The Focus on Open Science Workshops recommend management solutions tailored according to the individual requirements of each institution. What is needed for that?

‘Scholarship is a complex system. Open Science is even more complex The transition to Open Science affects all stakeholders – universities, researchers, teachers, students, funders, publishers, policy makers and support organizations. Bringing that change at research organizations requires:

European universities, and to an extent most research organizations, admit that one-size-fits-all solutions are in most cases inappropriate and unlikely to be successful, but there will be areas where large groups can work together on shared goals. Such a commitment is enshrined in the LERU advice paper on open science:

As the LERU advice paper on open science, launched in May 2018, strongly suggests, cultures do not change overnight. 5 A programme of change management needs to accompany and support any move to open science. Universities need to decide which mix of policies, measures and engagements best supports their missions and implementation strategies. Since these vary across Europe, it is impossible to have identical goals across all universities.

There are many challenges in moving to an open science environment, including copyright, costs, data privacy and so on. However, having met with many relevant players in a diverse range of European research communities, we have noticed that the institutions leading in open science all share the same opinion: the most difficult change needed seems to be cultural change.

Competition is built around the verb ‘to have’ and increases the sense of ownership. Collaboration is built around the verb ‘to be’ and, amongst other things, it opens up opportunities for new ways of performance. Combining the principles of competition and collaboration, we can obtain the right level of ownership in research (from knowledge to infrastructure) and the right model for collaborative performance that will ensure recognition and sustainability.

We would like to highlight what we consider to be the most fundamental difference between locked science (closed science, where data sets are locked in private archives) and open science. Today, locked science is performed within a highly competitive framework, as described above. Competitive research is tracked numerically; researchers keep making comparisons between colleagues and wanting to win.

In scholarly communication, in particular, which has been transformed from avenues of communication into a network of publication with metrics and analytics, we can see important areas left undeveloped. The results of research are more likely to be published if they are positive. Instead of growing a culture for disseminating the (ultimately important) results of research activity that was conducted rigorously, under a solid methodology which produced important data sets, we have built a system that is doing so only if the results are positive, a system that is pushing for certain areas of exploration that are more likely to win the metrics competition. Editors should not make a decision for publication based on results alone. They should do so based on the rigour of the research process and how the results contribute with all their elements to the field of study: from data sets to algorithms and to conclusions.

Open science is a different way of conducting research in which collaboration stands right next to competition. This novel route is able to unlock further resources as well as create a more stable, distributed, powerful and sustainable infrastructure that is more efficient than it otherwise might have been. Yes, we do also suggest that funders should look again at the type of research they fund, possibly less oriented to project-based investments. Research investments should match ideas and not the opposite. Great ideas are currently shaped to fit calls for projects and are sacrificed if the competition barometer does not predict success.

The authors of this article started to organize a series of events on open science throughout Europe in 2015. The series is called Focus on Open Science, 3 with a mission to promote the concept of, values for and best practices in open science to European communities. Each of these events (called chapters) is organized in close collaboration with a local academic institution, in this way determining each year the topics that are most suitable to be discussed within their own open science landscape, but having in mind the overall recommendations on open science from the European Commission (EC). The series started with one chapter in Ljubljana and the team went on to deliver 11 events in 2019. 4 We reached a number of conclusions during these events and many of them have helped us to orient this opinion piece.

Open science, that is open research and open scholarship in all disciplines, is a different way of pursuing scholarship. Today, science is carried out in a highly competitive framework. Researchers and organizations compete to promote their scientific assumptions, to win funds, to be the first to discover something or find solutions, and/or to get the best publication space to communicate their success and make their conclusions shine. In this landscape, researchers compete to publish more, compete for attention, and/or compete to win comparative assessments. There is an important observation we should make here: competition is about winning a race where the rules are set by others. Success is measured by someone else’s definition of it. Competition is one important element of human progress, but it is not the only one and it usually works better when it is related to other elements, like collaboration.

