Skip to main content
Springer Nature Link
Log in

Database Use in Science Applications

  • Reference work entry
Encyclopedia of Database Systems

  • 387 Accesses

Definition

A science application is any application where a natural, social or engineering problem is investigated.

The Problem

Many science applications are data intensive. Scientific experiments produce large volumes of complex data, and have a dire need to create persistent repositories for their data and knowledge. It would seem natural that data management systems and technology will be heavily used in science. And yet, scientists traditionally do not use database management systems, and often develop home-grown solutions, or file-based software for their complex data management needs. Clearly, there is a gap between scientists’ intended use of data and what current data management systems provide.

Foundations

There are many reasons, both technical and non-technical, that explain why science users do not use data management systems for their applications. A recent study [3] highlights a number of factors scientists have cited. Others [2,4,6] have analyzed different reasons why...

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Recommended Reading

  1. Altintas I., Berkley C., Jaeger E., Jones M., Ludäscher B., and Mock S. Kepler: an extensible system for design and execution of scientific workflows. In Proc. 16th Int. Conf. Scientific and Statistical Database Management, 2004, pp. 423–424.

    Google Scholar 

  2. Buneman P. Why Scientists Don’t Use Databases? NeSC presentation, 2002. Available from www.nesc.ac.uk/talks/opening/no_use.pdf.

  3. Gray J., Liu D.T., Nieto-Santisteban M.A., Szalay A.S., Heber G., and DeWitt D. Scientific data management in the coming decade. ACM SIGMOD Rec., 34(4): 35–41, 2005.

    Google Scholar 

  4. Liebman M.J. Data management systems: science versus technology? OMICS J. Integr. Biol., 7(1):67–69, 2003.

    Google Scholar 

  5. Livny M., Ramakrishnan R., Beyer K., Chen G., Donjerkovic D., Lawande S., Myllymaki J., and Wenger K. DEVise: Integrated Querying and Visual Exploration of Large Datasets. In Proc. 2007 ACM SIGMOD Int. Conf. on Management of Data. Tucson, AZ, 1997, pp. 301–312.

    Google Scholar 

  6. Maier D. Will database systems fail bioinformatics, too? OMICS J. Integr. Biol., 7(1):71–73, 2003.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of California-San Diego, La Jolla, CA, USA

    Amarnath Gupta

Authors
  1. Amarnath Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. College of Computing, Georgia Institute of Technology, 266 Ferst Drive, 30332-0765, Atlanta, GA, USA

    LING LIU (Professor) (Professor)

  2. Database Research Group David R. Cheriton School of Computer Science, University of Waterloo, 200 University Avenue West, N2L 3G1, Waterloo, ON, Canada

    M. TAMER ÖZSU (Professor and Director, University Research Chair) (Professor and Director, University Research Chair)

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer Science+Business Media, LLC

About this entry

Cite this entry

Gupta, A. (2009). Database Use in Science Applications. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_1276

Download citation

Publish with us

Policies and ethics