rdm basics

Apr 19, 2023

RDM basics

Session 1.2

RDMRose: Research Data Management for LISSession 1 Introductions, RDM, and the role of LISSession 1.2 RDM basics

Learning material produced by RDMRose http://www.sheffield.ac.uk/is/research/projects/rdmrose

Apr 19, 2023

Learning outcomes

• At the end of this session you will be able to:– Discuss the definition of “Research Data

Management” and “Digital curation”– Describe the strategic context within which RDM

has appeared on the agenda and the key drivers and issues for researchers


Apr 19, 2023 Learning material produced by RDMRose http://www.sheffield.ac.uk/is/research/projects/rdmrose

Session overview

• RDM definition• Digital curation definition• Context• Incentives• Issues for researchers


ACTIVITY 1.2.1What words to you associate with RDM?


Activity 1.2.1 What words do you associate with RDM?


Some words that have been suggested

• Storage• Preservation• Reuse• Accessibility• Data Management

Plans

• Unknown• Forbidding• Exciting• Boring• Technical


RDM definition

• “Research data management concerns the organisation of data, from its entry to the research cycle through to the dissemination and archiving of valuable results.” (Whyte & Tedds, 2011)


Digital curation definition

• “Digital curation, broadly interpreted, is about maintaining and adding value to a trusted body of digital information for current and future use.” (DCC, n.d. b, p. 6)– Linking content– Managing digital material from the point it is created– Destruction

• Beyond archiving and preservation• “Digital curation is concerned with actively managing data for as long as it

continues to be of scholarly, scientific, research and/or administrative interest, with the aim of supporting reproducibility of results, reuse of and adding value to that data, managing it from its point of creation until it is determined not to be useful, and ensuring its long-term accessibility and preservation, authenticity and integrity.” (DCC, n.d. b, p. 6)


Context

• “Data deluge”– eScience, cyberscholarship, e-research– Collaborations– Multiple forms of complex data– Huge cost of research

• National policy– Data Protection Act, Freedom Of Information Act

compliance• Funders’ mandates


Position of the funders

• Funders’ mandates– A key landmark for the UK was EPSRC’s

requirement that every institution seeking funding needed a roadmap to compliance by 1st May 2012 and actual compliance by 1st May 2015.

– NSF requirements key in USA


Institutional policy

Whyte & Tedds (2011) identify that institutional policy is likely to• “Identify areas of responsibility for the institution and for

researchers• Commit the university to develop appropriate guidelines, training

and support, including mechanisms and services for storage and backup

• Support deployment of data repositories and/ or mechanisms for registering metadata about research data

• Recognise that management and curation of research data requires cooperation and coordination with research funders, and with existing national and international providers of data services and subject-based repositories”

Apr 19, 2023

Incentive 1: Direct benefits to scientist

• Improve the quality of research data• Provide access to reliable working data• Allow conclusions to be validated externally• Apply good record-keeping standards to data capture including in lab and field

electronic notebooks, which enables scientists to draw conclusions from reliable and trustworthy working research data

• Enable large amounts of data to be analysed and developed across different locations by maintaining consistency in working practices and interpretations

• Manage relationships between different versions of dynamic or evolving datasets, and facilitates linkage with other related research and between primary, secondary and tertiary data

• Ensure valuable knowledge and data originating from short-term research projects does not become obsolete or inaccessible when funding expires

• Allow data sets to be combined in new and innovative ways



Incentive 2: ‘Public good’ obligations

• Demonstrate Return on Investment• Open Access


Incentive 3: Compliance reasons

• Compliance with funding body requirements• Legal requirements• Publishers’ requirements


The RDM agenda

• There may also be a data security incentive.• Beagrie and Pink (2012) analyse the benefits

of RDM to different stakeholders• It is not clear how far these different

incentives are temporarily or permanently aligned.


Issues for researchers

• The nature of data• How important is it relative

to doing the research; projects only get short term funding

• Authority structures in universities; the social organisation of research

• Is infrastructure available?• Lack of RDM knowledge and

skills• No checking of compliance

• Legal, ethical and commercial motives

• Desire to keep control over data

• Informal sharing practices already exist

• Lack of reuse culture


ACTIVITY 1.2.2The researcher’s viewpoint


Activity 1.2.2 The researcher’s viewpoint

• Which issues with RDM are the most critical barriers in your opinion?

• Which of the arguments in favour of RDM would play best with researchers?


SOURCES AND REFERENCES


Sources

• Slides incentives 1-3 are based on DCC (n.d. a).


References• Beagrie, N. and Pink, C. (2012). Benefits from Research Data

Management in Universities for Industry and Not-for-Profit Research Partners. Charles Beagrie Ltd and University of Bath. Retrieved from http://opus.bath.ac.uk/32509/ .

• DCC (n.d. a). DC101: Incentives for digital curation. Edinburgh: Digital Curation Centre. Retrieved from http://www.dcc.ac.uk/webfm_send/433.

• DCC (n.d. b). DC 101: What is digital curation? Edinburgh: Digital Curation Centre. Retrieved from http://www.dcc.ac.uk/webfm_send/437.

• Whyte, A., & Tedds, J. (2011). Making the case for Research Data Management. Edinburgh: Digital Curation Centre. Retrieved from http://www.dcc.ac.uk/webfm_send/487.

http://opus.bath.ac.uk/32509/

http://opus.bath.ac.uk/32509/

http://www.dcc.ac.uk/webfm_send/433



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