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As the demand increases for a standardised approach to responsible research and innovation, Susanne Hollman (University of Potsdam and SB Science Management UG, both Germany) discusses the need for standardising life science research and implementing minimal quality measures, before considering the impact of standardisation on open research.

I am a biochemist and chemist by training and hold a PhD in biochemistry (synthetic biology). I have worked as a researcher in various universities and companies, including the pharmaceutical industry where I faced the first-time quality management and SOPs issues. Due to my education at first, I was not aware of the need and benefits of these measures, but it became fast understandable and finally entered my daily workflow.

While at university, I further continued holding and implementing minimal standardisation measures but realised that my academic environment was not ready to do so too. Therefore, I started to promote standardisation and the establishment of minimal quality measures whenever possible and was successfully granted international and national grants aiming to enable and harmonise standardisation efforts in my field. Due to my involvement with those projects I was appointed member of the Deutsches Institut für Normung (DIN) working group in biotechnology and its international mirror committee, ISO / TC 276 Biotechnology.

Beyond my work at the university, in 2014 I founded my company and started to work as a Consultant, Coach and Trainer in the context of scientific management. Beyond these service activities, I conduct research in the context of Responsible Research and Innovation (RRI), where standardisation play a key role, especially with open science and innovation transfer. 

Find out more with my LinkedIn profile >>

RRI is a new principle for conducting and evaluating research, development, and innovation. Key issues include ethics, open access, gender and equality, public engagement and participation, governance and institutions, and education. The implementation of RRI in the research ecosystem faces several barriers at individual, institutional and administrative levels. Looking at the institutional and individual levels, we see that the culture and existing structures of our educational and research systems and its evaluation are often inadequate to enable the individuals to understand and address them accordingly. This limits a broad implementation of the RRI principles in daily practice.

In our company, we focus on the development of new strategies to implement RRI in the research ecosystem. Based on the current status across Europe and within projects we are involved in, we develop training concepts for implementing RRI e.g., via educational curricula, but we also develop recommendations for institutional change and participatory approaches in multi-stakeholder research projects.

The need for standardisation in life science research

The motivation to write the article is a result from work of the Cost Action CHARME I headed up (COST Action CA15110 “Harmonising standardisation strategies to increase efficiency and competitiveness of European life-science research“). The Action aimed to identify needs and gaps, and to join forces with other initiatives and organizations to avoid duplication and overlap of standardization activities within the life-science communities.  

In the beginning of the Action, we first collected information about the current status quo in respect to standardisation within the participating stakeholders. We realized that at the metadata level, considerable efforts in standardisation have already been made (FAIR principles, BioSharing, NIH Common Data Elements etc.). However, FAIR data principles mainly address the metadata levels and data structures, whereas with raw data, comparable fundamental efforts are still fragmented and, in some cases, completely missing. This is still a bottleneck in life science research because of missing common and unified ‘Formal Quality Systems’ that should ensure quality assurance and reproducibility of research data.

We also identified huge differences between disciplines and academic structures within our participating stakeholders. Looking at the institutional and individual levels, we saw that the culture and structures of educational and research systems are often inadequate in respect to ensure the implementation of full FAIR principles and quality management.

Looking at the cross-European level, it became visible that low-income countries were still more penalised by the lack of adequate infrastructures and resources compared to participating high-income countries.

At a systemic level within the European Union, we realised that the priorities for standardisation in Europe sets out specific objectives and policies for European standards and standardisation deliverables, but that life science research is not sufficiently taken into consideration within this strategy, which currently focuses almost on Artificial Intelligence (AI) and its connected areas. With our Opinion Article, we wanted to draw attention to the existing gaps in the discussion for standardisation in order to ensure that the demands within life science research will be included in  future policies and measures of the European strategy on standardisation.

A holistic approach to standardising life science research

The problem of standardisation is complex and should not be viewed or tackled in isolation, but holistically. The catalogue of recommendations described, therefore reflects and takes into consideration all stakeholder levels involved in the process.

At the individual level: new European policies, strategies and solutions developed in this field remain rather unknown to the majority of academic researchers, whereas their knowledge is essential to align the life science research life cycle to the pressing request about the application of fairness and open access principles properly. Here, researchers need to be informed and trained in quality management and the use and development of standards to overcome current limitations in life-science research in respect to efficient generation and integration of information.

But we also see that the institutional levels are equally challenged: For example, at the institutional level outdated curricula need to be revised, rules need to be adapted, structures need to be (re)created etc. Here, a particularly important element is a revision of institutional recognition systems, which unfortunately still focus, beyond others, on the quantity of publications but do not consider their quality.

