Information Technology Reference
In-Depth Information
SCENARIO : training those who (will) deposit research data
DataManager Z works at a national research institute that was one of the
very first to require from its researchers that all data collected for their
research is stored in its datacentre. It took a little while before the practice
had found its pattern, but now Mr Z gets inundated by datasets, of any sort,
size and shape. On the website of his datacentre a manual was published
about the formats to use, the “metadata” to add and the descriptors to use to
ensure optimal storage, preservation and re-use of the data. But to no avail.
The biggest problem is that hardly any of the researchers have been think-
ing through what later storage, preservation and re-use implies for the way
the data is collected. And after the fact, it is difficult to repair any flaws, if
only because many of the researchers have already moved on to their next
project.
Z decides that the situation will not get any better if the researchers (most of
them young and enthusiastic but relatively inexperienced PhD? 's) do not get
any training. So he starts 1-day training sessions, widely announced, but with
very few attendants. Then he thinks of e-learning modules. New researchers who
join the institute are required to work through the module in their first month and
finish it with an online test. Also, any research proposal at the institute requires a
separate paragraph about the data collection, preservation and possibilities for
re-use.
24.3.2 Next Steps
Make organisations aware that digital preservation is not only a technical
challenge but also requires adjustments to their policies and procedures.
Define and apply standards for exchange of data sets across research institutes
and archives.
Define and apply standards for openness of data (aka Creative Commons for
data).
Agree on a checklist for digital archives to become "trusted".
Develop training courses to teach researchers how to cope with digital data
(awareness raising).
Develop e-learning modules for training researchers to work with data sets and
how to archive and share them.
Develop guidelines for researchers and their institutes to come to common
practice data formats which are suitable for archiving.
Build a cross-domain virtual platform for researchers to learn about best practices
in sharing and archiving of data.
Commission expert panels (for each discipline) to support the selection process
of what needs to be preserved and what not.
 
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