iridium – ‘core’ institutional research data management plan development

Research data management plan authoring is a key part of our draft institutional RDM policy and good practice. Most RCUK funders (apart from EPSRC, currently) require a formal RDMP. NERC now require a pre- and post award RDMP.  These types of templates are available in the DMP Online system.

We wanted to write an institutional RDMP within iridium for research projects that do not have a Funder mandated template (a fair proportion, ~66% of research projects?).  This was to be as easy to complete by end user as possible (i.e. low time burden for researchers) and to be used across Faculties (disciplines) if possible.

What are the ‘essential’ RDMP questions (a ‘core plan’, Donnelley, 2012)? We reviewed several RCUK RDMP templates from different disciplines for similarities, but also distinctive and pertinent questions. Also we had project specific criteria together with good practice from DATUM RDMP template with strong actions and review (‘active plan‘) emphasis.

It was decided to pursue a post-award RDMP template approach for projects without a mandate plan, as less it was burden to write ‘core’ plans for projects that were not awarded in the end and maximise uptake. We noted need for key aspects of RDMP planning to be brought forward in pre-award processes and RIM systems (such as ethics which is already strongly monitored institutionally, but also including RDM costs/atypical data volume size (plus extended curation duration?)). For example, recommending for questions/planning to be a ‘flag’/check-box in  a ‘minimal’ (‘ultra-minimal’?) RDMP check-list in existing RIM systems/pre-award Faculty peer review process.

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iridium institutional template post-award RDMP v5 [DRAFT]

This template is for projects that DO NOT have a Funder mandated research data management (RDM) plan. Funding body requirements relating to the creation of a research data management plan are available from …

{ Our institution RIM system MyProjects contains research project administration data (see below). In the long term it would be useful to have this imported and auto-populated into a RDMP direct from RIM system. This aligns to the ‘header’ information in the DMP Online template }

Proposal Type:
Proposal Title:
Proposal Short Title:
… ….  … …. etc.

Contact details of named individuals (Role/Name/Unit):

MyProjects Owner:

Date of creation of this plan:
Plan version/supersedes:

 Aims and purpose of plan: … …

[SCOPE NOTES: Guidance on completion of this plan is available from …. ‘DCC 1.x references link to additional guidance provide by the Digital Curation Centre]

