Open Science and Responsible Science

This study explores the responsibility framings researchers adopt when implementing Open Science (OS) policies, focusing on how responsibility dynamics are integrated into research practice. Three key responsibility framings emerged: internal orientation to responsibility (individual ethics), external orientation to socially/societally responsible science (social and societal ethics), and external orientation to shared, collective responsibility (collective ethics). These framings influence OS policy implementation, highlighting researchers’ roles in navigating ethical challenges and shaping OS practices. The first framing emphasizes personal ethics and reflection on OS policies, the second stresses the societal impact of research, and the third underscores the need for collective governance. This study contributes to understanding responsibility in science by presenting a dynamic, proactive view of responsibility, where researchers actively engage, challenge, and shape policies. It offers policy recommendations for adaptive OS frameworks, critical reflection on ethical challenges, and inclusive governance involving diverse stakeholders to foster responsible Open Science.

The integration of Artificial Intelligence (AI) into scientific, technological, and medical(STM) research raises critical questions about balancing open science and responsible science. Open science promotes transparency, accessibility, and knowledge sharing to foster collaboration, innovation, and reproducibility. However, as sensitive data and proprietary technologies become central to research, security and intellectual property protection are significant concerns. This chapter explores the tension between these objectives and provides a framework for balancing transparency with security in AI-driven research. It discusses the ethical, legal, and technical challenges faced by researchers and institutions in adopting practices that promote both open access and secure data management. The chapter offers insights into reconciling open science initiatives with responsible science practices that prioritize privacy, confidentiality, and safety, highlighting the importance of policies and strategies for secure and ethical research practices.

Research to address global environmental and societal challenges increasingly depends on the availability of large-scale, multidisciplinary datasets, making the need for robust systems that ensure data discoverability, accessibility, and interoperability evermore critical. However, having the data is not enough, one also needs to know about—and understand the connections among—related outputs and entities that support the veracity and reproducibility of the research.The International Generic Sample Number (IGSN) is a persistent identifier (PID) for material samples arising from any research discipline. Originally developed in the Earth Sciences, the IGSN provides a vital component in solving the abovementioned challenges, enabling seamless integration of sample data across diverse platforms, disciplines, and organizational and geographic boundaries. By uniquely and permanently linking samples to their descriptions (provided as structured metadata), analytical results, and associated publications, IGSNs facilitate transparency, traceability, and reusability of material samples in line with the FAIR and CARE Principles. This is underpinned by the proven interoperability of the IGSN with the scientific communication infrastructure, which also enables citations of samples in the literature to be automatically captured.This presentation will showcase the collaborative efforts of the IGSN Organization (IGSN e.V.) and DataCite to establish a resilient, cross-disciplinary, globally harmonized PID system for material samples. Use cases will illustrate how IGSNs enhance research workflows, enabling researchers to be more effective and attributed. We will also discuss governance, technical standards, and best practices that promote trust in the IGSN-DataCite partnership and scalability of sample PID adoption, aligning with UNESCO’s Open Science recommendations.

Many initiatives addressing different types of problems of the practice of science and research have been described or cited in this book. Some were one-issue local actions, some took a broader approach at the national and some at EU level. Some stayed on, others faded after a few years. Many of the issues addressed by these movements and initiatives were part of the system of science and appeared to be systemically interdependent. This is how they converged and precipitated in the movement of Open Science, somewhere at the beginning of the second decade of this century. I discuss the major move that was made since 2015 in the EU to embrace the Open Science practice as the way science and research are being done in Europe. This elicited tensions at first foremost relate to uncertainty regarding scholarly publishing, of how and where we publish open access. But also, with respect to what immediate sharing of data and results in daily practice of researchers means, how we value and give credit for papers and published data sets. It thus poses the question of how, if at all, we must compare incomparable academic work, how we get credit and build reputations in this new open practice of science. It is indeed believed that Open Science with its practice of responsible science will be a major contribution to address the dominant problems in science that we have analysed thus far, or at least will help to mitigate them. Open Science holds a promise to take science to the next phase as outlined in the previous chapters. That is not a romantic naive longing for the science that once was. It will be a truly novel way, but realistic way of doing scientific inquiry according to the pragmatic narrative pointed out.The Transition to Open Science as can be anticipated from the analyses above will not be trivial. The recent discussions have already shown that the transition to Open Science, even between EU member states, is a very different thing because of specific national, societal and academic contexts.I will conclude this chapter reporting some of my first-hand experiences, in Brussels and during visits to several EU member states in the course of a Mutual Learning Exercise, but also encounters in North America, South East Asia and South Africa where we in the past years have discussed Open Science. Although we know science and scholarship have many forms and flavours and that wherever you go, there is not one scientific community. For me discussing the Transition to Open Science in the past four years was really a Learning Exercise, an amazing, mostly encouraging, but many times quite shocking, even saddening adventure.

