Publishing research data

Traditionally publishing the results of your research in a journal article or book was the main way to share the findings of your research. However, it is increasingly best practice, and often required by research funders, for researchers to publish the final set of data that underpins the findings of their research. This page will give you some brief guidance on what to consider when publishing your data - the ideal time to consider these questions is when writing a Data Management Plan in the preparatory stage of a research project.

Contact the Scholarly Communications Team for help with publishing research data

See the page above for all the Research Data Management support services available to Oxford Brookes researchers

Principles

Below are some questions from the Digital Curation Centre (2013) for you to consider about publishing your data.

Sharing

  • How will potential users find out about your data?
  • With whom will you share the data, and under what conditions?
  • Will you share/publish data via a repository, handle requests directly or use another mechanism?
  • When will you make the data available?
  • Will you get a persistent identifier for your data? (e.g. a DOI)

Restrictions

  • What action will you take to overcome or minimise restrictions on other people re-using your data?
  • For how long do you need exclusive use of the data and why?
  • Will your data need a sharing agreement/publishing licence (or equivalent)? 

Digital Curation Centre (2013) Checklist for a Data Management Plan. v.4.0. Edinburgh: Digital Curation Centre.

Metadata

For other researchers to correctly interpret and effectively reuse your data you will need to provide information about it - this is called metadata. Ideally the metadata will be recorded in a standardised format (e.g. Dublin Core) that is easily understood and communicated. However, it may sometimes be necessary to create a 'readme' file to provide this information to potential users of your research data. Below is some advice on writing a good quality 'readme' file.

Best Practices

  • Create one 'readme' file for each data file, whenever possible. Name the 'readme' so that it is easily associated with the data file(s) it describes.
  • Write your 'readme' document as a plain text file.
  • Format multiple 'readme' files identically.
  • Use standardized date formats (e.g. YYYYMMDD or YYYYMMDDThhmmss).
  • Follow the scientific conventions for your discipline for taxonomic, geospatial and geologic names and keywords.

Recommended minimum content

General information

  • Provide a title for the dataset
  • Name/institution/address/email information for Principal investigator (or person responsible for collecting the data)
  • Date of data collection (can be a single date, or a range)
  • Information about geographic location of data collection

Data and file overview

  • For each filename, a short description of what data it contains
  • Date that the file was created

Sharing and access information

  • Licenses or restrictions placed on the data

Methodological information

  • Description of methods for data collection or generation
  • Description of methods used for data processing (describe how the data were generated from the raw or collected data)

Data-specific information (repeat this section as needed for each dataset, or file, as appropriate)

  • Variable list, including full names and definitions (spell out abbreviated words) of column headings for tabular data
  • Units of measurement
  • Definitions for codes or symbols used to record missing data

Research Data Management Group (no date) Guide to writing "readme" style metadata. Cornell University.

Choosing a repository

The best place to deposit your data is in a trustworthy repository where the researchers in your field or discipline are most likely to find it.

RADAR

You can use Oxford Brookes' institutional repository RADAR to publish your data. The intention of RADAR is to freely share your data with other researchers and the general public - if you would like to archive your data, i.e. store it for the long term, please consider using the Arkivum service offered by IT Services. Some of the benefits of publishing your data through RADAR include the following:

  • Assign your data a DOI (Digital Object Identifier) to aid long-term discovery and for citing in associated publications (e.g. journal articles that are informed by the dataset).
  • Deposit your data in RADAR's research data collection, though for large or continually growing datasets we can create entirely separate collections (e.g. the Sonic Art Research Unit collection).
  • License your data with an internationally recognised Creative Commons license.

Other repositories

You can also choose to deposit your research data in a subject-specific national or international data service or domain repository - this is a good option to choose if you know of a repository that is commonly used by researchers in your discipline. If you choose this option please consider the following questions first:

  • Who will own the Intellectual Property of the data once it is deposited?
  • Is there a financial implication to depositing your data with the data service for the short or long term?
  • How sustainable is the business model of the data service?
  • What will happen to your data if the service is bought by a third party?
  • Will the data service assign your data a unique and persistent identifier (e.g. DOI) to aid long-term discovery?