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This presentation has been given the 7th of June 2023 at the last INFO/RAC National Focal Points meetingand resumes the principal aspects and the future perspectives of the adopted UNEP-MAP Data Policy. The presentationis related to the document"MAP Data Policy (UNEP/MAP WG. 512/6)".

Companion Site for Harvard Medical School Canvas Network MOOC Best Practices for Biomedical Research Data Management Funding: NIH Big Data to Knowledge (BD2K) Initiative Research Education, Massive Open Online Course (MOOC)

The Human Genomes Platform Project (HGPP) is an Australian nationally-funded collaborative research project aiming to enhance capability for securely and responsibly sharing human genomics research data. National and international connectivity will maximise the utility of these sensitive and valuable assets. A major challenge to human genome data sharing is navigating restrictions on secondary use. Decisions on how and to whom to grant access to data require significant human effort by DAC (Data Access) Committees. This manual approach is slow and burdensome. The aims of the DAC Automation sub-project are to explore a new data access request and approval paradigm driven by automation for the national human genome research community. The initial focus of the DAC Automation sub-project team was a discovery and recording phase to define the current state of data access requests and data sharing agreements within the community, the set of problems that need to be addressed, and key sub-project areas and their (likely) requirements. The DAC Automation Discovery Phase Report (this document) records: the current state of processes and tools for data access requests and data sharing across the community, national community needs, gap analysis, and identification of international projects with potential solution components for piloting in later project stages.This document will be the reference for planning the pilot for a system that addresses prioritised requirements to create a Minimum Viable Product (MVP). The Australian human genome research community has many connections to consortia in Europe and the USA, but retains the need to work independently, according to our own national requirements and guidelines. International readers, particularly those who are outside Europe and the US, may find this discovery report useful for reference in their own human genome research data sharing program efforts.

The COVID-19 pandemic has highlighted the inadequacies of the world’s collective approach to data. The inability, and sometimes unwillingness, to share and use data to combat COVID-19 or to protect against predatory uses of data has negatively impacted individuals, private enterprise, citizens, research institutions and governments around the globe. A lack of trust combined with asymmetric economic interests are slowing progress on data sharing. This paper provides a clear overview of how to create the technology, commercial and policy frameworks required to ensure data sharing in future crises and some real-world examples of how they are currently being trialled and implemented globally.

Transparency, openness, and reproducibility are important characteristics in scientific publishing. Although many researchers embrace these characteristics, data sharing has yet to become common practice. Nevertheless, data sharing is becoming an increasingly important topic among societies, publishers, researchers, patient advocates, and funders, especially as it pertains to data from clinical trials. In response, ASTRO developed a data policy and guide to best practices for authors submitting to its journals. ASTRO's data sharing policy is that authors should indicate, in data availability statements, if the data are being shared and if so, how the data may be accessed. (C) 2019 The Author(s). Published by Elsevier Inc. on behalf of American Society for Radiation Oncology.

A group of publishers came together to discuss how we could reduce the complexity and inconsistency provided inpublisher's advice to researchers when selecting an appropriate data repository. It is a shared goal among publishers and other stakeholders to increase repository use – which remains far from optimal – and we assume that helping researchers find a suitable repository more easily will help achieve this. To address this a list of features has been created and it is intended only as a framework within which publishers can make recommendations to researchers, not as a way to restrict which repositories researchers may choose for their data. Our intention is that the features we highlight will act to initiate engagement and collaboration among publishers, repositories and the RPOs, government and funders that ultimately make the policies around Open Research. As we start this conversation, it is important that we act together with other stakeholders to raise awareness of the challenges involved around FAIR data and to prevent any perverse consequences. From the RDA FAIRsharing WG point of view, the ultimate objective is to map repository features across all existing initiatives, and to identify a common core set of metadata fields that all stakeholders want to see in registry ofrepositories. The FAIRsharing registry in particular is agnostic as to the selection process of standards, repositories and policies, as part of its commitment to working with and for all stakeholder groups.

Representatives from journals, journal publishers and scholarly communication organisations have come together in the FAIRsharing Community to propose a set of criteria for the identification and selection of those data repositories that accept research data submissions. These repositories can be recommended to researchers when they are preparing to release and publish the data underlying their findings. This work intends to (i) reduce complexity and inconsistencies for researchers in journal data policies, (ii) increase efficiency for data repositories that currently have to work with all individual publishers, and (iii) simplify the process of recommending data repositories by publishers. This work will make the implementation of research data policies more efficient and consistent, which may help to improve approaches to data sharing through the promotion and the use of reliable and sustainable data repositories.

This study reviews research data policies and author instructions of 31 journals from the Earth sciences and from Biodiversity that are published by German learned societies or research institutions. 12 journals don’t address data sharing at all. The statements on data sharing of the journal’s data policies/author guidelines were matched to 14 defined features of journal research data policies. A brief discussion on quality of data policies is presented to raise awareness of German learned societies/research institutions and to guide them towards improved data policies of their journals.

Institutions, funding bodies, and national research organizations are pushing for more data sharing and FAIR data. Institutions typically implement data policies, frequently supported by an institutional data repository. Funders typically mandate data sharing. So where does this leave the researcher? How can researchers benefit from doing the additional work to share their data? In order to make sure that researchers and institutions get credit for sharing their data, the data needs to be tracked and attributed first. In this paper we investigated where the research data ended up for 11 research institutions, and how this data is currently tracked and attributed. Furthermore, we also analysed the gap between the research data that is currently in institutional repositories, and where their researchers truly share their data. We found that 10 out of 11 institutions have most of their public research data hosted outside of their own institution. Combined, they have 12% of their institutional research data published in the institutional data repositories. According to our data, the typical institution had 5% of their research data (median) published in the institutional repository, but there were 4 universities for which it was 10% or higher. By combining existing data-to-article graphs with existing article-to- researcher and article-to-institution graphs it becomes possible to increase tracking of public research data and therefore the visibility of researchers sharing their data typically by 17x. The tracking algorithm that was used to perform analysis and report on potential improvements has subsequently been implemented as a standard method in the Mendeley Data Monitor product. The improvement is most likely an under-estimate because, while the recall for datasets in institutional repositories is 100%, that is not the case for datasets published outside the institutions, so there are even more datasets still to be discovered.

The paper aims to present the implementation of the RDA research data policy framework in Slovenian scientific journals within the project RDA Node Slovenia. The activity aimed to implement the practice of data sharing and data citation in Slovenian scientific journals and was based on internationally renowned practices and policies, particularly the Research Data Policy Framework of the RDA Data Policy Standardization and Implementation Interest Group. Following this, the RDA Node Slovenia coordination prepared a guidance document that allowed the four pilot participating journals (from fields of archaeology, history, linguistics and social sciences) to adjust their journal policies regarding data sharing, data citation, adapted the definitions of research data and suggested appropriate data repositories that suit their disciplinary specifics. The comparison of results underlines how discipline-specific the aspects of data-sharing are. The pilot proved that a grass-root approach in advancing open science can be successful and well-received in the research community, however, it also pointed out several issues in scientific publishing that would benefit from a planned action on a national level. The context of an underdeveloped data sharing culture, slow implementation of open data strategy by the national research funder and sparse national data service infrastructure creates a unique environment for this study, the result of which can be used in similar contexts worldwide.

Purpose Open data and data sharing should improve transparency of research. The purpose of this paper is to investigate how different institutional and individual factors affect the data sharing behavior of authors of research articles in sociology and political science. Design/methodology/approach Desktop research analyzed attributes of sociology and political science journals (n=262) from their websites. A second data set of articles (n=1,011; published 2012-2014) was derived from ten of the main journals (five from each discipline) and stated data sharing was examined. A survey of the authors used the Theory of Planned Behavior to examine motivations, behavioral control, and perceived norms for sharing data. Statistical tests (Spearman’s ρ, χ2) examined correlations and associations. Findings Although many journals have a data policy for their authors (78 percent in sociology, 44 percent in political science), only around half of the empirical articles stated that the data were available, and for only 37 percent of the articles could the data be accessed. Journals with higher impact factors, those with a stated data policy, and younger journals were more likely to offer data availability. Of the authors surveyed, 446 responded (44 percent). Statistical analysis indicated that authors’ attitudes, reported past behavior, social norms, and perceived behavioral control affected their intentions to share data. Research limitations/implications Less than 50 percent of the authors contacted provided responses to the survey. Results indicate that data sharing would improve if journals had explicit data sharing policies but authors also need support from other institutions (their universities, funding councils, and professional associations) to improve data management skills and infrastructures. Originality/value This paper builds on previous similar research in sociology and political science and explains some of the barriers to data sharing in social sciences by combining journal policies, published articles, and authors’ responses to a survey.

To improve the quality and efficiency of research, groups within the scientific community seek to exploit the value of data sharing. Funders, institutions, and specialist organizations are developing and implementing strategies to encourage or mandate data sharing within and across disciplines, with varying degrees of success. Academic journals in ecology and evolution have adopted several types of public data archiving policies requiring authors to make data underlying scholarly manuscripts freely available. Yet anecdotes from the community and studies evaluating data availability suggest that these policies have not obtained the desired effects, both in terms of quantity and quality of available datasets. We conducted a qualitative, interview-based study with journal editorial staff and other stakeholders in the academic publishing process to examine how journals enforce data archiving policies. We specifically sought to establish who editors and other stakeholders perceive as responsible for ensuring data completeness and quality in the peer review process. Our analysis revealed little consensus with regard to how data archiving policies should be enforced and who should hold authors accountable for dataset submissions. Themes in interviewee responses included hopefulness that reviewers would take the initiative to review datasets and trust in authors to ensure the completeness and quality of their datasets. We highlight problematic aspects of these thematic responses and offer potential starting points for improvement of the public data archiving process., 35 pages, 1 figure, 1 table

In recent years, there is growing interest in the ways the European aviation industry can leverage the multi-source data fusion towards augmented domain intelligence. However, privacy, legal and organisational policies together with technical limitations, hinder data sharing and, thus, its benefits. The current paper presents the ICARUS data policy and assets brokerage framework, which aims to (a) formalise the data attributes and qualities that affect how aviation data assets can be shared and handled subsequently to their acquisition, including licenses, IPR, characterisation of sensitivity and privacy risks, and (b) enable the creation of machine-processable data contracts for the aviation industry. This involves expressing contractual terms pertaining to data trading agreements into a machine-processable language and supporting the diverse interactions among stakeholders in aviation data sharing scenarios through a trusted and robust system based on the Ethereum platform.

Background Many scholarly journals have established their own data-related policies, which specify their enforcement of data sharing, the types of data to be submitted, and their procedures for making data available. However, except for the journal impact factor and the subject area, the factors associated with the overall strength of the data sharing policies of scholarly journals remain unknown. This study examines how factors, including impact factor, subject area, type of journal publisher, and geographical location of the publisher are related to the strength of the data sharing policy. Methods From each of the 178 categories of the Web of Science’s 2017 edition of Journal Citation Reports, the top journals in each quartile (Q1, Q2, Q3, and Q4) were selected in December 2018. Of the resulting 709 journals (5%), 700 in the fields of life, health, and physical sciences were selected for analysis. Four of the authors independently reviewed the results of the journal website searches, categorized the journals’ data sharing policies, and extracted the characteristics of individual journals. Univariable multinomial logistic regression analyses were initially conducted to determine whether there was a relationship between each factor and the strength of the data sharing policy. Based on the univariable analyses, a multivariable model was performed to further investigate the factors related to the presence and/or strength of the policy. Results Of the 700 journals, 308 (44.0%) had no data sharing policy, 125 (17.9%) had a weak policy, and 267 (38.1%) had a strong policy (expecting or mandating data sharing). The impact factor quartile was positively associated with the strength of the data sharing policies. Physical science journals were less likely to have a strong policy relative to a weak policy than Life science journals (relative risk ratio [RRR], 0.36; 95% CI [0.17–0.78]). Life science journals had a greater probability of having a weak policy relative to no policy than health science journals (RRR, 2.73; 95% CI [1.05–7.14]). Commercial publishers were more likely to have a weak policy relative to no policy than non-commercial publishers (RRR, 7.87; 95% CI, [3.98–15.57]). Journals by publishers in Europe, including the majority of those located in the United Kingdom and the Netherlands, were more likely to have a strong data sharing policy than a weak policy (RRR, 2.99; 95% CI [1.85–4.81]). Conclusions These findings may account for the increase in commercial publishers’ engagement in data sharing and indicate that European national initiatives that encourage and mandate data sharing may influence the presence of a strong policy in the associated journals. Future research needs to explore the factors associated with varied degrees in the strength of a data sharing policy as well as more diverse characteristics of journals related to the policy strength.

An output of the Data policy standardisation and implementation Interest Group (IG) of the Research Data Alliance (RDA) More journals and publishers – and funding agencies and institutions – are introducing research data policies. But as the prevalence of policies increases, there is potential to confuse researchers and support staff with numerous or conflicting policy requirements. We define and describe 14 features of journal research data policies and arrange these into a set of six standard policy types or tiers, which can be adopted by journals and publishers to promote data sharing in a way that encourages good practice and is appropriate for their audience’s perceived needs. Policy features include coverage of topics such as data citation, data repositories, data availability statements, data standards and formats, and peer review of research data. These policy features and types have been created by reviewing the policies of multiple scholarly publishers, which collectively publish more than 10,000 journals, and through discussions and consensus building with multiple stakeholders in research data policy via the Data Policy Standardisation and Implementation Interest Group of the Research Data Alliance. Implementation guidelines for the standard research data policies for journals and publishers are also provided, along with template policy texts which can be implemented by journals in their Information for Authors and publishing workflows. We conclude with a call for collaboration across the scholarly publishing and wider research community to drive further implementation and adoption of consistent research data policies. Publisher's Note: a correction article relating to this publication has been published and can be found at http://doi.org/10.5334/dsj-2020-017

The majority of publications across many disciplines in biology do not make their data available in repositories. On the other hand, there are several advantages associated with archiving data in open access repositories, and technological resources are available to do so. To date, no study has estimated the frequency of data from animal behaviour publications made available in digital repositories or supplementary materials. To evaluate how much data from those studies are available, we surveyed publications from two well-known journals in the field. Since journal policy is an important factor influencing the availability of data from publications, we list the data policy of each journal that publishes animal behaviour research. We found that only a small proportion of the articles published in 2013 made even part of their data available and that journals do not require data to be archived prior to or after publication. If not deposited in repositories, data supporting those findings will most likely be lost from lack of usage, inability to access obsolete storage devices or even the death of the authors. Although it is difficult to appreciate the relevance of data for future studies at the time of a research article's publication, such data may inspire fruitful opportunities that we cannot afford to lose. We discuss the benefits of making data available, review resources for data archiving and provide practical guidelines. We hope that raising awareness about this problem will help foster a data-sharing culture among animal behaviourists.

The main message of the JERICO-NEXT data policyisthat data produced within the project isfree and unrestricted with no charge for third parties. The JERICO-NEXT Data Policy provides recommendations on ownership, to which data these recommendations are applied, DOI, data citationand the main recommendations on data sharing and dissemination principles. Deliverable 5.1is embedded within Work Package 5 (Data management). One main objective of this Work Package is to provide procedures and methodologies to enable data collectedthrough the project to comply with international standards regarding their quality and metadata Published Contributors: A.Novellino; P. Fernandez Refereed Current 14 TRL 9 Actual system "mission proven" through successful mission operations (ground or space) Best Practice Manual (incl. handbook, guide, cookbook etc)

Purpose – Data sharing is key for replication and re-use in empirical research. Scientific journals can play a central role by establishing data policies and providing technologies. The purpose of this paper is to analyses the factors which influence data sharing by investigating journal data policies and the behaviour of authors in sociology. Design/methodology/approach – The web sites of 140 sociology journals were consulted to check their data policy. The results are compared with similar studies from political science and economics. A broad selection of articles published in five selected journals over a period of two years are examined to determine whether authors really cite and share their data and the factors which are related to this. Findings – Although only a few sociology journals have explicit data policies, most journals make reference to a common policy supplied by their association of publishers. Among the journals selected, relatively few articles provide data citations and even fewer make data available – this is true both for journals with and without a data policy. But authors writing for journals with higher impact factors and with data policies are more likely to cite data and to make it really accessible. Originality/value – No study of journal data policies has been undertaken to date for the domain of sociology. A comparison of authors’ behaviours regarding data availability, data citation, and data accessibility for journals with or without a data policy provides useful information about the factors which improve data sharing.

Global change has a significant impact on the lives of humankind. Earth observation can help to better understand our earth and cope with global change. With the availability of more reliable environmental data sets, digital earth is becoming a popular way to monitor the Earth and provide information to researchers and decision makers on environment protection, disaster mitigation, and social benefits. Therefore, accessing data with lowering costs is essential for digital earth. Nevertheless, there are big challenges in ensuring the feasibility of access to Chinese remote sensing data. This paper outlines some of the main challenges in realizing data sharing, provides an analysis of the core reasons leading to these challenges, and proposes recommendations to overcome the challenges. Amongst the main challenges are differences in data policy to gain access to satellite data, diverse data formats, and delivery mechanisms. The major challenge for the decision makers is to define a more open policy and for t...

Managing interest in collaborative data sharing involves determining interest of both owner and other parties. Interest management method is bound to information such as user request, location, history, preferences and data policies. Considering other researchers' works, managing data interest of sharing for its' constitutional adhered policy are rarely done in computerize manner. With attention that data shared are constituted with policy implicitly or explicitly, this paper proposes an automatic design of data policy via policy programming language in order to handle interest management. The study starts by analyzing secondary data through massive literature reviews. Two pertinent issues on interest management and data policy are explored, analyzed and summarized. Based on the research gap found in these analyses, an interest management for automated data policy is designed. As a case study, a new set of programming constructs are implemented and embedded into an existing collaborative language called JACIE (Java-based Authoring language for Collaborative Interactive Environments) that acts as a policy programming language. The results of this study conform that automated data policy is feasible and functioning well. Thus, this helps an interest manager to have flexible data policy in handling collaborative activities.

The field of global health is evolving and moving forward from not just securing open access publication toaid in the dissemination of research but further still,making the data underpinning the results of that publication open. Funders1 in the field, and recently theInternational Committee of Medical Journal Editors(ICMJE) [1], are increasingly requiring that researchersmake data produced during their grants publiclyaccessible.Although the push for more data sharing and transparency started with the genomics community, it is quicklyspreading to the global health communities. Indeed, twomajor organisations in the field have already set up a stronginfrastructure for data reuse and sharing. Many of us arealready familiar with the power of open data through theWHO Global Health Observatory Data Repository [2] andthe World Bank Open Data Catalogue [3], both of whichare invaluable resources. In February 2016 the WellcomeTrust also joined ?over 30 global health bodies in calling forall research data gathered during the Zika virus outbreak,and future public health emergencies, to be made availableas rapidly and openly as possible? [4]. This follows a consensus statement arising from a WHO consultation in September 2015 moving towards making this the global norm [5].Reproductive Health wants to help spearhead thisparadigm shift to ensure all data underlying the researchpublished within the journal is publicly available to ensure transparency of research and contribute to enhancing research in the field. Fil: Salaria, Natasha. No especifíca; Fil: Kenall, Amye. No especifíca; Fil: Belizan, Jose. Instituto de Efectividad Clínica y Sanitaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Este trabalho objetiva analisar a autoria científica a partir do compartilhamento de dados de pesquisa. Para esta finalidade, utiliza a Teoria Ator-Rede (ANT), a qual busca, a partir de uma ideia de simetria entre humanos e nõ humanos, não assumir uma divisão entre essas entidades, possibilitando visualizar o estabelecimento e a dissolução de uma rede a partir das relações que se criam em diversos níveis. Os dados que serviram de base para descrição e análise a partir da literatura foram recolhidos a partir de observação, de entrevistas e de materiais bibliográficos. A investigação ocorreu junto ao Repositório de Dados de Estudo Ecológicos do Programa de Pesquisa em Biodiversidade (PPBio). Conclui que os objetos conceituais e pragmáticos não podem ser vistos de maneira isolada, mas sim como atores-rede afetados diretamente pela tecnologia, devendo ser considerados atuantes importantes no processo de produção, compartilhamento e uso de dados digitais de pesquisa. A construção do fato científico e social autoria é coordenada por uma série de elementos, como a coleta de dados, a curadoria, os próprios dados científicos, seus metadados, as fontes de fomento, a política de dados, o repositório e seus softwares de gerenciamento e envio de dados e metadados, o licenciamento, a propriedade e a responsabilidade, agindo como um tipo de instrumentalização de um arranjo de fenômenos. This work aims to analyze the scientific authorship from the data sharing. For this purpose, it uses the Actor-Network Theory (ANT), which seeks, from an idea of symmetry between human and non-human, do not assume a division between those entities, allowing to view the establishment and dissolution of a network from the relationships that are created at different levels. The data collected, which were the basis for description and analysis from the literature that also emerged from what ware collected by observation, interviews and bibliographic materials. The study was carried out by the Repositório de Dados de Estudo Ecológicos do Programa de Pesquisa em Biodiversidade (PPBio). Concludes that conceptual and pragmatic objects can not be seen in isolate way, but like actors directly affected by the technology, should be considered important actants in the process of production, sharing and use of digital research data. The construction of scientific and social fact authorship is coordinated by a number of elements, such as data collection, curation, scientific data and its metadata, funding sources, data policy, repository and its management software for data and metadata, licensing, ownership and responsibility, acting like a kind of exploitation of a phenomena arrangement. Este estudio tiene como objetivo analizar los autores científicos de intercambio de datos de la encuesta. Con este fin, utilizar la teoría del actor-red (ANT), que busca, a partir de una idea de simetría entre el ser humano y no humano, no asuma una división entre esas entidades, lo que permite ver la creación y disolución de una red a partir de las relaciones que se crean en los distintos niveles. Los datos que sirvieron de base para la descripción y el análisis de la literatura se obtuvieron de observación, entrevistas y material bibliográfico. La investigación se llevó a cabo en el Programa de Investigación Ecológica depósito de datos de investigación sobre la biodiversidad (PPBio). Se llega a la conclusión de que los objetos conceptuales y pragmáticos no pueden verse de manera aislada sino como afectados network-actores directamente por la tecnología, y debe considerarse importante en el proceso de producción activa, el intercambio y uso de los datos digitales de investigación. La construcción de los hechos científicos y la autoría social está coordinado por una serie de elementos, tales como la recopilación de datos, curación, propios datos científicos, sus metadatos, las fuentes de desarrollo, la política de datos, el repositorio y su software de gestión y el envío de datos y metadatos, la concesión de licencias, la propiedad y la responsabilidad al actuar como una especie de instrumentalización de una disposición de fenómenos.

