More than Open Data mandates: a staged model for achieving Open Access to scientific data

Not opening scientific data is costly. It has been estimated that a significant share of scientific knowledge disappears every year. In a 2014 study less than half of biological datasets from the 1990s have been recovered and when possible the recovery has necessitated significant time and efforts. In comparison, 98% of datasets published on PLOS with unique identifiers (data DOIs) are still available for future research. Open scientific data are fundamental resources for a large variety of scientific activities: meta-analysis, replication of research results or accessibility to primary sources. They also bring a significant economic and social value, as scientific data is commonly used by non-academic professionals as well as public agencies and non-profit organizations. Yet open scientific data is not costless. Ensuring that data is not only downloadable but usable requires significant investment in regards to documentation, data cleaning, licensing and indexation. Not all scientific data can be shared and verifications are frequently necessary to ensure that they do not incorporate copyrighted contents or personal information. To be effective, data sharing has to be anticipated throughout the entire research lifecycle. New principles of scientific data management aims to formalize the preexisting cultures of data in scientific communities and apply common standards. First published in 2016, the FAIR Guiding Principles (findability, accessibility, interoperability, and reusability) is an influential framework for opening scientific data. Policies in support of data sharing have moved from general and broad encouragement to the concrete development of data sharing services. Early initiatives go back to the first computing infrastructures: in 1957 the World Data Center system aimed to make a large range of scientific data readily available. Open data programs were yet severely limited by the lack of technical support and compatibility for data transfer. After 1991, the web created a universal framework for data exchange and entailed a massive expansion of scientific databases. Yet, numerous projects ran into critical issues of long term sustainability. Open science infrastructure have recently become key stakeholders in the diffusion and management of open scientific data. Data repositories ensure the preservation of scientific resources as well as their discoverability. Data hosted on repositories are more frequently used and quoted than data published in a supplementary file.

Purpose of the study. The purpose of this paper is to analyze the current state and prospects for introducing the principles of open access to scientific publications and scientific data in the sphere of science and education in Belarus. Its relevance is related to the need to develop measures to accelerate the process of digital transformation of science and education of the Republic of Belarus.Materials and methods. Information base of the research was made by publications of scientists and specialists on the issues under study, normative documents, final documents of conferences on this topic, data from the Open Data in Belarus portal, national and international aggregators of institutional repositories, open scientific data repositories.Results. The analysis of the state and prospects of introducing the principles of open access to scientific publications and scientific data into the sphere of science and education of Belarus was carried out during the research. It is shown that the digital transformation of science and education is at an early stage. The dissemination of the principles of open science and the introduction of new instruments of scientific communication in the Belarusian academic and university science are uneven, there is a need to develop a strategy in this direction. The principle of open access to publications is being most actively introduced into practice through the development of a network of university repositories. In Belarus, the open data infrastructure is at the very beginning of its formation. In this regard, there is a need to conduct additional research to identify problems associated with the discovery of scientific data. One step in the transition to open science is the unification of all the repositories on a single platform of the national aggregator. The review of national and international aggregators of institutional repositories is presented. The questions on creation of the national system-aggregator of information resources of open access in the Republic of Belarus in the context of the formation of the Republican information and educational environment are considered: the purpose of the system, the platform used, technical solutions for organizing the integration of information systems of higher education institutions and the rules of interaction of system users.Conclusions. The creation of a national system-aggregator will not only provide a single point of access to the institutional repositories of project participants, which will significantly improve the convenience and completeness of the search, but will also solve one of the most important tasks of the project - popularizing the idea of open access to scientific publications. The implementation of the proposed measures to create conditions for the discovery of scientific data in Belarus will contribute to the introduction of the principle of open access to scientific data. The considered approaches will allow accelerating the process of digital transformation of the scientific and educational sphere of Belarus.

