Research Data Management

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What is Research Data Management? Why is there an RDM policy? What does the policy cover?

Research Data is all data generated as a result of research work while in the employment the university or the academic partners - funded or un-funded work, short-term or archival. Research Data Management is about making provision for the storage of both working data and for long-term archival of research results and associated data.

Taking the definition from the RCUK Concordat on Open Research Data:

"Research data are the evidence that underpins the answer to the research question, and can be used to validate findings regardless of its form (e.g. print, digital, or physical). These might be quantitative information or qualitative statements collected by researchers in the course of their work by experimentation, observation, modelling, interview or other methods, or information derived from existing evidence. Data may be raw or primary (e.g. direct from measurement or collection) or derived from primary data for subsequent analysis or interpretation (e.g. cleaned up or as an extract from a larger data set), or derived from existing sources where the rights may be held by others."

University Research Data Management Policy

At UHI we have developed a framework policy, based on the above concordat and research council requirements, to guide UHI researchers in their everyday work and in consideration of data that is generated as a result of research projects. Some locations already have data management policies in place, others do not; the university policy has been developed with this in mind to enable all locations to adopt the policy framework.  The policy consists of 10 policy principals and an accompanying set of guidelines to explain in more detail the reasoning behind the policy principals. Additionally, you can download a checklist, adapted from one developed at University College Dublin, for use as you consider your data management needs.

The policy framework is the beginning of the process of curating your data, not the end.  The challenge comes in implementing and maintaining these principles.

Downloads:

UHI RDM Policy and guidelines 2018

UHI RDM checklist

UHI RDM Appendices ; documents detailing the various policies and mandates that have been taken into account while shaping our policy.

Best practice in the management of research data content

Best practice in the management of research data

Best practice in the management of research data

There is an increased emphasis from all funders that research data must be as openly available as possible.  Researchers should be aware of and follow individual funder policy requirements, links are in the section 'Research Council Policies'.

  • RCUK funded researchers should read Guidance on best practice in the management of research data in addition to individual Council's policies (RC policies section) and the university policy.
  • Jisc have developed an RDM toolkit which covers the various aspects of managing data and the considerations involved.  There is also an extensive further reading list of guides, videos and courses.
Why develop an RDM plan? content

Why develop an RDM plan?

Why develop an RDM plan?

The reasons for developing plans for management of research data are summarised in the below graphic:

Effective data management example

Developing a Data Management Plan content

Developing a Data Management Plan

Developing a Data Management Plan

Sections 2 and 3 of the UHI RDM Policy and guidelines 2018 discusses your options and responsibilities in developing a DMP.

Developing a Data Management Plan (DMP)

Data Management Plans should always be developed as part of writing any funding application; indeed many funders will require a DMP as part of an application.  At the very least, an outline DMP should list all the expected data to be generated and allow for the development of a full DMP at a later stage. When creating a plan, your funder policy must take precedence.  If any part of the funder policy is at odds with University Partnership policy, you must raise this with the person responsible for research/records management at your institute or department to arrive at a resolution acceptable to all parties.

You should expect to cover subjects such as:

Planning data capture

  • Description of the data
  • Short-term data management

Description of the data

  • Format, number of files, size of data/files
  • Relations to other data
  • Processing methodologies
  • Quality assurance

Metadata content and format

  • Additional documentation about the data
  • Interpretable? Ensure lasting usability of your data

Policies for access, security, sharing and re-use

  • Backups and security
  • Consent, restrictions, copyright
  • Available for re-use
  • Attributed a re-use licence so users know how to re-use your data

Long-term storage and Management

  • Data archive location
  • Data to be curated to ensure long-term interprability
  • Long-term storage costs
Storing your research data content

Storing your research data

Storing your research data

Section 6 of the UHI RDM Policy and guidelines 2018explores storage issues.

Storage costs

Research data will typically be stored, managed and shared during a project, but may also need to be retained beyond the lifetime of a project.

