Skip to main content

VIEW LARGER COVER

The concept of utilizing big data to enable scientific discovery has generated tremendous excitement and investment from both private and public sectors over the past decade, and expectations continue to grow. Using big data analytics to identify complex patterns hidden inside volumes of data that have never been combined could accelerate the rate of scientific discovery and lead to the development of beneficial technologies and products. However, producing actionable scientific knowledge from such large, complex data sets requires statistical models that produce reliable inferences (NRC, 2013). Without careful consideration of the suitability of both available data and the statistical models applied, analysis of big data may result in misleading correlations and false discoveries, which can potentially undermine confidence in scientific research if the results are not reproducible. In June 2016 the National Academies of Sciences, Engineering, and Medicine convened a workshop to examine critical challenges and opportunities in performing scientific inference reliably when working with big data. Participants explored new methodologic developments that hold significant promise and potential research program areas for the future. This publication summarizes the presentations and discussions from the workshop.

RESOURCES AT A GLANCE

Suggested Citation

National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. https://doi.org/10.17226/24654.

Import this citation to:

Publication Info

114 pages | 7 x 10 | 

ISBNs: 
  • Paperback:  978-0-309-45444-5
  • Ebook:  978-0-309-45447-6
DOI: https://doi.org/10.17226/24654

What is skim?

The Chapter Skim search tool presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter. You may select key terms to highlight them within pages of each chapter.

Additional Downloads

Copyright Information

The National Academies Press (NAP) has partnered with Copyright Clearance Center's Rightslink service to offer you a variety of options for reusing NAP content. Through Rightslink, you may request permission to reprint NAP content in another publication, course pack, secure website, or other media. Rightslink allows you to instantly obtain permission, pay related fees, and print a license directly from the NAP website. The complete terms and conditions of your reuse license can be found in the license agreement that will be made available to you during the online order process. To request permission through Rightslink you are required to create an account by filling out a simple online form. The following list describes license reuses offered by the National Academies Press (NAP) through Rightslink:

  • Republish text, tables, figures, or images in print
  • Post on a secure Intranet/Extranet website
  • Use in a PowerPoint Presentation
  • Distribute via CD-ROM
  • Photocopy

Click here to obtain permission for the above reuses.If you have questions or comments concerning the Rightslink service, please contact:

Rightslink Customer Care
Tel (toll free): 877/622-5543
Tel: 978/777-9929
E-mail: customercare@copyright.com
Web: http://www.rightslink.com

To request permission to distribute a PDF, please contact our Customer Service Department at 800-624-6242 for pricing.

To request permission to translate a book published by the National Academies Press or its imprint, the Joseph Henry Press, pleaseclick here to view more information.

Loading stats for Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop...