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This presentation has been given the 7th of June 2023 at the last INFO/RAC National Focal Points meetingand it has beenalready presented in some bilateral meetings with the Contracting Parties(https://doi.org/10.5281/zenodo.7645445), but it is reported here with an homongeneized stylization after the entire meeting slides. Itdescribes the implications of the UNEP-MAP Data Policy for the Contracting Parties. The presentationis related to the document "MAP Data Policy – Implications for the Contracting Parties(UNEP/MED WG.566/Inf. 7)".

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)".

This presentation has been given the 7th of June 2023 at the last INFO/RAC National Focal Points meetinganddetails the UNEP-MAP Data Policy application rules for each mandatory and not mandatory data flow. The presentationis related to the documents "Data Policy Annex on Barcelona Convention Reporting System (BCRS) data flow(UNEP/MED WG.566/6)", "Data Policy Annex on National Baseline Budget (NBB) data flow (UNEP/MED WG.566/7)", "Data Policy Annex on IMAP data flow (UNEP/MED WG.566/8)" and "Data Policy Annex on InfoMAP Node data flow (UNEP/MED WG.566/9)".

The first policy paper offers a conceptual framework to address the elusive economics of data and a decalogue for policymakers to optimize the value of data flows,highlighting the need for tailored approaches based on data's utility function.

Policies communicate expectations to stakeholders, codify legal and administrative procedures, and espouse underlying values. However, often moving from policy to actual practice requires interpretation, the development of new procedures, and has various resource implications. In the United States, the federal government has been expanding policies related to the management and sharing of research data with the NIH Data Management and Sharing policy in effect as of January 2023 and other agencies developing and revising policies in response to the recent “Nelson” OSTP memo on immediate and equitable access to research. At Duke University, the research administration has also been working to implement a new institutionally-based research data policy. As information professionals situated within a library part of our role is to help researchers navigate this changing policy landscape. Likewise, we are stakeholders when considering the development of resources and services to support policy implementation. We may also take on the role of advocates for values we hold, such as the value of openness or equity in the research enterprise. How can we balance these different roles? What are some common challenges or pitfalls? What makes the library’s position in this policy space unique? In this presentation, we will share some reflections from our recent experiences at Duke navigating this complex landscape and engage the audience in a discussion about their experiences.

The International Science Council (ISC, formerly ICSU and ISSC) is the parent body of SCAR. In its Assessment on Scientific Data and Information in 2004, the ISC observed that “science has long been best served by a system of minimal constraints on the availability of data and information”, and that a strong public domain for scientific data and information promotes greater return from investment in research, stimulates innovation and enables more informed decision-making. Thus, one of the fundamental recommendations of the assessment is that “ICSU should continue to actively promote the principle of full and open access to scientific data”. Additionally, countries working in the Antarctic operate within the framework of the Antarctic Treaty System. The cornerstone of the system is the Antarctic Treaty, which was signed on December 1, 1959, and came into effect on June 23, 1961. Of particular relevance for polar data management and delivery is Article III, section 1(c), which stipulates that “scientific observations and results from Antarctica shall be exchanged and made freely available”. This Article has been followed up by ATCM Resolutions, such as: ATCM Recommendation XIII-5 (1985), which invites SCAR to offer advice “on steps that possibly could be taken to improve the comparability and accessibility of scientific data on Antarctica.” ATCM XXII Resolution 4 (1998), which recommends that Consultative Parties establish National Antarctic Data Centres and link these to the Antarctic Data Directory, and that they give priority consideration as to how the requirement for freedom of access to scientific information is achieved within their national data management systems. Effective data management is a critical part of operating responsibly within the Antarctic environment, and it is essential that SCAR is able to provide clear guidance to researchers and research programmes on data management requirements. In 2019, theStanding Committee on Antarctic Data Management (SCADM)initiated a process to align the data policies of international scientific bodies coordinating research in the polar regions. Following this, a working group under SCADM, SOOS, IASC, SAON, and the Arctic SDI published the report “Alignment of Polar Data Policies - Recommended Principles'' in November 2021 (DOI:10.5281/zenodo.5734900). The report examines external policy drivers and overarching global and regional data policies, notably those of the Antarctic Treaty, ISC, UNESCO, WMO, IOC, UN-GGIM, OECD, and GEO, and concludes by recommending and explaining ten fundamental principles for polar data policies. This data policy is based on those ten principles.