Case studies

Case study 1: competition and collaboration The authors of this article organized a workshop at OAI11 in Geneva (21–23 June 2019), an event co-hosted by CERN and the University of Geneva.8 This workshop aimed to create stepping-stones for building a path for raising collaboration to the same level as competition in a new definition of success in research. It brought together 15 people from eight countries, with various professions: researchers, research administrators, publishers, librarians and representatives of technology companies. The meeting started with two short presentations from the authors of this article: one from Dr Tiberius Ignat (Director of Scientific Knowledge Services) and the second from Dr Paul Ayris (Pro-Vice-Provost, University College London [UCL] Library Services and Fellow of the Royal Historical Society, UK). The main message of the first presentation was that without a high level of collaboration, open science is less vibrant, is disadvantaged and is a ‘reversible’ movement. Tiberius Ignat also presented his view regarding the hazards of open science. These are: failure itself (i.e. not delivering a radical and positive change, not attracting the world’s biggest talents nor nurturing diverse communities of explorers)

becoming an exclusive movement of public research that continues to increase the disconnect with society

associating ‘open’ with ‘ignore’ when it comes to resources that are needed to perform using ‘open’ methods

danger of the lack of reciprocity: where some communities benefit from FAIR data, OA and other research output shared globally, while others use the output thus shared without themselves contributing to the global research commons. Next, he brought the perspective of misdirection to the fore: that open science is about changing patterns of participation. We have become used to hearing that science should be taken back by public institutions, with a certain preference for not-for-profit organizations. Yet, that is misleading! Limiting participation in research activities to just one part of society (public and not-for-profit) creates unnecessary isolation and increases the gap between public research and the broader society. Instead, the speaker stressed that: great research exists in non-public as well as not-for-profit organizations

research should no longer be perceived as an elite activity

distributed participation gives far more public control than a concentration on one particular sector. Instead of looking to limit participation, we should look to increase and distribute both membership and governance. That could make a much bigger difference in the process of opening up research activities to obtain transparency, integrity, long-term support and agile steering. In Paul Ayris’s presentation, the takeaway message that he proposed to the participants was: academically, competition should be against yourself, not really against each other

no university can be self-sufficient

emphasis is on multidisciplinary and interdisciplinary research

universities need to partner with society to show their value

all these principles are underpinned by collaboration. This presentation showed what collaboration looks like in practice, at a research-intensive institution. Paul Ayris presented an analysis of the 2019 UCL Research Strategy9 which contains three references to Competition and 19 equivalents to Collaboration. Among the six principal directions of UCL 2034: a new 20-year strategy for UCL,10 Principal Theme No. 6 (Delivering global impact)11 is described as ‘delivering global impact through our international activities, collaborations and partnerships’. As an example of European engagement, UCL’s triple-track European strategy has included consolidating existing partnerships with European universities, launching a new initiative called the Cities Partnerships Programme (starting in Rome and Paris) and stepping up the University’s support for EU research collaboration. In terms of national partnerships, UCL was selected in December 2016 to host the research hub and operational headquarters of the UK DRI (UK Dementia Research Institute), forming the focal point for activity across the six university partners of the UK DRI. The other centres are at the University of Cambridge, Cardiff University, the University of Edinburgh, Imperial College London and King’s College London. Breakout groups The workshop continued with two breakout groups, where the meeting split into teams to try and identify how new goals and new principles could support researchers and research organizations, if we indeed want collaboration to be valued as equally as competition. Here are the principles and goals that were suggested: share knowledge with the broader society

create funding systems that encourage young talents to become researchers. Embed collaboration from the early stages of activity as a long-term strategy

make public engagement part of research proposals and a criterion for funding

find new resources/extend existing ones to support research ambitions, outside current templates (channels)

funding through projects should not be the only channel for supporting research activities

support research programmes more obviously and not simply research projects

disseminate outputs (publications, data, software) more broadly. Debate, brainstorming and speed-talk tables The last part of the workshop included a debate, a brainstorming session and three speed-talk tables, in an effort to find the first stepping-stones towards a path for more collaboration in research activities. Here are the ideas that were shaped: collaboration might build more reproducibility into the system and avoid creating a single point of failure

collaboration is a sign of research integrity and should be embedded in institutions and in careers

measure the performance of research funders, who should include in their policies actions towards more collaborations in science and between science and society

leadership is a necessary element of redesigning research frameworks, with particular importance being given to developing the role of collaboration

create more stability for research careers. Collaborations could be an important element of such stability

project competitions have the potential for producing great ideas that simply do not fit into calls for projects. Continue to launch project competitions, but find complementary routes for funding research ambitions

a DORA-type declaration concerning how research funders should align policies on how they evaluate research and how collaboration plays a role in that evaluation

encourage pioneering for bringing collaboration up to the same level as competition

define the constitutive elements of collaboration

reward collaboration

the governing bodies of projects/programmes should be multidisciplinary and multisector

the new landscape should encourage registered reports (that give equal attention to negative results)

science storytelling is important for open science.

