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Research Data Management: Data Sharing

Bringing together University resources and services to facilitate researchers in the production of high quality data.

The Importance of Sharing

Researchers devote a large amount of physical and intellectual effort to collect, manage, collate, and analyse their data before publishing their results. Many of these datasets have significant value beyond the usage for the original research, and sharing the data can be seen as beneficial in a number of ways:

Research integrity and reproducibility
Publishing research data and citing its location in published research papers allows other to replicate, validate or build upon your results thus improving the scientific record by encouraging scientific enquiry and debate. Openly sharing research data also encourages the improvement and validation of research methods and minimises the need for data re-collection.

Funder requirements
A growing number of funding bodies and research councils have adopted research data sharing policies and mandate or encourage researchers to share data and outputs to avoid duplication of effort and reduce data collection costs. Including data sharing plans in a funding bid can confer a funding application advantage.

Journal publisher requirements
A growing number of journal publishers require data that underpin research findings to be published in open access repositories when manuscripts are submitted.

Others who re-use your data and cite it in their own research help to raise interest in your research and increase your impact within your field and beyond. “Open” data leads to increased citations of the data itself, and of associated papers.


Data sharing may lead to new collaborations between data users and data creators. Sharing data can often lead to improvements such as corrections in the documentation, or combination or comparison of datasets leading to new information.

Data created for one research purpose may be re-invented or re-interpreted for future unrelated research and into contexts not currently envisaged. Data sharing and re-use across borders and disciplines can also promote innovation by potential new data users.

Preservation for your own future use
Some research data will be unique and cannot be replaced if destroyed or lost. By preparing your data for sharing with others, you will benefit by being able to identify, retrieve, and understand the data yourself after you have lost familiarity with it, perhaps several years hence. Sharing via a repository will mean that the repository will look after and preserve your data into the future, even after technology becomes obsolete.

Your data may be useful for students or new generations of researchers to learn how to collect and analyse similar types of data. Attempting to reproduce published results by analysing an existing dataset is an excellent way for students to learn methods.

To Share or Not to Share

Not all of the data you have collected will be suitable or appropriate for sharing. The following need to be considered:

  • What is and isn’t important to keep?
    • If you work on a collaborative project the appraisal should be conducted by the whole group, led by the PI. 
  • Do your data have commercial value or are the basis for potentially valuable patents
  • Is there an embargo period in order to allow time to assimilate, develop and publish the research hypothesis?
  • Is sensitive personal information included in your research data? You may need to anonymise  your data prior to depositing to an archive.
  • Are there any ethical issues around releasing data? 

Help With Costs

The anticipated costs of depositing research data may be included in a grant application. Consider including costs relating to the preparation of data for deposit and ingestion, data storage, ongoing digital preservation and curation after the project, etc.

Tracking Retractions Blog / Database

How to Share Your Data

Forward planning
Enabling others to re-use your data will mean planning for this from the start of your research project. You will need to think critically of how research data can be shared, what might limit or prohibit data sharing (e.g. consent forms, confidentiality concerns), and whether any steps can be taken to remove such limitations. Refer to our Checklist which will point you to key matters to consider in managing and sharing your data.

Deposit your data with a data repository / archive
There are many services available, depending on your research area. Each repository will have different policies and they may charge you to deposit your data. If you are planning to use one of these repositories it is important that you include such charges in your funding bid. In addition to depositing your data you will also need to include your supporting documentation and metadata in order to help others make sense of your data.

You will also need to use a data license to clearly indicate how you expect the data to be used.

Where to deposit data

Ideally your data should be desposited in a disciplinary specific repository to facilitate discoverability and preservation of the data.

If no disciplinary repository exists for your discipline consider depositing data in a multidisciplinary repository:

Irish repositories include:

Submit your data to a journal

“The intent of a data paper is to offer descriptive information on the related dataset(s) focusing on data collection, distinguishing features, access and potential reuse rather than on data processing and analysis.”

Newman Paul; Corke Peter (2009). "Data papers — peer reviewed publication of high quality data sets". International Journal of Robotics Research. 28 (5): 587–587. doi:10.1177/0278364909104283.

Below are some examples of Data Journals, however there are many more:

Publishing and Sharing Sensitive Data

If you are conducting a clinical study, or any study involving human participants, and wish to make the data available at the end of the study then you need to consider from the very beginning  when designing the study. You will need to ensure you are asking for informed consent to share the data. Clinical research in particular is highly regulated and requires extensive approval before it can be made available. Contact the UCD Office of Research Ethics for further advice.


By SangyaPundir (Own work) [CC BY-SA 4.0 (], via Wikimedia CommonsBy SangyaPundir CC BY-SA 4.0

The FAIR Data Principles are a set of community developed guiding principles for making data Findable, Accessible, Interoperable, and Re-usable. Below we list resources that will help you make your data FAIR.

  • Findable – Assign persistent IDs, provide rich metadata, register in a searchable resource,...
  • Accessible – Retrievable by their ID using a standard protocol, allows for authentication/authorization, metadata remain accessible even if data aren’t...
  • Interoperable – Use standard vocabularies, qualified references, shared and broadly applicable language for knowledge representation...
  • Reusable – Rich, accurate metadata, clear licences, provenance, use of community standards...

Guidance on sharing research data

Sharing Social Research Data in Ireland

ICPSR's Guide to Social Science Data Preparation and Archiving