Big data in libraries

Robert Olendorf, Yan Wang

Research output: Chapter in Book/Report/Conference proceedingChapter

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.

Original languageEnglish (US)
Title of host publicationBig Data and Visual Analytics
PublisherSpringer International Publishing
Pages191-202
Number of pages12
ISBN (Electronic)9783319639178
ISBN (Print)9783319639154
DOIs
StatePublished - Jan 15 2018

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All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

Cite this

Olendorf, R., & Wang, Y. (2018). Big data in libraries. In Big Data and Visual Analytics (pp. 191-202). Springer International Publishing. https://doi.org/10.1007/978-3-319-63917-8_11