Case study 2: UCL Press UCL Press12 is the UK’s first fully OA university press. It was started in 2015, building on the foundations of earlier commercial press activity. The purpose in refounding the press as an OA press was to offer support for the UCL academic community in publishing their research outputs as OA to help achieve their research objectives. In the UK the OA agenda was and is being driven by research funders such as the Wellcome Trust13 (now rebranded as Wellcome) and HEFCE (now part of UK Research and Innovation [UKRI]).14 UCL, as a global research-intensive university, wanted to develop research platforms which would support UCL’s academic activity. Partnership with academics was a prime motivator for the University to invest in systems and processes to support OA publishing. As CEO of UCL Press, Paul Ayris decided that it should develop publishing strategies for research monographs, textbooks and journals. The activity and the impact of that work in the areas of research monographs and textbooks are described below. The commercial business model for research monographs was broken.15 Traditional publishing models had taken insufficient notice of OA or even digital publishing. Between 2014 and 2016 UCL led the Academic Book of the Future project.16 The results of this project underlined the continuing importance of the book as a unit of output. ‘It seems that the future is likely to be a mixed economy of print, e-versions and networked-enhanced monographs of greater or lesser complexity.’ Much confusion, however, existed about the role of OA in this landscape.17 UCL Press started its OA journey with research monographs and has currently published just over 100 monographs. The most popular platforms on which to access these materials are UCL Discovery,18 the UCL OA repository, and JSTOR.19 In terms of the conventional print business model for books, sales over the bookshop counter are falling: ‘With sales of monographs falling and the publication of individual titles often based on print sales of 200 or fewer, some now question whether the current model is even viable and for how long.’20 While print copies of published outputs are available from UCL Press as print-on-demand copies, this is not the main form of output. Digital OA copy is the form which is easily the most popular. The UCL Press books are held as PDFs in UCL Discovery and made available via the main platforms listed above, supplemented by other routes. In July 2019 download stats stood at 2,167,470, with print sales at 13,643. The ten most downloaded titles are shown in Table 1. Title Publication date Downloads The Petrie Museum of Egyptian Archaeology 4 June 2015 48,211 How the World Changed Social Media 29 February 2016 338,615 Social Media in an English Village 29 February 2016 77,584 Textbook of Plastic and Reconstructive Surgery 2 August 2016 65,495 Social Media in Industrial China 13 September 2016 100,262 Conservation of Natural and Cultural Heritage in Kenya 7 October 2016 41,945 Fabricate 2017 3 April 2017 46,771 A Conversation about Healthy Eating 3 July 2017 64,359 Social Theory After the Internet 4 January 2018 57,043 Brexit and Beyond 29 January 2018 77,426 The download figures speak for themselves. The most downloaded book by far is Professor Danny Miller’s How the World Changed Social Media.21 Miller was awarded a European Research Council grant to look at the impact of social media around the world and his research team has produced a number of books on this theme, for which How the World Changed Social Media is the summary volume. One of the top ten is a textbook: Textbook of Plastic and Reconstructive Surgery, edited by Dr Deepak Kalaskar and others. This documents innovative clinical techniques in burns and plastic surgery. In discussion with the lead author, it was clear that he wanted the textbook to be OA in order to share such clinical practice with colleagues in developing countries, who simply would not be able to afford multiple copies of paper textbooks. Another finding from the UCL Press stats is the debunking of the idea that OA publication kills paper sales. Although not the primary form of dissemination, the Press is still making significant sales of paper copy, for example over 13,000 in July 2019. These figures debunk another misconception. Mandates for OA publishing from research funders usually exclude research monographs from their remit on the grounds that it is very difficult to change the current book publishing model. This is certainly the view of Plan S22 from Science Europe. Yet, the UCL stats suggest the opposite: that OA research monograph publishing is ripe for development. At the workshop on research practice held as part of OAI 11 in Geneva, the attendees looked at collaboration and sharing as a complement to traditional models of research competition. The theme of sharing and the creation of a global community being able freely to access research outputs is fundamental to the values held by UCL Press. Through the activity of the Press, UCL is able to fulfil its strap-line as ‘London’s Global University’ and to act as a generous partner in sharing its research outputs with the world. These are also the same ambitions as UCL’s Global Engagement Strategy.23 The heat map (Figure 1) shows the impact around the world of the downloads of UCL Press titles. Through the model of OA publishing, UCL has been able to reconnect its research activities in a very real way with communities across the globe. By doing so, UCL is able to share its insights to help discover solutions to the ills which face society – such as global warming, poor health and poverty. UCL has been able to develop its concept of sharing in the publishing arena in one further direction. The Press offers ‘white label’ publishing services to universities who wish to have their own university press but do not wish to invest in all the infrastructure necessary to deliver it. In this way, UCL Press can provide back-end publishing services to universities who want to become publishers. Front-end services, such as commissioning and peer review are the responsibility of the local university. All published outputs are branded with the name of the local university press. Dublin City University is the first European university to avail itself of these services, becoming the first fully OA university press in Ireland.

