Principle 6 (Transparency): The access, use and sharing of data is transparent, and is communicated clearly and accessibly to the public
20. Public access to outcomes
Low risk:
Research outcomes are, or will be, openly available to the public
Average risk:
Don’t know, or unsure if research outcomes will be openly available to the public
High risk:
Research outcomes are not, or will not be, openly available to the public
The use of data produced by the public offers an exciting opportunity to the statistical community but comes with a responsibility to be transparent to the public in the way we use their data. It is imperative that we share the research outcomes with the public and ensure that they remain openly accessible. This transparency principle is enshrined in the Code of Practice for Statistics and Research Code of Practice and Accreditation Criteria, and is also set out in the UK Research and Innovation’s Open Access Policy.
Back to top21. Sharing of methods and tools
Low risk:
Both methods and/or tools are, or will be, made widely available to the public
Average risk:
Don’t know, or unsure if methods and tools will be available to the public
High risk:
Both methods and tools are not, or will not be, made widely available to the public, or will only be shared internally
In parallel with research outcomes, researchers often develop new methods and tools to enable future research to be more effective. Where appropriate, it is good practice for researchers to make these new methods and tools available for others to use, as this enables wider research impact and innovation throughout the research community.
N/A: There are some cases where researchers may not be able to share these tools and methods:
- Firstly, when reverse engineering the tools or method could compromise the confidentiality of the statistical outputs produced; and
- Secondly, when there is a legal agreement in place that prevents us from doing so, for example tools and methods are produced in partnership with a third party which retains intellectual property rights.
In these instances, this item can be omitted.
Back to top22. Data curation and re-use
Low risk:
Data will be curated based on data retention policies and it will be available for re-use by the wider research community
Average risk:
It is unsure whether data will be available for re-use, and/or data retention policies are not known/unclear
High risk:
Data will not be available for re-use, or data retention policies are not in place
You should select an appropriate retention period for the data to ensure that your research can be reproduced and validated. Due to the significant costs and burden involved with re-acquiring and preparing data, we encourage you to re-use raw and linked datasets when possible. You should remain vigilant of the sensitivity of identifiable datasets to be retained when selecting retention periods and data re-use.
N/A: Omit this item when data sharing agreements or original consent does not allow re-use of the dataset.
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