Storing data costs money, as shown by the UK DATA costing tool provided by the UK Data Archive. Extended data retention periods may have some additional costs that will impact your project directly or they may be covered by the full economic costing included in your project proposal.  Invariably data retention periods will outlive projects, so you may want to consider how this will be funded as part of your data management plan (DMP) and/or in your proposal – check with your funder’s guidelines. In some cases the costs and benefits of data storage and retention decisions may need to be assessed and justified for funding purposes.

Where to store data?

Active storage - during your research

All data generated, from any project, must be deposited on institutional network storage, as soon as possible, where it can be securely backed up and preserved in its original state. This is to ensure that all University Partnership data, files and client, supplier, and other business information is properly secured and protected from accidental loss or unauthorized use.

In the first instance researchers should contact their local ICT or data management team to discuss their particular technical and data storage needs. If in doubt please contact the UHI Servicedesk who will direct you to the right person.

These solutions will enable you to:
  • Create records and attach data files for storage and access
  • Deposit your data at various points in the data life-cycle
  • Set access criteria, during and after your project either to secure or open up your data
  • Link your data to publications, grant and award information
  • Populate your profile page with relevant datasets
  • Safeguard your data through regular automatic back-up procedures
  • Describe your data

Archival storage - following publication of your research

At the end of a research project, in a timely manner and in accordance with any funding requirements, research data should be deposited in an appropriate institutional or disciplinary data repository. Long-term curation of research data secures its ongoing accuracy, authenticity, reliability and readability. It is also ensures specific funders and/or sponsor’s requirements are met.

Discipline specific repositories and funder requirements may mean that research data can be held elsewhere.  In such cases a record of any external archive should always be created within PURE, and include a link to the location of your data. Remember to consider what services you may require to meet the retention requirements applicable to your data.

You can deposit small datasets (up to 10Mb) in PURE for long-term storage.  For larger amounts of data, contact your local ICT team to discuss how to deposit your data. 

What to retain?

Deciding what to retain and what to destroy at the end of a project can be tricky. How long you retain your data will vary from discipline to discipline. You may have your own view on how long you need or want to retain data. This will be influenced by the discipline you are working in, the type of data created and whether further work or publications will be based on it.  Factors that may influence retention include:

  • Research impact
  • Academic reputation
  • Derived and linked publications
  • Statutory/legal obligations
  • University and/or Funder policy requirements (see the 'RC policies' tab)
  • Validation and testing by others

University research data policy has a requirement that all significant research data should be held for a minimum of 10 years from last use.  Where you are unsure what data might need to be held you should seek discipline specific advice from your supervisor or Head of Research as appropriate.  If you have specific questions relating to the correct access to set for your data or retention period to apply you should refer to the University Data Protection Officer.

Deposit of datasets in external repositories content

Deposit of datasets in external repositories

Deposit of datasets in external repositories

Section 9 of the UHI RDM Policy and guidelines 2018 discusses your options where you are required/expected by discipline norms to deposit data in specific repositories.

Many disciplines have an expectation of deposit of datasets in specific repositories where most data for a particular subject is generally stored.  Where this discipline norm is observed and datasets deposited outwith university systems you must ensure a record is created in PURE of where the data is available with a clear link to the dataset in the external repository.

For example, ICES has a well-established Data Centre, which manages a number of large dataset collections related to the marine environment. By maximizing the availability of data to the community at large, ICES promotes the use of these data, thereby ensuring that their maximum value can be realized. Authors are encouraged to read the ICES data submission guidelines and policy.

Alternately, PANGAEA® is a data archive that is certified by the International Council for Science (ICSU) World Data System (WDS). Data can be submitted in any format in accordance with PANGAEA’s general data submission guidelines. There are many alternative archives that may suit a particular data set, including the Dryad repository for ecological and evolutionary biology data. For gene sequence data and phylogenetic trees, deposition in GenBank or TreeBASE, respectively, is often appropriate.