Should research institutions from developing countries provide open access to their data? Who would benefit? These are highly relevant questions for environmental research. In the backdrop of increasing discussions regarding open data, attention should be paid to guarantee that research institutions from developing countries do not become mere data providers. At the same time, restricted access to data should not become a barrier for advancing our knowledge of critical environmental issues. Open access policies for environmental data must be developed not only for advancing science, but also to provide growing opportunities for researchers in developing countries.

The Open Knowledge Foundation has launched a Working Group on Open Data in Science.

An understanding of the similar and divergent metrics and methodologies underlying open government data benchmarks can reduce the risks of the potential misinterpretation and misuse of benchmarking outcomes by policymakers, politicians, and researchers. Hence, this study aims to compare the metrics and methodologies used to measure, benchmark, and rank governments' progress in open government data initiatives. Using a critical meta-analysis approach, we compare nine benchmarks with reference to meta-data, meta-methods, and meta-theories. This study finds that both existing open government data benchmarks and academic open data progress models use a great variety of metrics and methodologies, although open data impact is not usually measured. While several benchmarks’ methods have changed over time, and variables measured have been adjusted, we did not identify a similar pattern for academic open data progress models. This study contributes to open data research in three ways: 1) it reveals the strengths and weaknesses of existing open government data benchmarks and academic open data progress models; 2) it reveals that the selected open data benchmarks employ relatively similar measures as the theoretical open data progress models; and 3) it provides an updated overview of the different approaches used to measure open government data initiatives’ progress. Finally, this study offers two practical contributions: 1) it provides the basis for combining the strengths of benchmarks to create more comprehensive approaches for measuring governments’ progress in open data initiatives; and 2) it explains why particular countries are ranked in a certain way. This information is essential for governments and researchers to identify and propose effective measures to improve their open data initiatives.

Scholarly publishing has rapidly moved towards open access (OA) over the last few decades. However, OA publishing is only one part of a larger open science movement. The recent UNESCO recommendation for open science (UNESCO, 2021) defines open science broadly to cover the openness of scientific knowledge, science infrastructures, engagement with societal actors, and dialogue with other knowledge systems. In its recommendations, open scientific knowledge includes OA to scientific publications but also open research data, metadata, open educational resources, software, and source code and hardware. Earlier research about open scientific knowledge from the point of view of academic publishers has mainly been focused on one element such as OA publishing and neglected other elements.This paper aims to fill this gap by surveying how society publishers in Finland adopted other elements of open scientific knowledge. In Finland, learned societies account for 70% of national journal output (Late et al., 2020) and their publishing model is mainly diamond open access, which excludes author processing charges and relies on publishing subsidies (Pölönen et al., 2020). Furthermore, their activities often go beyond scholarly publishing to include education and research activities such as funding research and collecting and storing research data (Korkeamäki et al., 2019).We conducted an electronic survey addressed to Finnish learned societies in November 2021 to answer the following research questions: “To what degree society publishers take up the elements of open scientific knowledge including open access to publications, open data, and open education?” (RQ1) and “Are elements of open scientific knowledge cumulative?” (RQ2)In total 97 society publishers responded (40% response rate). We analysed their responses through nine variables measuring how they adopted different elements of open scholarly knowledge (Table 1) in view of the UNESCO recommendations for open science. The results show elements related to open scholarly publications prevail. Almost 70% of respondentspublish either gold, green, or hybrid OA publications. Most society publishers reported to support open data policies only some do collect, store, and provide open access to research datasets. Furthermore, only a few societies offer training for opening research data. Even so, a high share of publishers offers open education, and some share their educational materials openly. Although earlier studies have reported differences in adopting open science between disciplines (Rousi & Laakso, 2020), our analysis does not support these findings.However, it has confirmed that adopting the elements of open scholarly knowledge is cumulative, as OA publishers are more likely to take up other elements of open scholarly knowledge. However, adopting all elements is not yet common. Since activities (e.g. collecting research data, offering education, etc.) of publishers other than societies seem to influence the take up of these elements, further research of their activities is needed. For example, it will show how often and how openly these other publishers provide research data or education beyond.

