Research Data Management

Preserving and Sharing

The Research Data Management Policy at the University of Galway states that

Research data of future historical interest, and all research data that represent records of the University, including data that substantiate research findings, will be offered and assessed for deposit and retention in an appropriate national or international data service or domain repository, or a University repository.
Exclusive rights to reuse or publish research data should not be handed over to commercial publishers or agents without retaining the rights to make the data openly available for re-use, unless this is a condition of funding. An exemption from this must be agreed with the Technology Transfer Office.

Reasons for sharing data

Impact & longevity: Your data may be cited by others. Open publications and data receive more citations, over longer periods
Compliance: Funders, publishers and institutions may require that you share your data
Transparency & quality: Your findings can be replicated and compared with other studies
Collaboration: creates opportunities for follow on research and collaboration
Re-use: Your data can be used in novel ways. Data sharing facilitates re-use of your data for future / follow-on research and discovery as data collection can be funded / collected once, and used many times for a variety of purposes
Efficiency: Data sharing is good research practice!

There may be reasons for not sharing your data e.g. privacy and confidentiality issues, commercial value of the data. Horizon 2020 has coined the phrase “As open as possible, as closed as necessary.”

If you are unable to publicly share your data, consider the possibility that you may wish to make your data available internally to future researchers to facilitate follow-on research, and/or to create a metadata record in your chosen archives or repository. A metadata record will describe your data and aid others in knowing about it. In order to ensure this can happen you will need to manage your data.

Ref: CONUL Research Group (2018). Where to submit data: CONUL Information Sheet.

Legal and Ethical considerations

Some data may not be suitable for sharing. There may be legal or ethical factors to consider e.g., consent, privacy, copyright or commercial considerations.

For further information read the DCCs (Digital Curation Centre) guide on How to appraise and select research data for curation

Data deposits should be accompanied by supporting documentation and metadata to help others make sense of your data.A data license to indicate how you expect the data to be used is also necessary. For further information Information read the DCCs (Digital Curation Centre) guide on How to License Research Data

Restricting access to your research data

There are many reason why access to research data may need to be restricted. Some examples are provided below

“We intend to make a patent application, and must avoid prior disclosure.”

“Don’t want to make locations of members of endangered species available to poachers.”

“The research data are confidential because of the arrangement my research group has made with the commercial partner sponsoring our research.”

“My data form part of a long-term study upon which my research group is entirely reliant for its on-going research publications and academic reputation. We only share this with trusted colleagues.”

Sensitive Data

A Guide for Researchers from OpenAIRE: How to deal with sensitive data: Learn how to preserve your sensitive data safely

Attribution and credit for research outputs also applies to research data. Data citation provides the information necessary to locate, attribute and access the research data, also enabling it to verified or reused.

Benefits of data citation

Facilitates a link from publications to underlying data
Ensures recognition of scholarly effort
Increases transparency of research
Enables the measurement of impact
Facilitates access to and re-use of data

Citations should include a Persistent Identifier

ORCID (for people)
DOI (Digital Object Identifier) unique, alphanumeric string assigned by a registration agency to identify content and provide a persistent link to its location. DOIs may be assigned to any item of intellectual property that is defined by structured metadata
ARK (Archival Resource Key) an URL designed to support long-term access to information objects. An ARK can refer to digital, physical, or intangible objects or living beings and groups

ADVICE: Use the Library's DOI service to obtain a DOI for a dataset.

A dataset citation should include where applicable:

Author/Principal Investigator/Data Creator
Publication date/Release Date, for a completed dataset
Title of Data Source – formal title of the dataset
Version/Edition Number – the version of the dataset used in the study
Format of the Data – physical format of the data
Publisher
Resource type
Persistent Identifier - such as a DOI
Location or Identifier – a persistent URL where the dataset may be accessed e.g., Digital Object Identifiers (DOI), Handles, Archival Resource Key (ARK), etc.
Access Date and Time – when data is accessed online
Subset of Data Used – description based on organization of the larger dataset
Editor or Contributor – reference to a person who compiled data, or performed value-added functions
Publication Place – city and state and country of the distributor of the data
Data within a Larger Work – refers to the use of data in a compilation or a data supplement (such as published in a peer-reviewed paper)

See also guidelines provided by the Data Curation Centre

Learn more about ...

