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International Symposium on Intelligent Data Analysis

IDA 2012: Advances in Intelligent Data Analysis XI pp 7–22Cite as

Queries for Data Analysis

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7619))

Abstract

If we view data as a set of queries with an answer, what would a model be? In this paper we explore this question. The motivation is that there are more and more kinds of data that have to be analysed. Data of such a diverse nature that it is not easy to define precisely what data analysis actually is. Since all these different types of data share one characteristic – they can be queried – it seems natural to base a notion of data analysis on this characteristic.

The discussion in this paper is preliminary at best. There is no attempt made to connect the basic ideas to other – well known – foundations of data analysis. Rather, it just explores some simple consequences of its central tenet: data is a set of queries with their answer.

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Author information

Authors and Affiliations

  1. Algorithmic Data Analysis Group, Universiteit Utrecht, The Netherlands

    Arno Siebes

Authors
  1. Arno Siebes
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Editor information

Editors and Affiliations

  1. Department of Information and Computer Science, Aalto University School of Science, P.O. Box 15400, 00076, Aalto, Finland

    Jaakko Hollmén

  2. Department of Computer Science, Ostfalia University of Applied Sciences, Salzdahlumer Straße 46/48, 38302, Wolfenbüttel, Germany

    Frank Klawonn

  3. School of Information Systems, Computing and Mathematics, Brunel University, UB8 3PH, Uxbridge, Middlesex, UK

    Allan Tucker

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© 2012 Springer-Verlag Berlin Heidelberg

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Siebes, A. (2012). Queries for Data Analysis. In: Hollmén, J., Klawonn, F., Tucker, A. (eds) Advances in Intelligent Data Analysis XI. IDA 2012. Lecture Notes in Computer Science, vol 7619. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34156-4_3

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  • DOI: https://doi.org/10.1007/978-3-642-34156-4_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34155-7

  • Online ISBN: 978-3-642-34156-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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