. 7295, pp. 469–483. Springer, Heidelberg (2012)

    Google Scholar 

  6. Gómez, L.I., Gómez, S.A., Vaisman, A.A.: A Generic Data Model and Query Language for Spatiotemporal OLAP Cube Analysis Categories and Subject Descriptors. In: Proceedings of EDBT (2012)

    Google Scholar 

  7. Kämpgen, B., Harth, A.: Transforming Statistical Linked Data for Use in OLAP Systems. In: Proceedings of the 7th I-Semantics (2011)

    Google Scholar 

  8. Kämpgen, B., Harth, A.: No size fits all – running the star schema benchmark with SPARQL and RDF aggregate views. In: Cimiano, P., Corcho, O., Presutti, V., Hollink, L., Rudolph, S. (eds.) ESWC 2013. LNCS, vol. 7882, pp. 290–304. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  9. Shukla, A., Deshpande, P.M., Naughton, J.F.: Materialized View Selection for Multi-cube Data Models. In: Proceedings of EDBT, pp. 269–284 (2000)

    Google Scholar 

  10. Siegel, M., Sciore, E., Rosenthal, A.: Using semantic values to facilitate interoperability among heterogeneous information systems. Transactions on Database Systems (1994)

    Google Scholar 

  11. Stadtmüller, S., Harth, A.: Data-Fu: A Language and an Interpreter for Interaction with Read / Write Linked Data. In: Proceedings of WWW (2013)

    Google Scholar 

  12. Torlone, R.: Two approaches to the integration of heterogeneous data warehouses. Distributed and Parallel Databases 23(1), 69–97 (2007)

    Article  Google Scholar 

  13. Tseng, F., Chen, C.: Integrating heterogeneous data warehouses using XML technologies. Journal of Information Science 31 (2005)

    Google Scholar 

  14. Wilkinson, K., Simitsis, A.: Designing Integration Flows Using Hypercubes. In: Proceedings of EDBT/ICDT (2011)

    Google Scholar 

  15. Zapilko, B., Mathiak, B.: Object property matching utilizing the overlap between imported ontologies. In: Presutti, V., d’Amato, C., Gandon, F., d’Aquin, M., Staab, S., Tordai, A. (eds.) ESWC 2014. LNCS, vol. 8465, pp. 737–751. Springer, Heidelberg (2014)

    Google Scholar 

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© 2014 Springer International Publishing Switzerland

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Kämpgen, B., Stadtmüller, S., Harth, A. (2014). Querying the Global Cube: Integration of Multidimensional Datasets from the Web. In: Janowicz, K., Schlobach, S., Lambrix, P., Hyvönen, E. (eds) Knowledge Engineering and Knowledge Management. EKAW 2014. Lecture Notes in Computer Science(), vol 8876. Springer, Cham. https://doi.org/10.1007/978-3-319-13704-9_20

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  • DOI: https://doi.org/10.1007/978-3-319-13704-9_20

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13703-2

  • Online ISBN: 978-3-319-13704-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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