This study investigates which combination of institutional and infrastructural arrangements positively impact research data sharing and reuse in a specific case. We conducted a qualitative case study of the institutional and infrastructural arrangements implemented at Delft University of Technology in the Netherlands. In the examined case, it was fundamental to change the mindset of researchers and to make them aware of the benefits of sharing data. Therefore, arrangements should be designed bottom-up and used as a “carrot” rather than as a “stick.” Moreover, support offered to researchers should cover at least legal, financial, administrative, and practical issues of research data management and should be informal in nature. Previous research describes generic institutional and infrastructural instruments that can stimulate open research data sharing and reuse. This study is among the first to analyze what and how infrastructural and institutional arrangements work in a particular context. It provides the basis for other scholars to study such arrangements in different contexts. Open data policymakers, universities, and open data infrastructure providers can use our findings to stimulate data sharing and reuse in practice, adapted to the contextual situation. Our study focused on a single case and a particular part of the university. We recommend repeating this research in other contexts, that is, at other universities, faculties, and involving other research data infrastructure providers.

The array of problems presented to Extension professionals is broad and growing in number and complexity. As Extension has demonstrated its adaptability in addressing these issues, new ways of working have emerged. Access to an expanding pool of scientific reports and data can potentially provide Extension professionals with the greater tools and knowledge they need to collaboratively engage with their communities. However, a key challenge and possible impediment will be access to rapidly emerging research and data. Open science and open data can broaden the evidence base available to Extension educators, and the emerging field of data science offers new tools to help Extension stakeholders make data-informed decisions. A new data-sharing partnership among Canada, Mexico, and the United States may serve as a model for other countries’ rural advisory services and national Extension systems. Fully implementing this expanded role for Extension will require resources to establish a National Community Learning Network and a national data commons as well as advocacy for open access policies at all levels of government. As abstract as open science and open data may seem to local and regional Extension practitioners, equal access to scientific knowledge and underlying research data is not only imperative for local community engagement but also integral for locally appropriate decision-making. Widening access to research and data directly supports the democratization of science and Extension. Opening scientific research and providing effective access to publicly financed data will become essential platforms for university engagement and Extension. It is critical for Extension professionals to understand the analytic powers and emerging policies that easily-accessed research and data can bring to collaborative community engagement.

Supporters of open data believe that free and complete access to research data is beneficial for science, public policy, and society. In environmental science and policy, open data systems can enable relevant research and inform evidence‐based governmental decisions. This article examines the unlikely case of Brazil's National Institute for Space Research's transition toward an open data model. Considering Brazil's young democracy, incipient practice of government transparency and accountability, and lacking a tradition of science‐policy dialogue, this case is a striking example of how open data can support public debate by making information about forest cover widely available. The case shows the benefits and challenges of developing such open data systems, and highlights the various forms of accessibility involved in making data available to the public.

Background: In this commentary, we argue that it is time for communication scholars to turn their attention to how and why data journalists engage with the increasing amount of open research and government data available online. Analysis: We review the limited scholarship that has investigated data journalists’ engagement with open data and suggest directions for future research. Conclusions and implications: Research that explicitly examines data journalists’ use of open data is sorely needed, especially research that attends to the varied forms and practices that can emerge in different national and institutional contexts.

