Mike Mertens Directions for RDN day one summary

1. Directions for Research Data Management in UK
Universities
Day 1 Summary
Business case and Sustainability
&
Incentives

2. Business Case & Sustainability
In terms of the case you would make for your
organization.
1. What is the evidence of need? Where has your
institution failed to get a grant because of a poor RDM
plan?
2. Articulate the risk of not doing RDM? – eg data loss.
“our peer universities are ahead of us!”
3. Thinking about total resource – raw data and
software…
4. Scalability of the service – looking ahead, what is the
likely volume of data. Elasticity, cloud services, pace of
development required

3. Business Case and Sustainability
5. Staffing costs. How many people do you need?
Dedicated staff or part of wider staff remit. This relates
to institutional culture, there is no single ideal model
6. Cost of storage (and software)
7. disciplinary challenges – plan needs to account of
different things for difference disciplines (eg embargoes)
8. Advocacy costs – how do you get a service used after
you have it
9. Preservation – of raw and contextual data, software,
environment etc. What are the plans for review after
preservation?

4. Business Case and Sustainability
“Connect business case to the university
strategy to strengthen it.”
“Hard and soft money, revenue and
capital.”

5. Incentives
1. Reward Structures: still elitist and focused on high
impact journal publications. Can we provide other
avenues for academic reward?
2. Compliance - have we exhausted the full range of
measures to monitor and enforce compliance?
3. Possibility of academics also obtaining measurable
kudos by publishing data – more data journals, citation,
altmetrics then push into REF; publishers more
consistent regarding data deposit.
4. Make it easy! Tighter systems integration. Single
place for data deposit; support systems to farm out
data.

6. Incentives
5. Researcher RDM Champions: find, befriend,
collaborate with. An RDM Champion is worth a thousand
Research Support Staff words.
6. Quantify both amount of funding actually available that
requires researchers to re-use data, and also what re-use
*doesn’t* cost, in terms out outlay, start-up, fitting out
research proposals.
7. Build into selection of academic staff and Post-docs –
“open” is inscribed in job descriptions etc.
8. Our relationship with academic colleagues. Sometimes
difficult to get that influence – what incentives are there
for academics to speak to us? Especially future cohorts.

7. Incentives
9. HEFCE, REF and the status of research data. Bring
into scope as soon as possible.
Still a matter of sticks and carrots: but ‘stick-y carrots’ or
‘carroty sticks’?