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International Conference on Scientific and Statistical Database Management

SSDBM 2009: Scientific and Statistical Database Management pp 218–236Cite as

Enabling Ad Hoc Queries over Low-Level Scientific Data Sets

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5566))

Abstract

Technological success has ushered in massive amounts of data for scientific analysis. To enable effective utilization of these data sets for all classes of users, supporting intuitive data access and manipulation interfaces is crucial. This paper describes an autonomous scientific workflow system that enables high-level, natural language based, queries over low-level data sets. Our technique involves a combination of natural language processing, metadata indexing, and a semantically-aware workflow composition engine which dynamically constructs workflows for answering queries based on service and data availability. A specific contribution of this work is a metadata registration scheme that allows for a unified index of heterogeneous metadata formats and service annotations. Our approach thus avoids a standardized format for storing all data sets or the implementation of a federated, mediator-based, querying framework. We have evaluated our system using a case study from the geospatial domain to show functional results. Our evaluation supports the potential benefits which our approach can offer to scientific workflow systems and other domain-specific, data intensive applications.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, The Ohio State University, Columbus, OH 43210, USA

    David Chiu & Gagan Agrawal

Authors
  1. David Chiu
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  2. Gagan Agrawal
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Illinois at Urbana-Champaign, 201 N. Goodwin Avenue, IL 61801, Urbana, USA

    Marianne Winslett

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© 2009 Springer-Verlag Berlin Heidelberg

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Chiu, D., Agrawal, G. (2009). Enabling Ad Hoc Queries over Low-Level Scientific Data Sets. In: Winslett, M. (eds) Scientific and Statistical Database Management. SSDBM 2009. Lecture Notes in Computer Science, vol 5566. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02279-1_17

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  • DOI: https://doi.org/10.1007/978-3-642-02279-1_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02278-4

  • Online ISBN: 978-3-642-02279-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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