Decarbonisation and efficiency goals set as a response to global warming issue require appropriate decision-making strategies to promote an effective and timely change in energy systems. Conceptualization of change is a relevant part of energy transitions research today, which aims at enabling radical shifts compatible with societal functions and market mechanisms. In this framework, construction sector can play a relevant role because of its energy and environmental impact. There is, however, the need to move from general instances to specific actions. Open data and open science, digitalization and building data interoperability, together with innovative business models could represent enabling factors to accelerate the process of change. For this reason, built environment research has to address the co-evolution of technologies and human behaviour and the analytical methods used for this purpose should be empirically grounded, transparent, scalable and consistent across different temporal/spatial scales of analysis. These features could potentially enable the emergence of “ecosystems” of applications that, in turn, could translate into projects, products and services for energy transitions in the built environment, proposing innovative business models that can stimulate market competitiveness. For these reasons, in this paper we organize our analysis according to three levels, from general concepts to specific issues. In the first level, we consider the role of building energy modelling at multiple scales. In the second level, we focus on harmonization of methods for energy performance analysis. Finally, in the third level, we consider emerging concepts such as energy flexibility and occupant-centric energy modelling, considering their relation to monitoring systems and automation. The goal of this research is to evaluate the current state of the art and identify key concepts that can encourage further research, addressing both human and technological factors that influence energy performance of buildings.

The vision of NFDI4Chem is the digitalisation of all key steps in chemical research to support scientists in their efforts to collect, store, process, analyse, disclose and re-use research data. Measures to promote Open Science and Research Data Management (RDM) in agreement with the FAIR data principles are fundamental aims of NFDI4Chem to serve the chemistry community with a holistic concept for access to research data. To this end, the overarching objective is the development and maintenance of a national research data infrastructure for the research domain of chemistry in Germany, and to enable innovative and easy to use services and novel scientific approaches based on re-use of research data. NFDI4Chem intends to represent all disciplines of chemistry in academia. We aim to collaborate closely with thematically related consortia. In the initial phase, NFDI4Chem focuses on data related to molecules and reactions including data for their experimental and theoretical characterisation. This overarching goal is achieved by working towards a number of key objectives: Key Objective 1: Establish a virtual environment of federated repositories for storing, disclosing, searching and re-using research data across distributed data sources. Connect existing data repositories and, based on a requirements analysis, establish domain-specific research data repositories for the national research community, and link them to international repositories. Key Objective 2: Initiate international community processes to establish minimum information (MI) standards for data and machine-readable metadata as well as open data standards in key areas of chemistry. Identify and recommend open data standards in key areas of chemistry, in order to support the FAIR principles for research data. Finally, develop standards, if there is a lack. Key Objective 3: Foster cultural and digital change towards Smart Laboratory Environments by promoting the use of digital tools in all stages of research and promote subsequent Research Data Management (RDM) at all levels of academia, beginning in undergraduate studies curricula. Key Objective 4: Engage with the chemistry community in Germany through a wide range of measures to create awareness for and foster the adoption of FAIR data management. Initiate processes to integrate RDM and data science into curricula. Offer a wide range of training opportunities for researchers. Key Objective 5: Explore synergies with other consortia and promote cross-cutting development within the NFDI. Key Objective 6: Provide a legally reliable framework of policies and guidelines for FAIR and open RDM.

Open Bioinformation in the Life Sciences as a Gatekeeper for Innovation and Development

The notes and transcript from the first meeting of the Working Group on Open Data in Science (online, June 2, 2009) are now available.

With the wave of digitalisation, institutions across countries are pushing for the creation of open data and their governance. FAIR Data Principles have initiated the publishing of open research data to the key stakeholders and practitioners in the low- and middle-income countries to meet their developmental goals through practical usage in problem-solving. Open Data, which is part of the Open Science movement, has transformed the regime structure at a transnational level for the governance of critical issues surrounding water and energy. This paper provides a baseline survey to look into the various open data initiatives in the areas of water and clean energy across countries in general and India in particular. Given the multifaceted challenges around the water-energy nexus existing in India, it is critical to identifying the open data initiatives and studying their governance at the country level. Since governance requires the participation of various institutions and multiple stakeholders, the research aims at highlighting the various initiatives such as participation of institutions and the application of Creative Commons (CC) licensing terms in the open data governance for clean energy and water sectors in India.