Data citation principles

FORCE 11 a community of scholars, librarians, archivists, publishers and research funders that has arisen organically to help facilitate the change toward improved knowledge creation and sharing

Software citation principles

Smith AM, Katz DS, Nieme KE, FORCE11 Software Citation Working Group.(2016) Software citation principles. PeerJ Computer Science 2:e86 https ://doi.org/10.7717/peerj-cs.8

Data repositories or archives

A data repository allows researchers to upload and publish their data, thereby making the data available for other researchers to re-use. Similarly, a data archive allows users to deposit and publish data but will generally offer greater levels of curation to community standards, have specific guidelines on what data can be deposited and is more likely to offer long-term preservation as a service. Sometimes the terms data repositories and data archives are used interchangeably. A data repository or archive will provide services such as:

Persistent identifier such as a “digital object identifier” or DOI; the presence of a DOI facilitates discoverability and citeability
Assistance with metadata provision e.g. through the use of a template
Allow you to apply a licence to your data
Aid compliance with the FAIR data principles (data that are Findable, Accessible, Interoperable, and Reusable) as data are published online with appropriate metadata and are assigned a persistent identifier, see Jones, Sarah, & Grootveld, Marjan. (2017, November). How FAIR are your data?. Zenodo. http://doi.org/10.5281/zenodo.1065991
Accept a wide range of data types
Long-term access and, in some cases, long-term preservation
Offer useful search, navigation and visualisation functionality
Reach a wider audience of potential users
Manage requests for data on your behalf

When to select a data repository?

Choose early so that you can familiarise yourself with the repository’s requirements. Requirements may include:

depositing in certain file formats
using a specific metadata standard
inclusion of documentation to help describe your data.

Understanding such requirements will enable you to design your data collection materials for easier metadata and documentation creation.

Initial questions

Has a data repository been specified by my funder? e.g.
- NERC Data Centre for research funded by the UK’s Natural Environment Research Council

Has a data repository been specified by my publisher? e.g.
- SpringerNature via their recommended repositories
- PLOS recommended data repositories
- Scientific Data recommended data repositories

Is there a disciplinary-specific community-recognised data repository I can submit my data to, thereby helping to preserve my data according to recognised standards in my discipline? e.g.

How to select a data repository

Ask:

Is it reputable? Is it listed in Re3data thereby meeting their conditions of inclusion?
Is it appropriate to my discipline?
Will it take the data you want to deposit?
Is there a size limit?
Does it provide a DOI / persistent identifier?
Does it provide guidance on how the data should be cited?
Does it provide access control, where necessary, for your research data?
Does it ensure long-term preservation / curation?
Does it provide expert help with e.g. metadata provision, curation?
Is there a charge?

Other questions may pertain depending on your requirements. For more information see the UK’s Digital Curation Centre’s checklist

Locate a data repository

Some universities have their own data repositories that offer the facility for researchers to deposit, share and licence their data resources for discovery and use by others. There are more than 600 discipline-specific data repositories worldwide with community specific standards. They may also be called data centres or archives.

re3data.org (Registry of Research Data Repositories) is the primary place to locate a data repository. You can search it by specific research discipline and then filter by access categories, data usage licenses, whether the repository gives the data a persistent identifier etc.

Re3data uses a series of symbols to indicate key services e.g.

To be registered in re3data.org a research data repository must:
- be run by a legal entity, such as a sustainable institution (e.g. library, university)
- clarify access conditions to the data and repository as well as the terms of use
- have focus on research data

See also FAIRsharing.org another curated registry to help you select a suitable disciplinary repository

Discipline-specific repositories have the expertise and resources to deal with particular types of data. They have different policies and may charge for their services.

Research Data Management

Preserving and Sharing

Sensitive Data

A Guide for Researchers from OpenAIRE: How to deal with sensitive data: Learn how to preserve your sensitive data safely

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