Data science skills are rapidly becoming a necessity in modern science. In response to this need, institutions and organizations around the world are developing research data science curricula to teach the programming and computational skills that are needed to build and maintain data infrastructures and maximize the use of available data. To date, however, few of these courses have included an explicit ethics component, and developing such components can be challenging. This paper describes a novel approach to teaching data ethics on short courses developed for the CODATA-RDA Schools for Research Data Science. The ethics content of these schools is centred on the concept of open and responsible (data) science citizenship that draws on virtue ethics to promote ethics of practice. Despite having little formal teaching time, this concept of citizenship is made central to the course by distributing ethics content across technical modules. Ethics instruction consists of a wide range of techniques, including stand-alone lectures, group discussions and mini-exercises linked to technical modules. This multi-level approach enables students to develop an understanding both of “responsible and open (data) science citizenship”, and of how such responsibilities are implemented in daily research practices within their home environment. This approach successfully locates ethics within daily data science practice, and allows students to see how small actions build into larger ethical concerns. This emphasises that ethics are not something “removed from daily research” or the remit of data generators/end users, but rather are a vital concern for all data scientists.

The concept of Public Engagement (PE) is related to progress toward responsible and open science. This article aims to analyse how to define and integrate PE into the development of ethical governance systems for research and innovation. Multistakeholder consultation on the governance of Responsible Research and Innovation was carried out internationally within the framework of the European ETHNA project, with interviews, workshops and a survey answered by 889 experts. The results include the detection of the main drivers and barriers to the implementation of PE on the design and application of an ethical system of governance. The study concludes that PE is a fundamental criterion for the design and implementation of an ethical system for the governance of science, for normative reasons and due to implementation practices. The main driving forces depend on its inclusion in the governance of institutions (culture, management support, training, incentives and resources) and its application through ethical management tools (ethical codes, committees and ethics lines).

This document summarizes on two pages the main recommendations from the Guidelines on Governance Settings for Responsible and Open Science.

CLARIN is the European research infrastructure for language resources. It is a sustainable home for digital research data in the humanities and it also offers tools and services for annotation, analysis and modeling. The scope and structure of CLARIN enable a wide range of studies and approaches, including comparative studies across regions, periods, languages and cu a player in making the vision that is underlying the emerging European policies towards Open Science a reality, by interconnecting researchers across national and discipline borders and by offering seamless access to data and services in line with the FAIR data principles. CLARIN also aims to contribute to responsible data science by the design as well as the governance of its infrastructure and to achieve an appropriate and transparent division of responsibilities between data providers, technical centres, and end users. CLARIN offers training towards digital scholarship for humanities scholars and aims at increased uptake from this audience.

These Guidelines are intended to deal with this complex set of issues, starting from a simple question: how can RRI and OS be effectively embedded in research organisations? They're not intended to offer ready-made solutions to this problem, since readymade solutions simply do not exist. Rather, their main aim is to propose a pathway – in which the users of the guidelines will necessarily play a proactive and creative role – for activating institutional change processes towards RRI and OS in their organisation in a way that is as feasible, sustainable and useful as possible. The Guidelines can be useful for all those interested in promoting RRI and OS at any level, including, e.g., policymakers, science centres, technology developers or private firms. However, as can be easily understood, the main targets of these Guidelines are European research funding and performing organisations of any kind (universities, research labs, funding agencies, governmental research agencies, etc.) since they are increasingly asked to introduce institutional changes towards RRI and OS and are exposed the most to the transformations affecting science. The Guidelines are one the main products of the project “Fostering Improved Training Tools for Responsible Research and Innovation - FIT4RRI”, co-funded by the EU DG Research and Innovation under Horizon 2020 and coordinated by Sapienza University of Rome.

<em> We're excited to announce that Nicola Mulder will be delivering the keynote at BOSC 2019. Read the abstract below for a taster of the talk to come… </em> Dr Nicola Mulder Due to a history of exploitation and inequitable scientific partnerships, many African researchers are reluctant to fully embrace open science practices.

