[Humanist] 27.181 pubs: massive data analysis

Humanist Discussion Group willard.mccarty at mccarty.org.uk
Tue Jul 2 22:41:26 CEST 2013


                 Humanist Discussion Group, Vol. 27, No. 181.
            Department of Digital Humanities, King's College London
                       www.digitalhumanities.org/humanist
                Submit to: humanist at lists.digitalhumanities.org



        Date: Wed, 03 Jul 2013 06:33:19 +1000
        From: Willard McCarty <willard.mccarty at mccarty.org.uk>
        Subject: new publication: Frontiers in Massive Data Analysis

Frontiers in Massive Data Analysis
National Academies Press (www.nap.edu)

 From Facebook to Google searches to bookmarking a webpage in our 
browsers, today's society has become one with an enormous amount of 
data. Some internet-based companies such as Yahoo! are even storing 
exabytes (10 to the 18 bytes) of data. Like these companies and the rest 
of the world, scientific communities are also generating large amounts 
of data-—mostly terabytes and in some cases near petabytes—from 
experiments, observations, and numerical simulation. However, the 
scientific community, along with defense enterprise, has been a leader 
in generating and using large data sets for many years. The issue that 
arises with this new type of large data is how to handle it—this 
includes sharing the data, enabling data security, working with 
different data formats and structures, dealing with the highly 
distributed data sources, and more.

Frontiers in Massive Data Analysis presents the Committee on the 
Analysis of Massive Data's work to make sense of the current state of 
data analysis for mining of massive sets of data, to identify gaps in 
the current practice and to develop methods to fill these gaps. The 
committee thus examines the frontiers of research that is enabling the 
analysis of massive data which includes data representation and methods 
for including humans in the data-analysis loop. The report includes the 
committee's recommendations, details concerning types of data that build 
into massive data, and information on the seven computational giants of 
massive data analysis.

For more:
http://www.nap.edu/catalog.php?record_id=18374&utm_medium=etmail&utm_source=The%20National%20Academies%20Press&utm_campaign=NAP+mail+new+07.02.13&utm_content=Downloader&utm_term=allTopics
-- 
Willard McCarty, FRAI / Professor of Humanities Computing & Director of
the Doctoral Programme, Department of Digital Humanities, King's College
London; Professor, Research Group in Digital Humanities, University of
Western Sydney; Editor, Interdisciplinary Science Reviews
(www.isr-journal.org); Editor, Humanist (dhhumanist.org);
www.mccarty.org.uk/




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