Chapter 1 What is Open Science?

LEARNING OUTCOMES

  • Identify and explain Open Science's principles.
  • Compare the different initiatives promoting Open Science nationally and internationally.
  • Appraise the implications of using Open Science's principles of reproducibility, openness, and replicability in the research process.
  • Apply Open Science to comply with the regulations of research institutions and funders, governments, and publishers.
  • Identify the steps required and implement the best practices to promote data sharing, open code and software, and data curation.

According to the 2021 United Nations Educational, Scientific and Cultural Organization (UNESCO) Recommendation on Open Science, "... Open Science is defined as an inclusive construct that combines various movements and practices aiming to make multilingual scientific knowledge openly available, accessible and reusable for everyone, to increase scientific collaborations and sharing of information for the benefits of science and society, and to open the processes of scientific knowledge creation, evaluation and communication to societal actors beyond the traditional scientific community. It comprises all scientific disciplines and aspects of scholarly practices, including basic and applied sciences, natural and social sciences and the humanities, and it builds on the following key pillars: open scientific knowledge, open science infrastructures, science communication open engagement o societal actors and open dialogue with other knowledge systems." (2017, p. 7)

For The European Commission's task force on Research and Innovation (2021), "Open Science is a system change allowing for better science through open and collaborative ways of producing and sharing knowledge and data, as early as possible in the research process, and for communicating and sharing results. This new approach affects research institutions and science practices by bringing about new ways of funding, evaluating, and rewarding researchers. Open Science increases the quality and impact of science by fostering reproducibility and interdisciplinarity. It makes science more efficient through better sharing of resources, more reliable through better verification and more responsive to society’s needs" (p. 1)

In the United Kingdom, different regulations on open science (also named Open Research or Open Scholarship) has been developed. For example, the 2019 Concordat to Support Research Integrity (Universities UK) or the 2016 Concordat on Open Research Data (HEFCE, Research Councils UK, Wellcome Trust, Universities UK) have captured some of the initiatives on Open Science discussed and developed by other policy makers, institutions, publishers, funders, and research councils. It is important to note that the UK Reproducibility Network---supported by UK Research Institute, the British Psychological Society, Wellcome Trust, Cancer Research UK, UK Data Service, or Universities UK---has played a pivotal role in "seeking to understand the factors that contribute to poor research reproducibility and replicability, and to develop approaches to counter these and improve the quality of the research we produce" (UK Reproducibility Network, 2021, p. 1).

To empower researchers at every career stage, different organizations and Higher Education institutions have launched innovative educational programes along with institutional statements and strategies to promote Open Science best practices. For example, the University of Sheffield has launched an Open Science strategy to promote a culture of research excellence. The University of Manchester has created the Office for Open Research led big five strategic priorities: (1) open research skills, (2) open research communities, (3) open research recognition, (4) open research workflows, and (5) open and FAIR research outputs. Similarly, the University of Surrey developed a 5-year open research strategic goals and action plan that emphasizes the awareness, training and advocacy of open practice across the university in research, teaching, and learning.

In December 2021, Loughborough University published an Open Research Position Statement to develop, review, and promote an institutional policy framework for Open Research. Echoing the University of Manchester's strategic priorities, Loughborough University has emphasized the pivotal role of training and support for PhD students and senior academics to update their skills for open data and open methods (i.e., science communication, information and data literacy). Other universities stressing the importance of mastering digital literacy skills for open data and code/software (e.g., programming in R/Python, data sharing) are the Open Research Skills Framework at the University of York, King’s College and their Open Research Group Initiative (KORGI), the University of Glasgow, the Reproducible Research Oxford group (RROx) at the University of Oxford, the Birmingham Environment for Academic Research's (BEAR) software carpentry training (in R, Python, Matlab, and Git) at the University of Birmingham, Open Research education for doctoral students at Imperial College London, or the Edinburgh Open Research Initiative of the University of Edinburgh.

Table 1.1: Open Science Skills and Required Training
Skills Training
Digital content creation Copyright and intellectual property (CC-BY)
Management and use of institutional repositories (DORA)
OA publishers (e.g., bookdown)
Open publication options (e.g., Gold, Green)
Data repositories (OSF, Zotero, Figshare, Github)
Data management plan
Data presentation
Science communication Bibliometrics, Altmetrics, and researcher impact
DMU/Institutional webpage
Personal brand (e.g., ORCID, Researchgate, Google scholar, Scopus)
Public engagement (e.g., Leicester Business Festival)
Research informs teaching (handbooks, monographs, tutorials)
Innovation (e.g., the role of visual statistics during COVID-19)
Information and data literacy Data analysis and visualization
Data wrangling, modeling
Text mining (qualitative research)
Secondary sources (e.g., spatial data, census)
Reproducibility and data reuse
Publish in data journals
Transparency
Research integrity