Case study 3: open data, FAIR data and reproducibility LEARN Research data is the new currency in research activity. A useful set of tools and insights on the role of research data was established by the EC-funded LEARN project,24 which received funding from the European Union’s Horizon 2020 research and innovation programme. LEARN produced a number of important outputs: a toolkit of best practice in Research Data Management (RDM)

a model policy for RDM

executive briefing on RDM in six languages

key performance indicators

20 RDM best practice recommendations

an evaluation grid for RDM policies in Europe

core elements of an RDM policy

an RDM readiness survey data set. One of the case studies in the toolkit of best practice looked at levels of preparation amongst researchers in a research-intensive university, UCL, for systematic RDM. The case study built on a wider survey undertaken in 2016 by Miriam Fellous-Sigrist on UCL researchers and their research data: practices, challenges and recommendations.25 Question 61 of the survey asked at what stage of their projects researchers started thinking about RDM. Two thirds of those answering (n = 217) said that they thought about this at the beginning or all the time. The answers from the remaining third were less positive. (See Table 2.) At what stage of the project did you think about data management? Timespan Defined as: % Beginning of the project ‘Very early on’; ‘straightaway’; ‘pre-protocol’; ‘at the outset’ etc. 51 Always ‘All the time’; ‘Throughout’ 16 Project development ‘Proposal writing’; ‘for ethical review’; planning’ etc. 14 Before or after ‘data collection’ ‘Questionnaire design’; ‘fieldwork preparation’ etc. 4 During the project ‘Periodically’; ‘halfway through’; ‘1st year of PhD’ 4 Never 4 Late Also ‘Too late’ 2 End of project ‘At the end’; ‘towards the end’ 1 Project completion ‘Ready for publication’; ‘database completion’ 1 Ad hoc 1 When a problem occurred 1 ‘Not until I took this survey’ 1 N = 217 Free text answers UCL’s Research Data Repository (RDR) Open data is key to establishing sharing and collaboration as part of UCL’s research mission. With this in mind, 2019 saw the launch of the Research Data Repository (RDR) for open data – data which is not personal nor sensitive and can be shared with a broader community.26 The position of the RDR in the UCL research system is illustrated in Figure 2. As Figure 2 shows, publications can be disseminated as green OA outputs via the institutional repository or else made available as gold OA outputs. UCL Press would be one such avenue. The RDR serves the same function for research data, enabling UCL to share its research data assets with the rest of the world. RDR was launched in June 2019, the culmination of a substantial three-year project. Given the short amount of time that RDR has been live, figures for usage are still in their infancy. Nevertheless, the data so far shows that the launch of RDR has made an impact on the UCL research community. The provision can only grow in importance and visibility as research funders increasingly require data curation plans and mandate curation as a condition of grant funding. Where they require open access to publications, they do not (yet) mandate the same for funded research data. Figures 3a and 3b show the monthly number of views and the number of downloads from RDR broken down by each of the UCL’s Faculties and Schools. The RDR service also reports on the global impact RDR is making by analyzing record views per country. Figure 4 shows where users of the RDR are based. The RDR represents a major investment by UCL in open data and is a contribution by one of the world’s great research-intensive universities to the open science agenda. It fulfils the aspirations voiced by Professor Geoffrey Boulton in his contribution to the LEARN project, echoing the Accord on Open Data from The International Union of Crystallography:29 ‘Publicly funded scientists have a responsibility to contribute to the public good through the creation and communication of new knowledge, of which associated data are intrinsic parts. They should make such data openly available to others as soon as possible after their production in ways that permit them to be re-used and re-purposed.’30 This is the position adopted by the RDR. Research data should be ‘as open as possible, as closed as necessary’.31 It is not a mandate for openness. The decision on whether to make data open lies with the research group undertaking the research, but open approaches are strongly encouraged. FAIR data Fundamental to good RDM are the FAIR principles, supporting data that is findable, accessible, interoperable and reusable.32 Most of these principles concern metadata. It should be noted that FAIR data is not the same as open data. Data can be FAIR, but still not open. One of the challenges in implementing FAIR data practices at institutional level is that FAIR demands significant input by researchers to describe their data. UCL has taken a measured approach in requiring metadata to describe research data in RDR. The web guidance specifies the following points. If you do not need to follow a discipline-specific schema, or funder’s recommendations, then we advise you to use the DataCite metadata schema. 33

