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A Conceptual Modeling Framework for Expressing Observational Data Semantics

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Conceptual Modeling - ER 2008 (ER 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5231))

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Abstract

Observational data (i.e., data that records observations and measurements) plays a key role in many scientific disciplines. Observational data, however, are typically structured and described in ad hoc ways, making its discovery and integration difficult. The wide range of data collected, the variety of ways the data are used, and the needs of existing analysis applications make it impractical to define “one-size-fits-all” schemas for most observational data sets. Instead, new approaches are needed to flexibly describe observational data for effective discovery and integration. In this paper, we present a generic conceptual-modeling framework for capturing the semantics of observational data. The framework extends standard conceptual modeling approaches with new constructs for describing observations and measurements. Key to the framework is the ability to describe observation context, including complex, nested context relationships. We describe our proposed modeling framework, focusing on context and its use in expressing observational data semantics.

This work supported in part by NSF grants #0533368, #0553768, #0612326, #0225676, #0630033, and #0612326.

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Author information

Authors and Affiliations

  1. Genome Center, University of California, Davis

    Shawn Bowers

  2. Dept. of Biological Sciences, Macquarie University, Australia

    Joshua S. Madin

  3. National Center for Ecological Analysis and Synthesis, UC Santa Barbara, USA

    Mark P. Schildhauer

Authors
  1. Shawn Bowers
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  2. Joshua S. Madin
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  3. Mark P. Schildhauer
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Editor information

Editors and Affiliations

  1. Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China

    Qing Li

  2. EPFL-IC-IIF-LBD, Station 14 - INJ 236, 1015 Lausanne, Switzerland

    Stefano Spaccapietra

  3. Faculty of Information, University of Toronto, 140 St. George Street, M5S 3G6, Toronto, Ontario, Canada

    Eric Yu

  4. Universitat Politècnica Catalunya, Jordi Girona 1-3, 08034, Barcelona, Spain

    Antoni Olivé

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© 2008 Springer-Verlag Berlin Heidelberg

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Bowers, S., Madin, J.S., Schildhauer, M.P. (2008). A Conceptual Modeling Framework for Expressing Observational Data Semantics. In: Li, Q., Spaccapietra, S., Yu, E., Olivé, A. (eds) Conceptual Modeling - ER 2008. ER 2008. Lecture Notes in Computer Science, vol 5231. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87877-3_5

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  • DOI: https://doi.org/10.1007/978-3-540-87877-3_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87876-6

  • Online ISBN: 978-3-540-87877-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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