1. Research Data Dr Aoife Coffey, Research Data Coordinator
Research & Digital Services, UCC Library

2. What is Research Data?
“……….information generated, collected or observed during a research project.
It is evidence used to support research conclusions and will go on to form part of the scholarly record.

3. Why Manage Research Data?
Research Efficiency
Data Security
Funder Requirements
Research Integrity
Reproducibility
Maximise the potential of your data
Increase dissemination
Increase visibility
Increase citations

4. FAIR

5. Dissemination of Data Or Data for Re-use
Tricky and can be quiet subtle in some cases.
But what we have to be careful of is to distinguish between a an output that is dissemination of the data and an output that is the data……. For example a website that is primarily for dissemination would be one created to advertise events……. but one that is the data would be one that is designed to gather information or host information on which a publication of thesis is based…….. Its is the primary output.
If the output can be cited by you or another author then it should be preserved as part of the scholarly record.

7. /zenodo
So in this example they used a website to inform audiences about crusades and they used Omeka to pull different types and source of information together into a new resource ……..but they realised that it wasn’t perfect they could do better. But first they archived the 1st primary output of this website and that’s a good thing because if you had been using this as a resource or wanted to find this website now you cant the link ends in a 404. there is an updated version but by archiving the first you are showing the workflow and process and maintaining the resource for people that may have referenced it. Although in an ideal world the 404 would direct you to the archived version.

10. Reproducible, Replicable)
What is FAIR?
F   +    A   +    I     =   R
Findable
Accessible
Interoperable
Reusable
(… also
Reproducible, Replicable)
DOI: /sdata

11. Structure of Data
Management Plans

13. 1. Data Collection What is the type, format and volume of data?
How will data be collected or created?
Data collection should include data descriptions .Also known as a data dictionary. Keep a record of your variable names, the normal ranges of those parameters. It is a good place to plan things like your spreadsheets and define parameters around how the data you collect is going to be recorded. If your using a spreadsheet then put in place rules and processes and assumptions. Establish a standards approach. Having naming conventions and version control .
Identify any checks that your have in place to ensure the quality of your work, things like machine calibration, controlled temperature checks, spreadsheet validation etc. most people have some sort of internal checks to ensure that work is proceeding as per the protocol or the machine your using is working as it should.
What protocol or methodology will you use?
- Are there published standards in your area?
- What equipment will be used to collect the data?
- What file format is your raw data in does it need conversion (eg .pim)?
- Do you need specific software to read it?
- What format with the raw data be in tabular, images, spectra etc.?
It is also important to document the limitations of your data any caveats or problems that you have identified.

14. 2. Documentation and Metadata
What metadata and documentation will accompany data?
What data quality control measures do you use?

15. UCC Research DataStore
3. Storage and backup [DURING]
How will data be stored and backed up during the research?
How will you take care of data security and personal data protection?
How will you manage access and security?
UCC Research DataStore

16. 4. Data Sharing and Long-term Preservation
What data? All data?
Which data should be retained, shared and/or preserved?
What is the long-term preservation plan for the dataset?
“……..underlying data”
“………any other data”

17. 4. Data Sharing and Long-term Preservation

18. 5. Responsibilities and Resources
Who will be responsible of data management?
What resources will you require to deliver your plan?
Who is responsible for data management? Ensuring the DMP is updated and reviewed? This is were you need to identify any cost associate with data management and sharing. Its difficult to put a cost on data management as it varies widely depening on the project or the discipline and even what is allowed by your funder.
Identified roles in DMP
Data ownership
Storage backup and security
Long term storage
Applying a figure to data management its actually quite difficult to do
each project is different
the discipline
depends on the type of data
depends on what resources and supports are already available
level of FAIR your aiming for
data repository requirements

19. 4. Ethics and Legal Compliance
How will you manage ethical issues and codes of conduct?
How will you manage copyright and Intellectual Property Rights (IPR) issues?

20. https://libguides.ucc.ie/researchdataservice
Data Management Plan Review for funding applications
Advice on implementation of DMPs
Advice on active data storage option in UCC
Advice on data and metadata preparation for long-term preservation
Scheduled and tailored training in data management and FAIR
Digital Badge in Responsible Conduct of Research.