1 Introduction and Context
1.1 Introduction and Context
[DCC 1.2]: Short description of the project’s fundamental aims and purpose
[DCC 1.3.2(re-worded)]: Describe how you have considered the Newcastle University RDM institutional policy and any Faculty/research group guidelines, together with any other policy-related dependencies:
[From RC template] Document the RDM advice you have sought on planning your proposed project, including any consultation with projects using similar methods.
[DCC 10.2]: Glossary of terms
2 Data Types, Formats, Standards and Capture Methods
2.1 Data Types, Formats, Standards and Capture Methods
[SCOPE NOTE – for further guidance on ‘data’ definitions and the capture of non-digital data, please see XYZ]
[DCC 2.1]: Give a short overview description of the data being generated or reused in this research
[SCOPE NOTE – for further guidance on ‘open’ file formats, please see …]
[DCC 2.3.3(re-worded)]: Which open file formats will you use, and why?
DCC 2.3.4: What criteria and/or procedures will you use for Quality Assurance/Management?
[SCOPE NOTE – for further guidance on ‘Quality Assurance/Management, please see …]
DCC 2.5.1: Are the datasets which you will be capturing/creating self-explanatory, or understandable in isolation?
[DCC 2.5.2]: If you answered No to [DCC 2.5.1], what contextual details are needed to make the data you capture or collect meaningful?
[DCC 2.5.3]: How will you create or capture these metadata?
[DCC 2.5.4]: What form will the metadata take?
3A Ethics
3A Ethics
HAVE YOU COMPLETED A NEWCASTLE UNIVERSITY ETHICS APPLICATION?[YES] [NO] [NOT APPLICABLE] REFERENCE NUMBER:{ We already have strong RIM/institutional check points for ethics, we don’t want to duplicate information gathering, thus this section is brief. }
3B Intellectual Property
3B Intellectual Property
[SCOPE NOTE – for further guidance Intellectual Property/licensing, please see …]
[DCC 3.2.1]: Will the dataset(s) be covered by copyright or the Database Right? If so give details in DCC 3.2.2, below.
[DCC 3.2.2]: If you answered Yes to [DCC 3.2.1], Who owns the copyright and other Intellectual Property?
[DCC 3.2.3]: If you answered Yes to [DCC 3.2.1], How will the dataset be licensed?
4 Access, Data Sharing and Re-Use
4.1 Access, Data Sharing and Re-Use
[From Research Council template] Are there issues of consent, confidentiality (including commercial), anonymisation and other ethical considerations?
[From RC templates] What are the main risks to data security/ confidentiality?
[DCC 4.2.3]: Are there any embargo periods for political/commercial/patent reasons?
[DCC 4.2.4]: If you answered Yes to DCC 4.2.3, Please give details.
[DCC 4.3.1]: Which groups or organisations are likely to be interested in the data that you will create/capture?
[DCC 4.3.2]: How do you anticipate your new data being reused?
[DCC 5.3.2]: How will you implement permissions, restrictions and/or embargoes?
[DCC 4.1.1]: Are you under obligation or do you have plans to share all or part of the data you create/capture?
[DCC 4.1.3]: If you answered Yes to DCC 4.1.1, How will you make the data available?
[DCC 4.1.4]: If you answered Yes to DCC 4.1.1, When will you make the data available?
[DCC 4.1.5]: If you answered Yes to DCC 4.1.1, What is the process for gaining access to the data?
[From RC template] What will be the responsibilities of data sets users (for example as detailed in a ‘Statement of Agreement’)?
[SCOPE NOTE – for further guidance responsibilities of data sets users and ‘Statement of Agreement’ wording, please see ….]
[DCC 4.1.6]: Will access be chargeable?
5 Short-Term Storage and Data Management
5.1 Short-Term Storage and Data Management
[DCC 5.1.1]: Where (physically) will you store the data during the project’s lifetime?
[DCC 5.1.2]: What media will you use for primary storage during the project’s lifetime?
[From RC template] What is the anticipated (‘ballpark’ figure) of data volume that will be collected? Will this vary after processing?
[DCC 5.2.1]: How will you back-up the data during the project’s lifetime?
[DCC 5.2.2]: How regularly will back-ups be made?
Has the back-up process been tested and successfully validate?
Who is responsible for back-up process?
[DCC 5.3.1]: How will you manage access restrictions and data security during the project’s lifetime?
6 Deposit and Long-Term Preservation
6.1 Deposit and Long-Term Preservation
[DCC 6.1]: What is the long-term strategy for maintaining, curating and archiving the data?
[SCOPE NOTE – for further guidance curation and archiving of data sets, please see …]
[DCC 6.2.1]: Will or should data be kept beyond the life of the project?
What is your deletion policy? Will data sets be deleted? When, by whom and how will they be identified?
[DCC 6.2.2]: If you answered Yes to DCC 6.2.1, How long will or should data be kept beyond the life of the project?
[DCC 6.2.3]: If you answered Yes to DCC 6.2.1, What data centre/ repository/ archive have you identified as the long-term place of deposit?
What is the anticipated (‘ballpark’ figure) of data volume that will be archived?
[DCC 6.2.7]: Will transformations be necessary to prepare data for preservation and/or data sharing?
[SCOPE NOTE – for further guidance data set transformations, please see …]
[DCC 6.2.8]: If you answered Yes to DCC 6.2.7, what transformations will be necessary to prepare data for preservation / future re-use?
[DCC 6.3.3]: Will you include links to published materials and/or outcomes?
[SCOPE NOTE – for further guidance on include links to published materials and/or outcomes, including the Research Data Catalogue, please see …]
[DCC 6.3.4]: If you answered Yes to [DCC 6.3.3], please give details.
[DCC 6.3.5]: How will you address the issue of persistent citation?]
[SCOPE NOTE – for further guidance persistent citation, please see …]
[DCC 6.4.1]: Who will have responsibility over time for decisions about the data once the original personnel have gone?
7 Resourcing
7.1 Resourcing
[DCC 7.1]: Outline the staff/organisational roles and responsibilities for research data management
[DCC 7.2]: How will data management activities be funded during the project’s lifetime?
[DCC 7.3]: How will longer-term data management activities be funded after the project ends?
Describe how funding for RDM has been specifically been costed into funding application (where appropriate).
[SCOPE NOTE – for further guidance on costings for RDM, please see …]
8 Adherence and Review
8.1 Adherence and Review
[DCC 8.1.1]: How will adherence to this data management plan be checked or demonstrated?
[DCC 8.1.2]: Who will check this adherence?
[DCC 8.2.1]: When will this data management plan be reviewed?
[SCOPE NOTE – for further guidance on review points for for RDM plans, please see …]
[DCC 8.2.2]: Who will carry out reviews?
9 Actions Required
9.1 Actions Required
Please list actions and timelines against named individuals identified as a result of completing this RDM plan.
For example please indicate additional hardware, software and relevant technical expertise, support and training that is likely to be needed and how it will be acquired.
For any deferred or unanswered questions outline how you plan to seek advice.
Action: / Responsibility: / Review Date:-: / -: / -:-: / -: / -:
Signature Date
Print name Role/Institution
Signature Date
Print name Role/Institution
Signature Date
Print name Role/Institution