A sustainability sheet for the Photon and Neutron FAIR implementation framework after the ExPaNDS project, reporting in a condensed manner on the following items: Description of the framework, its target audience, its benefits Accessibility, including links to relevant documentation and feedback mechanism Competitors, TRL and EOSC integration status Plans for sustainability Exploitability potential and associated actions The source document is available for comments or reproducibility here.

WorldFAIR and a Festival of Data, looks back on 2022 and forward to 2023. It provides a report onCODATA activities and achievements and highlights the most important upcoming events. 2022 has been another busy and successful year for the CODATA community. We are very grateful for your committed collaboration and engagement with our mission. As a global, membership organisation, CODATA depends on the generosity of our funders and collaborators and the often voluntary efforts of committee, Task Group and Working Group members. In 2023, the International Data Week theme will be ‘a festival of data’ and an occasion to celebrate the richness and diversity of our community. That starts with this expression of gratitude. We are very fortunate to have an extremely committed group of Officers and Executive Committee members, dynamic leadership throughout our various initiatives and a secretariat that works beyond the call of duty. Through all these factors, and more, CODATA is genuinely greater than the sum of its parts and achieves a great deal more than our budget would suggest. As is customary, we would like to provide a summary of activities and achievements and take the opportunity to alert you to events in the coming year. This is a genuinely exciting time, as we see the vision for a Decadal Programme on Making Data Work for Cross-Domain Grand Challenges begin to come into fruition with the WorldFAIR project, a set of related Case Studies, and important work on units, vocabularies and a Cross-Domain Interoperability Framework. Also notable is new impetus and direction for our International Data Policy Committee and the new International Programme Office to support the Open Science initiatives. The report published here ended up a bit longer than intended! I hope it provides an informative and interesting snapshot of CODATA activities. An updated version and a revised CODATA Strategy will be published in 2023 in preparation for our General Assembly, Salzburg, Austria, 27-28 October.

Preprint of a paper submitted to Gigascience. Abstract:The relationship between people, place, and data underpins some of the greatest challenges and opportunities of the 21st century. While there has been general enthusiasm for and work towards Findable, Accessible, Interoperable, and Reusable (FAIR) data for Open Science, only more recently have these data-centric principles been extended into dimensions important to people and place. Notably, the CARE Principles for Indigenous Data Governance, which affect collective benefit, authority to control, responsibility, and ethics. The FAIR Island Project seeks to translate these ideals into practice leveraging the institutional infrastructure provided by scientific field stations. Starting with field stations in French Polynesia as key use cases that are exceptionally well connected to international research networks, FAIR Island builds interoperability between different components of critical research infrastructure, helping connect these to societal benefit areas. The goal is not only to increase reuse of scientific data and the awareness of work happening at the field stations, but more generally to accelerate place-based research for sustainable development. FAIR Island works reflexively, aiming to scale horizontally through networks of field stations and to serve as a model for other sites of intensive long-term scientific study.

This paper explores the particular issues raised by public sector access to and use of personal data held by the private sector. It adopts a legal perspective which considers how such data sharing is legally enabled and within what parameters. Given that legal frameworks for data sharing may not always keep pace with data needs and methods, this paper also takes a normative approach which examines whether and in what circumstances such data sharing should take place.

The Generic Place-based data policy is a template derived from the draft Tetiaroa Ecostation Data Policy and meant to be an example for other field stations, marine labs and research stations that may want to use it. V1.0.0 is the first official release of the Generic Place-based Data Policy. That includes significant community feedback on theV0.0.0from February 2021 through June 2022. V1.0.2 includes the correct DOI and citation. It also includes Hypothes.is in the Github HTML for additional annotations. Access the website here:https://fairislandproject.github.io/Generic-Place-based-Data-Policy/GenericPlacebasedDataPolicy.html&nbsp

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.

