[Humanist] 30.780 pubs: big data

Humanist Discussion Group willard.mccarty at mccarty.org.uk
Sat Feb 25 07:02:24 CET 2017

                 Humanist Discussion Group, Vol. 30, No. 780.
            Department of Digital Humanities, King's College London
                Submit to: humanist at lists.digitalhumanities.org

        Date: Sat, 25 Feb 2017 05:49:37 +0000
        From: Willard McCarty <willard.mccarty at mccarty.org.uk>
        Subject: big data

The following is not in digital humanities, but there are likely to be 
points of cross-over in it -- and it's free to download.


> Refining the Concept of Scientific Inference When Working with Big
> Data: Proceedings of a Workshop National Academies of Sciences,
> Engineering and Medicine
> https://www.nap.edu/download/24654
> 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.

Willard McCarty (www.mccarty.org.uk/), Professor, Department of Digital
Humanities, King's College London; Adjunct Professor, Western Sydney
University and North Carolina State University; Editor,
Interdisciplinary Science Reviews (www.tandfonline.com/loi/yisr20)

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