There is no question that the next higher level needs to support these measures accordingly through funding measures.

Finally, activities need to be harmonised and regulated across all working levels, communities and finally countries at systemic level. Consequently, this means that all stakeholders involved must carefully listen and communicate to each other to find solutions for both, bottom up and top-down measures.

I would particularly like to stress, that we do not want to give the impression that there are not enough initiatives, platforms, programs etc. but we feel that there are too many poorly communicated, accessible or connected activities and interests which strongly need to become harmonised.

Only through intensive exchange both within the scientific community and with various stakeholder groups and industry, can meaningful solutions be realised and implemented. Good networking of standardisation efforts, not only from Europe but around the world, includes the interaction with existing frameworks for agreement on nomenclature and international adoption.

Overcoming key challenges

As I mentioned before, it is important to view the whole picture. Therefore, all stakeholder groups involved in the process must cooperate in the different phases. Therefore, it is mandatory to connect the field of academic life science research with AI, industry, standardisation organisations/initiatives and with ongoing initiatives and politics. Everyone must have access to information at all times and relevant actors should be involved to ensure acceptance and thus, success.

Unfortunately, because the existing ranking systems, institutions are focussing to the on the track record of researchers (number of publications and citations) but not on the quality of produced data and the impact of the research results on the (scientific) community. Here, we see the strong necessary to change the reward systems from quantity to quality of data.

Owing to the current, dynamic developments around the different standardisation measures a situation has now been created that urgently needs the pooling, networking, and harmonisation of the various activities in order to be able to achieve optimal results. This can only be achieved through continuous consultation, elucidation, involvement of all working levels and transparency in the activities.

In the academic environment, it is still not common practice to work with quality management systems, standards, and SOPs. Often, these issues are considered to limit research freedom resulting in a strong resistance of a large part of the scientific community to adopt standards and FAIR principles. Here, University rankings are above all an important political instrument. Unfortunately, because the existing ranking systems, institutions are focussing to the on the track record of researchers (number of publications and citations) but not on the quality of produced data and the impact of the research results on the (scientific) community. Here, we see the strong necessary to change the reward systems from quantity to quality of data.

The pressure to publish as much as possible in the most respected journals is a major problem (for young) scientist in particular. A change of the ranking criteria might also remove this pressure and will allow them to become more sensitive to, and invest more time into quality measures.

Furthermore, researchers need to be trained in quality management and the use and development of standards to overcome current limitations in life-science research in respect to efficient generation and integration of information. Hence, incentives and investments must be made to increase the number of experts and to establish a uniform training across all disciplines.

Another challenge is that some institutions insist on introducing their own systems that do not always harmonise with the established systems. Here, common and uniform cross-national rules would help.

A movement towards open research

Currently, many efforts and investments need to be done either to reproduce or reuse data. The implementation of standardisation and quality measures along the pipeline of acquisition data would facilitate the transition towards open science.

The measures we propose contribute to speed up this overall process, especially because it reflects and includes demands from all working levels.

I welcome measures increasing openness and transparency at all levels connected to research. The open discussion of publications undoubtedly increases the transparency of the review process, which is often criticized. I think that transparency here requires authors and reviewers to communicate openly and respectfully with each other. I also believe that the number of publications based on insufficient study design or research data, as we have seen in the past in context with COVID-19, might decrease or become visible faster when discussed openly. If standardization would be taken into account as a criterion in the review process in general, independent of open peer review or not, authors would have to include respective measures in the study design in advance.

Poorly discussed publications also cast a bad light on the institutions of the authors. This could contribute to the needed rethinking of ranking systems and to provide more support to implement quality measures, but I am also aware that the open peer review process might not equally suitable for all fields.

Final thoughts

It is important to understand that standardisation does not necessarily mean the refinement or development of new and proprietary standards. Conversely, standardisation rather means the application of existing standards, whether de facto or de jure. There is no need to reinvent the wheel. Often standardisation or quality management measures are already existing in institutions, but their existence might not be well communicated. Therefore, I strongly recommend proactively engaging with colleagues, initiatives, platforms, etc. to find out what is already out there and how to enable and implement existing measures in the daily workflow. I know that the subject is complex and unfortunately there is far too little explanatory material and training to enable access at a simple level. Nevertheless, it is important to engage with and address the topic to align (technological) innovation of our findings with both, research, and broader social values.

Read the full Opinion Article, ‘The need for standardisation in life science research – an approach to excellence and trust’ >>