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Big Data in Libraries

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Big Data and Visual Analytics

Abstract

The term Big Data is somewhat loose. Roughly defined, it refers to any data that exceeds the users ability to analyze it in one of three dimensions (the three Vs): Volume, Velocity and Variety. Laney [1, 2] Each of these has different challenges. Huge volumes of data require the ability to store and retrieve the data efficiently. High velocity data requires the ability to ingest the data as it is created, essentially very fast internet connections. Highly variable data can be difficult to organize and process due to its unpredictability and unstructured nature. Bieraugel [3] Also, multiple data streams can be combined to answer a variety of question. All forms of big data can require high performance computing and specialized software to analyze. Given the fuzziness of defining big data,

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References

  1. Laney, D.: META delta. Application delivery strategies, 949:4. (2001)

    Google Scholar 

  2. McCoy, C., Marcinkowski, M., Sawyer, S., Sanfilippo, M.R., Meyer, E.T., Rosenbaum, H.: Social informatics of data norms. Proc. Assoc. Inform. Sci. Technol. 53(1), 1–4 (2016)

    Article  Google Scholar 

  3. Bieraugel, M.: Keeping Up with Big Data. (2013)

    Google Scholar 

  4. Rosenbaum, H.: Social informatics of data norms. Proc. Assoc. Inform. Sci. Technol. 53(1), 1–4 (2016)

    Google Scholar 

  5. Chen, H.-I., Doty, P., Mollman, C., Niu, X., Yu, J.-C., Zhang, T.: Library assessment and data analytics in the big data era: practice and policies. Proc. Assoc. Inform. Sci. Technol. 52(1), 1–4 (2015)

    Google Scholar 

  6. Stanton, J.M.: Data science: what’s in It for the new librarian? https://ischool.syr.edu/infospace/2012/07/16/data-science-whats-in-it-for-the-new-librarian/ (2012). Accessed 12 Jan 2017

    Google Scholar 

  7. Hecht, R., Jablonski, S.: NoSQL evaluation: a use case oriented survey. In: Proceedings—2011 International Conference on Cloud and Service Computing, CSC 2011, pp. 336–341 (2011)

    Google Scholar 

  8. Inmon, W.: Building the Data Warehouse. Wiley, Hoboken, NJ (2005)

    Google Scholar 

  9. Sugimoto, C.R., Ding, Y., Thelwall, M.: Library and Information Science in the Big Data Era: Funding, Projects, and Future [A Panel Proposal]. (2012)

    Google Scholar 

  10. National Institutes of Health: Nih Data Sharing Policy. https://grants.nih.gov/grants/policy/data_sharing/ (2006). Accessed 14 Jan 2017

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Author information

Authors and Affiliations

  1. PennState University, Pennsylvania, PA, USA

    Robert Olendorf

  2. University of Alabama at Birmingham, Birmingham, AL, USA

    Yan Wang

Authors
  1. Robert Olendorf
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  2. Yan Wang
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Corresponding author

Correspondence to Yan Wang .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Texas A&M University-Commerce, Commerce, Texas, USA

    Sang C. Suh

  2. Department of Electrical and Computer Engineering, The University of Alabama at Birmingham, Birmingham, Alabama, USA

    Thomas Anthony

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Olendorf, R., Wang, Y. (2017). Big Data in Libraries. In: Suh, S., Anthony, T. (eds) Big Data and Visual Analytics. Springer, Cham. https://doi.org/10.1007/978-3-319-63917-8_11

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  • DOI: https://doi.org/10.1007/978-3-319-63917-8_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63915-4

  • Online ISBN: 978-3-319-63917-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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