[okfn-discuss] FW: [dcc-associates] FW: [e-Science Strategy] Announcement of an Open Data-Intensive Research workshop 15 March in the e-Science Institute, Edinburgh

Thu Feb 18 12:13:24 UTC 2010

FYI- apologies if you have already seen this.
Non Scantlebury
Head of Research and Innovation
The Open University Library

-----Original Message-----
From: Joy Davidson [mailto:british.editor at erpanet.org] 
Sent: 18 February 2010 09:36
To: dcc-associates at lists.ed.ac.uk; projects at hatii.arts.gla.ac.uk
Subject: [dcc-associates] FW: [e-Science Strategy] Announcement of an Open Data-Intensive Research workshop 15 March in the e-Science Institute, Edinburgh

-----Original Message-----
From: owner-nesc-announce at nesc.ac.uk [mailto:owner-nesc-announce at nesc.ac.uk]
On Behalf Of Jo Newman
Sent: 17 February 2010 15:48
To: nesc-announce at nesc.ac.uk
Subject: [e-Science Strategy] Announcement of an Open Data-Intensive
Research workshop 15 March in the e-Science Institute, Edinburgh

Message sent on behalf of Malcolm Atkinson

++++++++++++

Dear Colleagues

We are holding a workshop on data-intensive research at the e-Science 
Institute in Edinburgh.
You may have already received an invitation, in which case my apologies 
for the duplicate mailing.

The event is described on the eSI events page
http://www.nesc.ac.uk/esi/events/1047/
which you should go to to register if you are able to come.

The provisional, but rapidly becoming firm timetable is on page
http://wikis.nesc.ac.uk/escienvoy/Data-Intensive_Research:_how_should_we_imp
rove_our_ability_to_use_data

and on the pages that it references.

If you know anyone who is likely to be interested in the event please 
forward this email.

The introduction to Monday begins:
----
The use of data in research is growing rapidly; the digital revolution 
generates more and more data, and policies encourage more data to be 
published. Expectations for openness, repeatability and evidence quality 
increase the data-use imperative.

Data use includes the data-curation lifecycle from creation or 
collection, through cleaning, integration, analysis, annotation, 
citation and presentation to preservation or discard. It includes 
finding data, developing an understanding of a body of data (often drawn 
from multiple sources), working out how to get evidence from data or 
what the newly available collections of data may now enable, deciding 
how to extract evidence from data possibly in combination with other 
data and presenting results so that evidence is understood, trusted and 
used.

There are many challenges in the wide range of data uses; for example, 
coping with complexity, with variable or poor data quality, with high 
volumes, with sophisticated analytic and presentation requests, with 
high data rates, with heterogeneity, with user numbers and diversity and 
so on. These challenges are addressed through multiple forms of 
iteration, progressively discovering and understanding data, 
progressively developing and understanding analytic methods, 
progressively refining the processes used to obtain particular forms of 
evidence, progressively improving the software, progressively adapting 
the computational platforms, and so on. Communities of data users build 
expertise around data and as they do they change requirements, patterns 
of use and modes of acceptable behaviour.

Data-intensive research is both research in any domain that has to pay 
serious attention to the ways in which it uses data in order to succeed, 
and research that improves our ability to use data. These co-evolve.

Monday's programme explores that co-evolution.
----

Space is limited to 100 participants, so please register quickly if you 
are interested.
If you are interested in staying beyond Monday, please email me 
(mpa at nesc.ac.uk).

With best wishes

Malcolm

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