<em> We're excited to announce that Nicola Mulder will be delivering the keynote at BOSC 2019. Read the abstract below for a taster of the talk to come… </em> Dr Nicola Mulder Due to a history of exploitation and inequitable scientific partnerships, many African researchers are reluctant to fully embrace open science practices.

In 2021 Sweden’s first national portal for citizen science will be launched to help researchers practice sustainable and responsible citizen science with different societal stakeholders. This paper present findings from two surveys on attitudes and experiences of citizen science among researchers at Swedish universities. Both surveys provided input to the development of the national portal, for which researchers are a key stakeholder group. The first survey (n=636) was exclusively focused on citizen science and involved researchers and other personnel at Swedish University of Agricultural Science (SLU). 63% of respondents at SLU had heard about citizen science (CS) prior to the survey; however a majority of these (61%) had not been involved in any CS initiative themselves. Dominant reasons for researchers choosing a CS approach in projects were to enable collection of large amounts of data (68%), improving the knowledge base (59%), improving data quality (25%), promote participants’ understanding in research (21%) and promote collaboration between the university and society (20%). The other survey (n=3 699) was on the broader topic of communication and open science, including questions on CS, and was distributed to researchers from all Swedish universities. 61% of respondents had not been engaged in any research projects where volunteers were involved in the process. A minority of the researchers had participated in projects were volunteers had collected data (18%), been involved in internal or external communication (16%), contributed project ideas (14%) and/or formulated research questions (11%). Nearly four out of ten respondents (37%) had heard about CS prior to the survey. The researchers were more positive towards having parts of the research process open to citizen observation, rather than open to citizen influence/participation. Our results show that CS is a far from well-known concept among Swedish researchers. And while those who have heard about CS are generally positive towards it, researchers overall are hesitant to invite citizens to take part in the research process.

The Bioinformatics Open Source Conference is a volunteer-organized meeting that covers open source software development and open science in bioinformatics. Launched in 2000, BOSC has been held every year since. BOSC 2019, the 20th annual BOSC, took place as one of the Communities of Special Interest (COSIs) at the Intelligent Systems for Molecular Biology meeting (ISMB/ECCB 2019). The two-day meeting included a total of 46 talks and 55 posters, as well as eight Birds of a Feather interest groups. The keynote speaker was University of Cape Town professor Dr. Nicola Mulder, who spoke on “Building infrastructure for responsible open science in Africa”. Immediately after BOSC 2019, about 50 people participated in the two-day CollaborationFest (CoFest for short), an open and free community-driven event at which participants work together to contribute to bioinformatics software, documentation, training materials, and use cases.

The CODATA-RDA Schools for Research Data Science (SRDS) is a network of schools originating in the RDA in 2016. In 2019 it was recognized as an RDA output. To date, over 400 students from 40 countries have been trained in 10 schools. The majority of these students were postgraduates from low/middle-income countries (LMICs). In contrast to many other data science training approaches, the SRDS schools are designed to be 2-week, disciplinarily-agnostic, residential events where students are introduced to a broad range of tools requisite for efficient and responsible data-centric research. This paper presents the results of a survey carried out on alumni from schools held between 2016 and 2019 (45% response). The results of the survey strongly support the SRDS’s long-term goals of facilitating data science training/capacity building within LMICs, and to foster communities of early career researchers (ECRs) conducting responsible and open data science research. The survey results demonstrated that 90% of respondent alumni continued to conduct research and make use of the skills acquired at the SRDS. Modules on open and responsible research and research data management were rated as important for future research. 79% of respondents confirmed that they maintained contact with peers, and 31% had set up academic collaborations with peers and/or instructors. Many had gone on to present content from the schools in their home institutions. The survey results clearly demonstrate the impact of the SRDS, and the value of an expanding network of schools supported by the RDA and CODATA.

The movement for open and reproducible science has promoted several changes in the scientific ecosystem. The Brazilian Reproducibility Network (BrRN), created in 2023, seeks to consolidate these efforts at a national level, promoting a collaborative environment for activism, development of educational resources and metascience. The BrRN encompasses institutions, scientific societies and journals, groups and individuals who are engaged in promoting common values in various areas of knowledge and regions of the country. In this article we present the background to the formation of the BrRN and its activities in its first two years of existence. We hope that the project will contribute to more reliable, responsible and rigorous science in Brazil through collaborative, transparent and reproducible practices.