Introduction
These recommendations are based on the results of one of the ROSiE project work packages aimed at mapping, analysing and addressing social and legal implications and challenges related to Open Science in the context of research ethics and research integrity.
The recommendations are based on a non-systematic critical interpretive review of the publicly available reports from relevant EU funded research projects and scientific literature, as well as on the results of focus group discussions organized by the ROSiE project where scientists discussed social implications and challenges related to Open Science.
Addressing social issues
- Identify and change cultural attitudes and elements of institutional culture that are potential barriers to the implementation of Open Sciencepractices. Scientists or institutions may lack motivation and opportunities to change existing power relationships, traditions, practices, and unwritten norms in science which are often based on cultural attitudes and the existing institutional culture that may differ in various cultural and institutional contexts. Social sciences research studies may help identify these potential barriers both at the institutional and national levels. To overcome cultural resistance and to incorporate Open Science practices, management aimed at the internalization of Open Science principles and values, fostering scientists’ well-being, as well as supporting scientists in their efforts to open scientific practices, data, and research results is important.
- Provide researchers with the necessary resources and infrastructure to support responsible Open Science practices. The Open Science Framework is infrastructure-heavy and functions at its best in countries with established and operational systems of public-funded research. However, Open Science resources and infrastructure must be accessible and affordable to all researchers, regardless of their location or institutional affiliation. Also, information about existing Open Science infrastructures and resources is crucial for the successful implementation of Open Science practices.
- Recognise legitimate differences in attitudes and readiness to engage in Open Science between different fields of science. Differences between scientific disciplines may be explained by differences in technical skills, traditions, data specificity (qualitative/quantitative/sensitive/personal, etc.), history of practicing Open Science in discipline, etc. Some scientific disciplines have well-developed traditions in Open Science and data sharing and have developed the necessary infrastructure and databases, whereas other disciplines may lack this experience, traditions, and infrastructure. Also, ethical issues in the case of human subject research may affect researchers’ willingness and ability to share data. There are also differences in attitudes related to the perception of data, where some scientists may see the research material and data as their personal property.
- Recognize the potential for global inequities in access to Open Science infrastructure and act to promote global justice and support the needs of researchers in low-and middle-income countries. More social sciences research and analysis are necessary to gather data on these needs and attitudes, especially in disadvantaged and less represented groups, e.g., scientists in low-and middle-income countries. For example, costs emerging in the context of Open Science (funding needed for the development of Open Science infrastructure, open publishing, implementation of citizen science, and additional training of researchers) can be a significant economic barrier for developing countries and institutions experiencing financial struggles. The situation where Open Science which initially was aimed at building equality creates new forms of inequality is not acceptable.
- Re-evaluate current institutional and national level incentives and evaluation systems to align them with Open Science practices. The hyper-competitiveness of the academic environment and the existing science assessment systems still heavily based on quantitative indicators are additional barriers to responsible practicing of Open Science calling for novel and effective solutions.
- Recognize and reward researchers for their contributions to Open Science, such as data sharing, publication of preprints, citizen science, and open access publications. The predominant evaluation system of scientists and scientific results still heavily relies on quantitative indicators such as citation indexes and impact factors. The Open Science movement aims to shift the focus towards transparency, reproducibility, and collaboration, encouraging researchers to embrace Open Science practices. Evaluation of researchers and research results should be a holistic process that considers a range of factors rather than relying solely on traditional metrics, such as the number of publications and their impact factor, which can still be relevant but should be complemented by more comprehensive indicators. Policy-makers at national and institutional levels should develop new indicators and evaluation systems following the available guidance.[1]
- Analyse and address the potential for gender-, ethnicity-, age-, disability-related and other biases in research and act to ensure that responsible Open Science practices promote equality and diversity. At the national and institutional level, when developing policies and diversity action plans for the research environment addressing inequalities based on gender, ethnicity, age, socio-economic status, disability, career stage, etc., issues related to Open Science should be addressed and included in these plans. An open question is why and how different types of inequalities impact the practicing of Open Science and vice versa and this aspect still needs further research.
- Promote Open Science practices in the industry sector. Industry researchers may encounter fewer opportunities and incentives to engage in Open Science practices due to the restrictions imposed by industry sponsors, who typically follow a more closed model of data management than academic environment.
[1] Evaluation of Research Careers fully acknowledging Open Science Practices. Rewards, incentives and/or recognition for researchers practicing Open Science. European Commission. Directorate General for Research and Innovation. Open Science and ERA Policy Unit 2017.
This passage is part of D2.3 Recommendations for addressing social challenges in OS written by Heidi Beate Bentzen, Teodora Konach, Signe Mežinska.