A Connected Culture of Collaboration
Collaborations can be a vital means to tackle complex scientific problems and global challenges. Although there can be benefits for research, it might not always be the best approach to take. Liz Allen discusses how to recognise the value of collaborations and the importance of understanding when and how to forge, sustain and nurture them.
“‘Science of science’ always seems woefully neglected, and under-funded, given that if we knew how to optimise support for science and research, we should be able to produce many more of those outputs that funding agencies are keen to count, and accelerate their impact both within and beyond academia.”
I contributed to the recently published Digital Science report on the Connected Culture of Collaboration. In it, I explore how it is important for science to understand more about how collaboration, multi-disciplinary research and team science work to best effect. And maybe, when collaboration might not be the best option. There is also a possibility of what researchers at MIT, Magdalini Papadaki and Gigi Hirsch, coined ‘consortium fatigue’ arising, whereby large scale research may result in, for example, low productivity or a sense of redundancy.
‘Science of science’ (or as the MIT team suggested ‘science of collaboration’) always seems woefully neglected, and under-funded, given that if we knew how to optimise support for science and research, we should be able to produce many more of those outputs that funding agencies are keen to count, and accelerate their impact both within and beyond academia.
The starting point for understanding collaboration is, as Laure Haak, Executive Director of ORCID, who wrote the Collaboration report’s foreword says, ‘we need to be intentional with our infrastructure’. The way research is set up, directed, executed, where, with what, with whom, and all the other things that can influence the results of an experiment at any given time, on any given day, provides the context that is likely to be pivotal in making a breakthrough, or not. Put simply, the environment and resources, and the team, available for scientific research are crucial.
It is easy to find examples of multi-disciplinary teams and collaborations that have produced significant leaps forward and far-reaching impact. A recent analysis of the UK’s Research Excellence Framework (REF) found that over 80 per cent of the REF impact case studies described impact that was based upon multidisciplinary research. There is, however, more to know about when and how to forge, sustain and nurture collaboration. There is also evidence that working as part of a large team or collaboration can have a detrimental effect on the career of some individuals; particularly while research articles remain a researcher’s main currency.
Assigning authors’ roles
Original research papers with a small number of authors, particularly in the life sciences, have become increasingly rare. Therefore, use of author position, as a way to estimate levels of researcher contributions is not useful nor is it easy to distinguish the role each author played. To provide an updated view of authorship and greater transparency around research contributions, the Contributor Roles Taxonomy (CRediT) was developed
CRediT is the result of cross-sector collaboration, medical journal editors, researchers, research institutions, funding agencies, publishers and learned societies, and provides a simple taxonomy of roles that can be assigned as descriptors of individuals’ contributions to scholarly published output.
Individual contributions are captured in a structured format and stored as a piece of meta-data during an article’s submission process. The taxonomy, going way beyond the concept of ‘authorship’, includes a range of roles such as data curation; development of design methodology; programming and software development; application of statistical or mathematical techniques to analyze data; and data visualization. Assigning these roles to those putting their name to a piece of scholarly output allows individuals to be recognised for specific skills and contributions to the research enterprise.
What changes have we seen?
Since its launch in 2014, there has been considerable support for CRediT’s pragmatic way to provide transparency and discoverability to research contributions, and importantly build this into the scholarly communication infrastructure at minimal effort to researchers. The standards organisation, CASRAI (Consortia Advancing Standards in Research Administration), is the custodian of the CRediT taxonomy, and many organisations are already using the taxonomy. In 2016 PLOS implemented the CRediT taxonomy for authors across all its journals; Cell Press have endorsed the use of the roles amongst their ‘authors’; Aries Systems includes the taxonomy in its Editorial Manager manuscript submission system; and F1000 are implementing the taxonomy across their open research publishing platforms during 2017.
If others follow, this means that we will be able to tie contributions, to collaborations, to outputs and to impact. Collaborations are considered by policymakers and funding agencies to be increasingly crucial ways to tackle complex scientific problems and global challenges. If we can understand how collaborations work and when, we can properly incentivise the sorts of behaviours and collaborations that might make breakthroughs more commonplace and potentially speed up the translation to tangible impacts. And for ‘science of science’ enthusiasts like me, it will take us a small, but helpful, step closer to being able to understand how science and research works.
I will be talking about the ‘connected culture of collaboration’ in a webinar on Thursday 6th April.
The original post can found on the F1000 blog.
Author: Liz Allen (@allen_liz) is Director of Strategic Initiatives at F1000, and involved in shaping new initiatives and partnerships to promote and foster open research. Prior to joining F1000 in 2015, Liz spent over a decade as Head of Evaluation at the Wellcome Trust, with a particular interest in impact assessment and the development of science-related indicators.