Sharing scientific data sharing about water resources is an indispensable component of national fundamental data-sharing construction and the science and technology innovation system. To implement data sharing about water resources, which covers a broad extent and a great variety of data, is a difficult task because of the technical complexity and, more critically, non-technical factors, such as data policy, standards, and sharing circumstances. In this paper, the status of water resources scientific data sharing is analyzed at home and abroad, and some concepts are presented regarding these analyses. Using data from the Scientific Data Sharing Project, the authors study the system of data sharing about water resources and propose technological standards and managing and servicing systems of data sharing of water resources for the public as well as for the scientific research sectors of the nation.

The LifeWatchGreece Research Infrastructure (LWG RI) stores biodiversity data and information from all biology-related disciplines derived from the Greek territory (or the Mediterranean Sea for the marine data). The aim of LWG RI is to facilitate data sharing and dissemination under harmonised standards in order to maximize the socio-economic benefits of research and knowledge transfer to the public. This publication describes the rationale behind the data policy of LWG RI, outlines the current legal situation for sharing research data and presents the Data Sharing Agreement which is signed between the data owner/provider and the LWG RI for each dataset, describing in detail the rights and duties of each party, as well as the license type and the embargo period under which the data are released.

"Large-scale data policies easily may have unplanned effects of 'homogeneity' on the available data supply. A narrowing of the scope of the data supply tailored to established research paradigms could limit the opportunities for unconventional, but also adventurous, new research directions with the risk of slowing down scientific progress. A systematic assessment of data portfolios not only on the aspects of quality, accessibility and sustainability, but diversity as well, could help to diminish this risk."

There are thousands of biology databases with hundreds of terminologies, reporting guidelines, representations models, and exchange formats to help annotate, report, and share bioscience investigations. It is evident, however, that researchers and bioinformaticians struggle to navigate the various standards and to find the appropriate database to collect, manage, and share data. Further, policy makers, funders, and publishers lack sufficient information to formulate their guidelines. In this paper, we highlight a number of key issues that can be used to turn these challenges into new opportunities. It is time for all stakeholders to work together to reconcile cause and effect and make the data-sharing culture functional and efficient.