© Northumbria University School of Computing, Engineering & Information Sciences, 2012 cc: by-nc-sa DATUM DMP template

© Newcastle University, iridium project, 2012 cc: by-nc-sa

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We are currently evaluating end user acceptance of this draft plan, time required to complete and support required to assist with writing.

iridium – early findings on research data management planning (approaches, tools and writing plans)

Below is brief summary of some resources, findings and discussions on research data management plans (DMP) that have been noted along the way since the project start up. This has been collected from several activities and events such as iridium support team use of the MANTRA RDM online training package, project RDM tools assessment, together with attendance at the JISC Meeting (Disciplinary) Challenges in Research Data Management Planning Workshop and the DCC Roadshow North East.


“Research data management refers to all aspects of creating, housing, delivering, maintaining, and archiving and preserving data. It is one of the essential areas of responsible conduct of research.” – MANTRA

“Plans typically state what data will be created and how, and outline the plans for sharing and preservation, noting what is appropriate given the nature of the data and any restrictions that may need to be.” – DCC


  • to assist in planning the research data management (RDM) aspects of your research
  • to assist you in making RDM decisions
  • to identify the RDM actions required
  • to highlight areas that need further thought
  • to provide a record of decisions made and actions taken

Attribution: Northumbria University School of Computing, Engineering & Information Sciences, 2012. CC-BY-SA


The benefits of managing your data include:

  • Meeting funding body grant requirements.
  • Ensuring research integrity and reproducibility.
  • Increasing your research efficiency.
  • Ensuring research data and records are accurate, complete, authentic and reliable.
  • Saving time and resources in the long run.
  • Enhancing data security and minimising the risk of data loss.
  • Preventing duplication of effort by enabling others to use your data.
  • Complying with practices conducted in industry and commerce.


Local DMP practice/DAF survey results

From our survey (128 projects), findings were were 23% of projects have a formal research data management plan for institutional as a whole, with further 33% having a partial RDM plan (by Faculty split suggested a slightly higher proportion in line with a likely higher proportion of Research Council awards). I expect this is similar across sector? Open Exeter project reported ‘few researchers have experience of completing a data management plan ‘ from their DAF survey.


