Principle 1 (Public Good): The use of data has clear benefits for users and serves the public good
1. Public benefit
Low risk:
This research will provide a significant public good in line with best practice guidance
Average risk:
Potential to achieve public good which requires further exploration
High risk:
Negligible public good that is not in line with best practice guidance
Assessing the public good is by default highly subjective. However, when assessing the public good of your research, you should consider the definitions of public good and public interest set out in the Statistics and Registration Service Act 2007 and the Research Code of Practice and Accreditation Criteria.
It might also help you to consider:
- how beneficial would your research be to society as a whole; and
- whether it is necessary to conduct this research to realise these benefits.
See our guidance on considering and articulating public good in research projects for further information to help you in completing this section.
Back to top2. Population coverage
Low risk:
Public good applicable to entire population
Average risk:
Societal benefits might be limited to certain groups/areas
High risk:
Societal benefits will be limited to certain groups/areas
When considering the public benefit of the project, you should assess how many people would be affected. If the study is focused on a small proportion of the population, or a particular group, then:
- the research might disproportionally benefit or disadvantage a group;
- the societal impacts of the research might be limited; and
- the risk of breaching confidentiality via re-identification increases.
N/A: Omit this item if the scope of the research is specific to a particular group. However, you should justify why the research is focused on that group, and whether this, or other groups, might be adversely affected by this research.
Back to top3. Potential harm
Low risk:
Negligible harm to anyone involved, including the public
Average risk:
Identified potential harm to anyone involved that can be justified and mitigated against
High risk:
Identified potential harm that cannot be mitigated against
You should consider whether the project could cause any potential negative consequences to the public, and whether these are proportionate to the proposed public benefits of the project. Where appropriate, you should also consider whether the activities involved with conducting the research project could cause potential harm or distress to any of the individuals involved, including the research participants, the research team, or the research facilitators.
Back to top4. Biases
Low risk:
As yet, bias has not been identified in planned methods and outcomes
Average risk:
As yet, there is potential for bias/bias has been identified, but it can be justified and mitigated against
High risk:
As yet, there is potential for bias/bias has been identified, but it cannot be mitigated against
Identifying and managing bias is essential in research and, to ensure its integrity, it is important that you consider:
- the data sources used and most importantly how these are produced;
- the effect of researcher or observation bias throughout the lifecycle of the project;
- the methods and algorithms employed, their assumptions and constraints; and
- the outcomes of your research and how your research is presented.
It is equally vital that you provide mitigations for any identified bias, as illustrated by the amber and red outcomes, the lack of mitigation would result in the research reaching a tolerance level. As bias could also be identified later in the research process, it is important to keep the self-assessment updated as research projects evolve to reflect any changes.
Back to top