Yasminers
here is a possible discussion topic
Big Data Made Sensible ? Making Big Data Meaningful ?
Lots of confusion out there under the buzz word of 'big data' that
conflates issues of form and content of large
data streams. A key caveat is that you can only analyse the data you
have not the data you need and of course
as Albert Einstein warned: Everything that can be counted does not
necessarily count; everything that counts cannot necessarily be
counted.
There is a big debate between empirical and qualitative methods in the
arts and humanities.
One interesting area that allows new approaches to make sense of large
data sets is complex network
science= where insights on the structure and interconnections of data
can be obtained. Leonardo for the past few
years has been championing the research and creative community that is
linking the arts, humanities and complex networks
through annual Leonardo Day Symposia at the NETSCI conferences. The
latest one is June 4 in Copenhagen.
http://artshumanities.netsci2013.net/
A Leonardo ebook now brings together the work of 45 artists and researchers :
http://www.amazon.com/kindle-store/dp/B007S0UA9Q
(note- if you bought previous editions of this ebook, you
automatically get the annual updates free).
The work ranges from the study of archeological remains, to social
media networks, to biological to art history to
network music that sonifies the structure of the web.
We are also having a great evening at the Medical Museum in Copenhagen
in the old dissection theater
on The Data Body on the Dissection Table= on complex networks and medicine
http://olats.org/studiolab/databody.php
There is no doubt set as data sets get bigger there are new research
areas that become 'enabled'- for instance the
study of rare events or unusual relationships is facilitated when data
sets become very large. Digitisation also brings
topics into the reach of numerical methods topics which until then
remain elusive or apocryphal ( eg the evolution of
language through analysis of millions of texts over 300 years).
However big data enthusiasts need to remember Einstein's warning that :
Everything that can be counted does not necessarily count; everything
that counts cannot necessarily be counted.
PS you can find the abstracts of the ebook at:
http://ahcncompanion.info/
and more discussion on my blog
http://malina.diatrope.com/2013/06/02/big-data-made-sensible/
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