Institutional policies on DMP, some examples (see also DCC website):

Edinburgh, point 3:

Lincoln (draft), point 4:

Warwick , point 7:

Funder polices on DMP:

Various requirements at application and funded project stages. For exampe:




See also DCC mappings across 6 funder policies to generic DCC Checklist (July 2011)

Training and guidance on research data management planning

External institutional support pages guidance:

MANTRA training package covers DMP.

Advocacy for why DMP is important:

“… the role of data management for a new researcher as being one of those essential skills that you really ought to get at the same time as you learn how to handle your references, as you understand methodology, as you get to grips with the theory that is going to set the frame by which you do your research. And it sits alongside those and it’s equal to them …” – Professor Jeff Haywood, Vice Principal, CIO & Librarian, University of Edinburgh talks about the role of of data management for  PhD students and early career researchers

“… it actually gives you a really good framework and for my postgrads now I am pointing them towards that and saying hey,  you know, take a look at that because it will help you to think about how you’re going to gather your data and how you are going to look after it from  the beginning to the end of the project. It gives you a framework to deal with it rather than realizing too late that you  haven’t done some things that you should have done and  therefore you’ve made your life and perhaps actually cause problems for you with the use of data subsequently or sharing your data is made that more difficult.” – Professor Jeff Haywood, Vice Principal, CIO & Librarian, University of Edinburgh talks about the role of data management for  PhD students and early career researchers

Attribution: EDINA and Data Library, University of Edinburgh. Research Data MANTRA [online course].

Also, available as a video.

DCC resources:

Discussion on DMP approaches and reviewing the styles of questions,  format, how ‘active’ in approach

Oxford DMPOnline Project wrote on and discussed the detail of research data management plans – very interesting reading. They discussed the concept of ‘plan questions’, ‘project questions’, ‘data questions’ and common issues they found when reviewing DMPs – such as compound questions, duplicates,  and individual plan unique questions [link to table XLS]. On DMP style they noted – discursive versus concise, ‘metadata’ versus ‘data’ questions, option to add possible responses and overall gaps in DMP scope and plans that lead to quantified expected data sizes/acquisition rates (resulting in actionable identification of requirements that can be report to a central service provider, as a result of the plan).

The conclusions should be read:

“.. difficult work, since there are many possible questions ..”

“.. avoid asking ambiguous questions ..”

“.. avoid asking for the same or similar information multiple times..”

“..unique questions not covered by the DMPonline ..”

“.. all of the available question sets have drawbacks ..”

“.. in terms of comprehensiveness, the best may be the enemy of the good enough..”

“.. devise and standardize the best possible set of questions for different constituencies of user ..”

[and more …]

DMPs for different audiences – from targeted plans to template author background ‘bias’/priorities

Life-cycle stage specific: from (conception?), pre-award, post-award, to post-project.

Postgrad research project versus PI bidding for new funding.

Curator/archiver versus researcher orientated.

DMP online authoring tools or offline Word/PDF templates

Online tool has many useful advanced staging, customisation & collaboration features.

Online systems:

DMPOnline – pre-award, post-award, post-project, templates for Research Council/major funders, default templates, post-grad, etc. Features – add additional questions from DCC checklist, save, share/collaborate, copy, export to Office files, etc.


  • Introduction and Context
  • Data Types, Formats, Standards and Capture Methods
  • Ethics and Intellectual Property
  • Access, Data Sharing and Re-Use
  • Short-Term Storage and Data Management
  • Deposit and Long-Term Preservation
  • Resourcing
  • Adherence and Review

DCC website/DMPOnline

DMPOnline tools training:

DMPOnline advocated by MRC (ref 14), etc.

Institutional customisation or tailoring for local use available.
GitHub code: (Ruby on Rails/MySQL)

Offline templates (Word/PDF format):

Some users do not like online systems, are overwhelmed by array of features/customisation options and just want a ready to go familiar Office document to type into.


