the ability to work independently at the intersection of digital data,
technology, and metadata. These core skills are the base on which training in
digital preservation concepts, data modeling, data standards, policy, and data
collection and management can be added to
round out a data liaison’s preparation. In
addition, because data services are in their
infancy, it cannot hurt for a data liaison to be
skilled in building library programs and
services.
There is a long-standing debate over
whether it is more important for engineering
and science data curation liaisons to have domain expertise or information
science expertise. The answer is that data liaisons must have both. To create
data liaisons with this combination of skills, libraries can develop existing
liaisons with interest, passion, and strong analytical skills; or they can recruit
domain experts, and teach them about excellent information science practices.
Consider the following four potential data liaison personas:
A subject liaison with a domain-specific education and work
experience in a field such as civil engineering or chemistry.
A subject liaison with no domain-specific expertise, but with
excellent analytical and technical skills who has a passion for
understanding and manipulating data.
A researcher in the life sciences who fell into managing data
for a lab because they were the only one available to do it and
they find the work enjoyable.
A newly minted Masters of Science candidate from a library
and information science program with a specialization
in research data curation.
One important feature of data curation in engineering and science fields is
that curatorial needs vary widely across each discipline. In physics there are
large, established data repositories and a hugely collaborative culture;
therefore the data curation services needed by individual physicists may be
fewer and necessarily very different from services that might be useful in the
neurosciences, where disciplinary repositories are not as common and the
proliferation of data types and formats prevents easy standardization. For this
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The Last Mile: Liaison Roles in Curating Science and Engineering Research Data
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AUGUST 2009 RESEARCH LIBRARY ISSUES: A BIMONTHLY REPORT FROM ARL, CNI, AND SPARC
The highly self-motivated liaisons who want to
work in this realm will need to have very strong
analytical, project management, and problem
solving skills, as well as the ability to work
independently at the intersection of digital data,
technology, and metadata.
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