Abstract
The amount of Linked Data containing statistics is increasing; and so is the need for concepts of analysing these statistics. Yet, there are challenges, e.g., discovering datasets, integrating data of different granularities, or selecting mathematical functions. To automatically, flexibly, and scalable integrate statistical Linked Data for expressive and reliable analysis, we propose to use expressive Semantic Web ontologies to build and evolve a well-interlinked conceptual model of statistical data for Online Analytical Processing.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Cyganiak, R., Field, S., Gregory, A., Halb, W., Tennison, J.: Semantic Statistics: Bringing Together SDMX and SCOVO. In: Proceedings of the WWW 2010 Workshop on Linked Data on the Web, pp. 2–6 (2010)
Kämpgen, B., Harth, A.: Transforming Statistical Linked Data for Use in OLAP Systems. In: Proceedings of the 7th International Conference on Semantic Systems. I-SEMANTICS 2011. ACM (2011)
Lechtenbörger, J., Vossen, G.: Multidimensional normal forms for data warehouse design. Information Systems Journal 28(5), 415–434 (2003)
Malinowski, E., Zimányi, E.: Hierarchies in a multidimensional model: From conceptual modeling to logical representation. Data Knowl. Eng. 59, 348–377 (2006)
Mazón, J.N., Trujillo, J., Serrano, M., Piattini, M.: Improving the Development of Data Warehouses by Enriching Dimension Hierarchies with WordNet. In: Collard, M. (ed.) ODBIS 2005/2006. LNCS, vol. 4623, pp. 85–101. Springer, Heidelberg (2007)
Nebot, V., Berlanga, R., Pérez, J.M., Aramburu, M.J., Pedersen, T.B.: Multidimensional Integrated Ontologies: A Framework for Designing Semantic Data Warehouses. In: Spaccapietra, S., Zimányi, E., Song, I.-Y. (eds.) Journal on Data Semantics XIII. LNCS, vol. 5530, pp. 1–36. Springer, Heidelberg (2009)
Niemi, T., Niinimäki, M.: Ontologies and summarizability in OLAP. In: Proceedings of the 2010 ACM Symposium on Applied Computing SAC 2010, p. 1349 (2010)
Niemi, T., Nummenmaa, J., Thanisch, P.: Constructing OLAP cubes based on queries. In: Proceedings of the 4th ACM international workshop on Data warehousing and OLAP. DOLAP 2001. ACM (2001)
Niinimäki, M., Niemi, T.: An ETL Process for OLAP Using RDF/OWL Ontologies. In: Spaccapietra, S., Zimányi, E., Song, I.-Y. (eds.) Journal on Data Semantics XIII. LNCS, vol. 5530, pp. 97–119. Springer, Heidelberg (2009)
Pardillo, J., Mazón, J.N.: Using Ontologies for the Design of Data Warehouses. Journal of Database Management 3(2), 73–87 (2011)
Pedersen, T.B., Jensen, C., Dyreson, C.E.: A foundation for capturing and querying complex multidimensional data. Information Systems Journal 26, 383–423 (2001)
Perez, J.M., Berlanga, R., Aramburu, M.J., Pedersen, T.B.: Integrating Data Warehouses with Web Data: A Survey. IEEE Transactions on Knowledge and Data Engineering 20, 940–955 (2008)
Phuoc, D.L., Hauswirth, M.: Linked Open Data in Sensor Data Mashups. In: Proceedings of the 2nd International Workshop on Semantic Sensor Networks (SSN 2009) in conjunction with ISWC 2009 (2009)
Rizzi, S., Abelló, A., Lechtenbörger, J., Trujillo, J.: Research in data warehouse modeling and design: dead or alive? In: Proceedings of the 9th ACM International Workshop on Data Warehousing and OLAP, pp. 3–10 (2006)
Romero, O., Abelló, A.: Automating Multidimensional Design from Ontologies. In: Proceedings of the ACM Tenth International Workshop on Data Warehousing and OLAP DOLAP 2007 (2007)
Shah, N., Tsai, C.F., Marinov, M., Cooper, J., Vitliemov, P., Chao, K.M.: Ontological On-line Analytical Processing for Integrating Energy Sensor Data. Iete Technical Review 26, 375 (2009)
Vassiliadis, P.: Modeling Multidimensional Databases, Cubes and Cube Operations. In: Proc. of the 10th SSDBM Conference. pp. 53–62 (1998)
Vrandečić, D., Lange, C., Hausenblas, M., Bao, J., Ding, L.: Semantics of Governmental Statistics Data. In: Proceedings of the WebSci 2010 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kämpgen, B. (2011). DC Proposal: Online Analytical Processing of Statistical Linked Data. In: Aroyo, L., et al. The Semantic Web – ISWC 2011. ISWC 2011. Lecture Notes in Computer Science, vol 7032. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25093-4_22
Download citation
DOI: https://doi.org/10.1007/978-3-642-25093-4_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25092-7
Online ISBN: 978-3-642-25093-4
eBook Packages: Computer ScienceComputer Science (R0)