Shotton 20 Questions [CC:BY 3.0]

Bath 360 (postgrad-specific):

DMPTPsych(York) (postgrad?):


Wellcome Trust:

Wider DMP discussions

  • extent of pre-population of template with default institutional information to aid researcher versus reducing actual thinking/planning for RDM
  • experience in information banks of DMPs, shared pool, ‘successful’ DMP
  • DMP online tools – metadata transfer protocols between systems/integration in existing RIM systems
  • DMP training needs, online/in person, embedding with training – ‘dual service engagement‘ (i.e. Monash), see DCC ‘support researchers with DMP
  • DMP embedding in existing institutional processes, internal peer review, funder review, DMP fields (i.e. data size) resulting a RIM system flag or automatic central service trigger
  • time requirements for writing a plan – minimal plans/resources required to support/advise/review DMP
  • DMP auditing – institutional, Funding Council, etc.
  • wider use as knowledge/information base for forward institutional planning, storing DMP (or parts of ) with an  archived data set, re-use to support metadata population

JISC Research Data Management Planning Projects

Strand B: DATUM, DMPSPsych, History DMP, etc.

Next steps for iridium project:

Reporting on initial user testing of DMPOnline and other templates, authoring a local DMP template and hosting options.

iridium – reporting on existing internal and external RDM-related policy analysis mapping

A RDM-related policy analysis mapping exercise was conducted by Niall O’Loughlin with assistance from members of the iridium support team.

As a short summary, this is where we found related policies both internally within institution and externally. Shared here, as it may be useful for the wider Programme and other institutions carrying out similar activities.

Internal sources of policy mapping and guidance documents:


Code of Good Practice in Research:
Policy on Access to Research Outputs:
Policy and Procedures in the event of Academic Fraud:
Policy Regarding the Participation of Volunteers in Research Projects:
Policy Statement on Intellectual Property:
Policy on Intellectual Property rights for Research Students and Visiting Workers:
Research Policy on Intellectual Property and Research Studentships:
Record Management Policy Document:
Records Retention Schedule:
Process for the Initiation, Development, Sign-off and Subsequent Management of MoUs and Other Types of Agreement Policy on Access to Research Outputs
Ethics Governance:

Links to Research Council Guidance: Links to professional Organisations & codes of Practice:

Links to legislation:
University Policy and Procedure for Investigating Allegations of Research Misconduct

Policies overview:


Concordat to Support the Career Development of Researchers:
Policy on Public Interest Disclosure (whistle blowing):

Data Assurance Policy and Procedure:

Freedom of Information Act:
Information Security Policy:
Information Security procedures:
Information Security Guidelines:

University Safety Policy:

Staff Policies:

Two iridium support team members took the draft policy principles and code of good practice document and looked at these in relation to above policies/guidance documents, mapping for any potential conflicts, key phrase matching and highlighting any further references. This highlighted the following existing guidance documentation/references:

  • CASE Award Students/Studentships/Self-funded Students
  • Policy and Procedure for Ethical Review (which includes reference to the NHS requirements)
  • Preliminary Ethical Assessment Forms/full ethical review, Research Ethics Committee, plus the Trust R&D Approvals Committee
  • Pricing policy and strategy for research, consultancy and other services rendered

A further iridium support team member took on some focused tasks looking at data security polices and examples of local policy implementation.

External sources of policy mapping and guidance documents:

Key Legislation:

Freedom of Information Act (2000)

The Data Protection Act (1998)

The Computer Misuse Act (1990)

External research funder policies:

This was made easier by the very useful guidance provided by the DCC website resources:

As an example, the MRC has a specific guidance:

Also, the LSHTM (thanks to Gareth Knight [@gknight2000]) have done some recent work for medical research funders on this and shared (with a CC licence!):

While, specifically, NERC have recently updated guidance: (see also blog at DCC)

External institutional RDM published policies:

Again, this was made easier by the DCC website resources:

New institutional policies/roadmaps are frequently being released in draft and final versions now, including recent ones.

External journal policies on research data sharing:

A recently awarded JISC project ‘Journal Research Data Policy Bank (JoRD) ‘ is looking at these issues (thanks to @simonhodson99 for linksvia JISCMRD JISCMAIL list). Early outputs:

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