Where external repositories are used you must ensure compliance with Section 9 of the

Sharing your research data content

Sharing your research data

Sharing your research data

Section 4 or the UHI RDM Policy and guidelines 2018 discusses best practise in data sharing.

Data-sharing is encouraged by all UK Funding Councils. They ask that wherever possible data and data records should be made available with as few restrictions as possible. Sharing the data created as part of your research work can:

Enhance your research profile
Promote your research
Enable data citation as well as publication
Facilitate follow-on funding
Be required by your Funder

Increasing awareness of the value of research data has led to an expectation that it will not only be used by the initial project but also shared with the wider community. The impact of data citation is also increasing in importance.

Funders may require a document that asks you to outline how you will meet their requirements in managing and/or sharing your data to be included as part of your funding applications.  They may also look for evidence of data from previous projects when considering your application, if appropriate.

The Digital Curation Centre provides a handy resource that provides links to the data policies of funders.

Where sharing data is a requirement, the time of the release can be linked to a number of different points in the data life-cycle. These can include

  • The date of creation
  • Any publication based on the data
  • The end or within a specified period after the end of the project

If there are any legal (including IP exploitation), ethical (see Ethics Policy) or confidentiality exceptions to these requirements this needs to be made clear in any data management plan, data sharing plan or data deposit form.

Roles and Responsibility

In the first instance, it is the responsibility of the Principal Investigator (PI) or lead researcher to be fully aware of the requirements of the funder with regard to data management and sharing. All members of a research team should be aware of what is required by the funder for the data created or that they are working with, i.e. secondary data.

Sharing data deposited elsewhere

You may not always deposit or store data locally. For instance, you may be working on a collaborative project where the other partner is the lead organisation. In this case you may be required to deposit data using their services and this should have been agreed at the start of any project.  Seek guidance on collaborative agreements from your local ICT contact.

Some disciplines are supported by specialist data repositories and your funder may request that you use a specialist data centre. The chosen repository will have its own mechanisms for managing access to the data. For data held at other institutions or in specialist repositories, refer to sections 7 and 9 of the university RDM policy guide.

Restrictions on sharing

The nature or source of the data you create may mean there are moral, ethical, commercial and legal reasons for not sharing or for restricting access. Please note that those datasets identified as being unsuitable for open access still require to be held safely and securely in accordance with the university RDM policy.

Maintaining access

Where you have identified that your data has long-term value or that it requires to be held for a long period of time, i.e. funder requirement, you need to consider if there are any implications for on-going access. This may include the selection of format, i.e. format needs to be durable; software used, bespoke or otherwise, where this is required to interpret the data; and the need to give permission for the data to be migrated to new formats over time. It is likely that this requirement will be included in the agreement to deposit in an external repository. If data is generated using specifically-developed software, it may be necessary to provide a copy of the software, noting operating requirements, with the data. This should all be added as an additional file to the PURE record.

Research Council policies content Online tutorial introducing best practice in RDM content

Online tutorial introducing best practice in RDM

Online tutorial introducing best practice in RDM

Acknowledgements:

This tutorial was first developed as part of the Jisc Managing Research Data Programme, it is now hosted by Bristol University.

About the online tutorial

This online tutorial is appropriate for all members of the university who undertake research with some kind of digital aspect. It will be relevant whether or not your research is funded by an external sponsor. The aim is to enable you to produce high quality data with potential for long-term use. You can work through the tutorial step-by-step using the navigation arrow on the right or the links at the bottom of each screen.

The tutorial includes several questions and the answer to each question will be revealed when you make your selection. These are designed to reinforce your understanding. Your use of the tutorial and your responses to the questions are not recorded.

This tutorial offers an elementary introduction to the key facets of research data management. It should take you about 30 minutes to complete. You will find links to more in-depth advice and guidance at the end of each section.

The bootcamp is designed introduce you to the concept of research data, what constitutes research data, and how it differs from other types of information and help you to recognise the importance of good practice in managing research data in general and to apply it to your own research.

https://data.blogs.ilrt.org/bootcamp/data/