Authors: Alastair Dunning, Marta Teperek, Anke Versteeg, Wilma van Wezenbeek
This is a joint response from TU Delft Library to the public consultation on the draft version of the VSNU Code of Conduct for Research Integrity.
- The focus on the relationship of research data to research integrity is welcomed.
- There are some inconsistencies in good practice in data management that need to be ironed out.
- The VSNU may need to consider the implications of researchers that frequently work with companies that do not have equivalents to this code.
- Reporting on research is increasingly done via other channels than traditional journals, e.g. via platforms, preprint servers or blogs. The paragraphs on assessment and reporting are still very much focused on the traditional ways of communicating about research.
- With the upcoming GDPR, is there enough being said about the need for researchers to be increasingly aware of their own role in how they share their own personal information and what tools or applications they use and share this information with?
- The document currently does not discuss the importance of management and sharing of source code used to create, process or analyse the data. However, most research projects have now a computational element and the ability to validate and reproduce research results often relies on the availability of the supporting source code. Results of a recent survey revealed that 92% of academics use research software in their research. Therefore, if the Code of Conduct is to be relevant and applicable to the current research practices, the issues associated with managing and sharing software/code need to be addressed.
- Terms such as “data”, “research material” and “sources” need to be defined.
1. Preamble; paragraph 4 Remove “large” in “the growing importance of the way large data files are used and managed” – this is applicable to all data files, and not only to big data.
2.2.7 Many private institutions will not have subscribed to the code, and may not even have these guarantees in place. It is good that this issue is mentioned in the code, but it will have implications for universities and their researchers that work with private companies, particularly smaller companies.
2.3.9 The reference to Citizen Science seems rather cavalier, and perhaps deserves more detail. Research projects can involve thousands of citizen scientists; sometimes they may come from non-western countries, with different ethical expectations/norms etc.
2.4, footnote 7 – Students (such as masters’ students) are excluded from this code of research. But what happens if work done by masters’ student (eg preliminary data collection) is integrated into research?
4.2 Overarching comments to the section on “design” standards:
- Make extra emphasis on transparency by design and the need for planning data management and sharing from the start.
- The ethical and societal issues of fair use and access to research results need to be addressed at the design stage of research experiments. As discussed in the recent issue of Science magazine, research should aim to “ensure that those societies providing and collecting the data, particularly in resource-limited settings, benefit from their contributions”.
4.2.9 What is meant by “joint research”? Should this not apply to any funded or commissioned research?
4.2.12 The research should not be accepted if agreements outlined in point 4.2.9 are not defined and signed by all partners.
4.3.21 “To your discipline” is a bit weak. Consider “appropriate for your discipline and methodology” instead.
4.3.22 Emphasise that all data underpinning an article should be FAIR. The statement is weak at the moment.
4.4 Given that source code is often necessary for validation and reproducibility of research results, it is crucial that availability of source code used to create, process or analyse data is also discussed.
4.4.26 Given the fact that we want all contributors to be acknowledged properly (“author” is not always the right word for this), could we add “and processing” before the data?
4.4.30 Methods and protocols necessary to verify and reproduce research results should be made available.
4.4.37 Rephrase to “Always provide references and attribution when reusing research materials, including research data and code”. It is crucial that any reused research outputs are properly cited and the original authors properly attributed. In addition, the phrasing “that can be used for meta-analysis or the analysis of pooled data” was limiting the scope of the reuse and should be omitted.
4.4.40 More emphasis is needed to ensure that research data and code supporting your findings are available for scrutiny. In addition, emphasise that research outputs should be made as open as possible, as closed as necessary.
5.4 As discussed before, ensure that good practices for managing and sharing research software are also discussed.
5.4.12 Research Infrastructure is the wrong phrase. Rather: “Ensure that proper data management is embedded in the research lifecycle and that the necessary support is provided.”
5.4.13 & 5.4.14 These need clarification. At present they are contradictory (ie should data be stored permanently vs data should be stored for a period appropriate for the discipline. Again, the appeal to disciplinary practice might be incorrect, eg one can have very different data in the same discipline. “Archived in the long term” would be a better phrase than stored permanently.
5.14.15 There is an appeal to the FAIR principle earlier in the document. It should be repeated here.
5.5.17 Does this refer to commercial funders/industry partners as well?
6.3 Under “other measures”, if a retraction would be valid as measure, this should also apply to the underlying data.