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Encyclopedia of Database Systems pp 1–6Cite as

Scientific Databases

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Definition

Scientific data refers to data that arise from scientific experiments, instruments, analytical tools, and computations. A chemistry experiment, for example, can yield data about the experimental setup, the pressure and temperature conditions under which the experiment was set up, measured variable like the heat released, initial and final masses the ingredients and products of the experiment, and so forth. The output of an instrument like a radio telescope, after running signal processing algorithms, will produce “images” of the radio-frequency sources in a part of the sky that the telescope was looking at. A biologist, after obtaining the image of a dye-filled nerve cell, uses image analysis software to produce a set of measurements that reflect the structure of the cell and its subparts. Recently, environmental sensors are cast in oceans and send real-time data on ocean temperature, salinity, oxygen content, and other parameters. A scientific database refers to an...

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Recommended Reading

  1. Ikeda H, Naito M. Evaluation of a combinatorial file organization scheme of order one. In: Proceedings of Study on Scientific Database Management Systems; 1979. p. 195–199 (in Japanese).

    Google Scholar 

  2. Coughran E. HYDROSEARCH, an easy-to-use retrieval system for hydrographic station data. Oceans. 1975;7:418–21.

    Google Scholar 

  3. Birss EW, Jones SE, Ries DR, Yeh JW. Scientific data base management at Lawrence Livermore Laboratory: needs and a prototype system. Technical Report UCRL-80146;CONF-771062–1, Lawrence Livermore Lab, California University. 1977.

    Google Scholar 

  4. Olle TW. The Codasyl approach to data base management. Chichester: Wiley; 1978.

    MATH  Google Scholar 

  5. Shoshani A, Olken F, Wong HKT. Characteristics of scientific databases. In: Proceedings of 10th International Conference on Very Large Data Bases; 1984. p. 147–60.

    Google Scholar 

  6. Shoshani A, Wong HKT. Statistical and scientific database issues. IEEE Trans Softw Eng. 1985;11(10):1040–7.

    Article  Google Scholar 

  7. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504.

    Article  Google Scholar 

  8. Demir E, Babur O, Dogrusoz U, Gursoy A, Nisanci G, Cetin-Atalay R, Ozturk M. PATIKA: an integrated visual environment for collaborative construction and analysis of cellular pathways. Bioinformatics. 2002;18(7):996–1003.

    Article  Google Scholar 

  9. Nikitin A, Egorov S, Daraselia N, Mazo I. Pathway studio – the analysis and navigation of molecular networks. Bioinformatics. 2003;19(16):2155–7.

    Article  Google Scholar 

  10. Gosink L, Shalf J, Stockinger K, Wu K, Bethel W. HDF5-FastQuery: accelerating complex queries on HDF datasets using fast bitmap indices. In: Proceedings 18th International Conference on Scientific and Statistical Database Management; 2006. p. 149–58.

    Google Scholar 

  11. Zhang X, Kurc T, Saltz J, Parthasarathy S. Design and analysis of a multi-dimensional data sampling service for large scale data analysis applications. In: Proceedings of 20th International Parallel and Distributed Processing Symposium; 2006.

    Google Scholar 

  12. Rotem D, Stockinger K, Wu K. In: Proceedings of 18th International Conference on Scientific and Statistical Database Management; 2006. p. 33–44.

    Google Scholar 

  13. Deshpande A, Samuel M. MauveDB: supporting model-based user views in database systems. In: Proceedings of the ACM SIGMOD International Conference on Management of Data. ACM; 2006. p. 73–84.

    Google Scholar 

  14. Fang L, Kristen L. Splash: ad-hoc querying of data and statistical models. In: Proceedings of the 13th International Conference on Extending Database Technology. ACM; 2010.

    Google Scholar 

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Author information

Authors and Affiliations

  1. San Diego Supercomputer Center, University of California-San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0505, USA

    Amarnath Gupta

Authors
  1. Amarnath Gupta
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Correspondence to Amarnath Gupta .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, Georgia, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, Ontario, Canada

    M. Tamer Özsu

Section Editor information

  1. San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, 92093-0505, La Jolla, CA, USA

    Amarnath Gupta

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Gupta, A. (2017). Scientific Databases. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_1275-2

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  • DOI: https://doi.org/10.1007/978-1-4899-7993-3_1275-2

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4899-7993-3

  • Online ISBN: 978-1-4899-7993-3

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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