As a general rule, DataCite 34 an identifier (a DOI) a creator (the name and affiliation of the main researchers involved in producing the data set) a title (the name or title by which the data set is known) a publisher (the name of the entity that holds the data set) a publication date (the year when the data set was or will be made publicly available) the type of resource you are describing. 35

FAIR data will underpin the development of the EOSC (the European Open Science Cloud) which is intended to become an ‘internet of things’. This point is made forcibly in the EC report Turning FAIR into reality.36 The report makes 27 recommendations, which are grouped into ‘priority’ and ‘supporting’ recommendations. The 15 priority recommendations should be considered the initial set of changes or steps to take in order to implement FAIR. Recommendation 10 recognizes the challenge which FAIR principles bring to an institution: ‘Steps need to be taken to develop two cohorts of professionals to support FAIR data: data scientists embedded in research projects, and data stewards who will ensure the management and curation of FAIR data.’37 There are significant financial implications behind this recommendation as, initially, there are extra upfront costs that have to be met. It will be a significant challenge for universities to meet. The Report acknowledges this and Recommendation 18 says: ‘Research funders should require data management costs and other relevant costs to be considered and included in grant applications where relevant. To support this, detailed guidelines and worked examples of eligible costs for FAIR data should be provided.’ However, not all research is grant funded and so the recommendation alone will not deliver a fully FAIR world.38 Recommendation 17 makes an important statement concerning FAIRness and openness: ‘Policies should be aligned and consolidated to ensure that publicly-funded research data are made FAIR and Open, except for legitimate restrictions. The maxim “as Open as possible, as closed as necessary” should be applied proportionately with genuine best efforts to share.’ This is exactly the position taken by the RDR at UCL.39 Reproducibility Reproducibility is critical to research in certain contexts, particularly in the experimental sciences with a quantitative focus. It forms part of UCL’s wider commitment to transparency and rigour in all of its research. UCL recognizes that behaviours in support of transparency and rigour vary considerably across disciplines and methodologies, and encourages researchers to adopt those actions most appropriate to their disciplines. In the arts, humanities and social sciences, it may be more useful to refer to transparency or academic rigour in the use of research methods and in the whole research process – from the collection of evidence or thoughts through analysis to final conclusions and the publication of findings. The reproducibility of research methods is required for research to be replicated. This, in turn, is essential in research contexts where findings must be robust and reproducible in order to form a solid foundation on which to build further knowledge. In research contexts where reproducibility is possible and appropriate, UCL strongly encourages researchers to use measures that support it. These include (but are not limited to): pre-registration of research studies

transparent reporting of research in line with guidelines 40

disclosure of all tested conditions, analysed measures and results

transparency around statistical methods (including sample size planning and statistical assumptions and pitfalls)

use of preprints

carrying out replication studies

publication of ‘null’ findings. Professor Marcus Munafo and others have set out a summary of initiatives that support reproducibility.41 UCL is committed to supporting transparency in research and to developing approaches to improve the quality of the research produced. This includes: continuing to support open research (including through the Academic Careers Framework 42 43

the development of governance processes to enable research outputs to be found, accessed, and reused appropriately when open sharing is not appropriate

the development of additional training, including in research methods, and consideration of how to promote transparency in academic teaching

improving the sharing of knowledge and best practice across UCL. In the autumn of 2019 UCL took steps to implement these convictions by issuing a Statement on Transparency in Research, which sets out the expectations the institution has for researchers relating to transparency and reproducibility at UCL.44