Announcement / press release for the launch of EC WIDERA-funded project WorldFAIR: Global cooperation on FAIR data policy and practice, 1 June 2022. WorldFAIR is funded by HORIZON-WIDERA-2021-ERA-01-41 HORIZON Coordination and Support Action.

The existence of FAIR-aligned and harmonised data policies across various stakeholders such as funding bodies, publishers and Research Performing Organisations (RPOs) is crucial for ensuring that we can progress from a vision of the European Open Science Cloud (EOSC) to it becoming a fully functioning reality. As noted in the Turning FAIR into Reality report and action plan, policies define and regulate various components of a FAIR ecosystem and the relationships between them. Indeed, policies are a cross-cutting theme in Turning FAIR into Reality (TFiR) and are reflected in many of the priority and supporting actions presented in the action plan. This guide aims to help Research Performing Organisations to assess the data policy framework currently in place and to consider where possible improvements may be needed. To complement the guide, a FAIRsFAIR policy support checklist will be available. This aims to help RPOs to consider the content of their data policy, and how they might better align it with the FAIR Principles. ACME-FAIR is a 7-part guide developed in the FAIRsFAIR project, whose main purpose is to help managers of Research Data Management and related professional services to self-assess how they are enabling researchers, and the professional staff who support them, to put the FAIR data principles into practice (for short we refer to this as ‘FAIR-enabling practice’). This part addresses the key issue of Defining the FAIR data policy environment. Please give us your comments in any of the ways detailed on p.5.

By creating and sharing a structured version of your data policy, you are helping to ensure that your policy is itself findable, accessible, interoperable and reusable (FAIR). You will also help make ongoing assessments of the policy landscape such as those outlined in the EOSC Strategic Research and Innovation Agenda (SRIA)more comparable and efficient. This guide walks users through creating a structured version of their data policy using the FAIRsFAIR policy structured description template (https://doi.org/10.5281/zenodo.6225938) and suggests how they can make this structured description accessible. &nbsp

This spreadsheet presents the list of the policy elements assessed in the FAIR data policy checklist and allows policy makers to characterise their policies against each using standard set of options.By creating structured descriptions, depositing them with a repository, and making them visible through registry services, the community can support a more efficient and comparable means of assessing the policy landscape over time such as that envisaged by the EOSC Strategic Research and Innovation Agenda (https://www.eosc.eu/sria). FAIRsFAIR has developed guidance to help policy makers to work through the process (Creating and Sharing Structured Policy Descriptions - a step by step guide (1.0). Zenodo. https://doi.org/10.5281/zenodo.6281105). &nbsp

The text of this ExPaNDS Guidance Note is extracted from ExPaNDS deliverable D2.3: Final data policy framework for Photon and Neutron RIs. The Guidance Note covers the 21 elements that comprise the final version of the ExPaNDS data policy framework. These elements fall under nine broad themes: General drivers and principles Roles and responsibilities Scope Enabling FAIR data Necessary restrictions to data sharing Availability of infrastructure and responsibility for costs Data management planning requirements Recognition and reward for data usage Reporting requirements, compliance monitoring, and any possible sanctions The Guidance Note is intended as a short-form, ready-access tool for policy makers working on data policy within Photon and Neutron Research Infrastructures. For additional context around the development of the ExPaNDS data policy framework, see the D2.3 deliverable and its earlier, draft version D2.1: Draft extended data policy framework for photon and neutron RIs.

The purpose of this document is to identify roles and requirements relating to the management of data and information collected in the Southern Ocean. As SOOS acts through the cooperative collaboration of many nations, institutions, and scientific disciplines, this policy aims to promote best practices amongst SOOS-aligned activities. This policy primarily relates to publicly funded research, but, where commercially acquired data is shared with the public, the guidance in this policy should apply. This version 02/2022 (10.5281/zenodo.6041433)will supersede the previous version (10.5281/zenodo.3973733).&nbsp

The Generic Place-Based Research Data Policy is a template developed from the Tetiaroa Society Research Data Policy for the Tetiaroa Ecostation. This template is meant to be an evolving, starting point for other field stations&nbsp

This document presents a basis for alignment of polar data policies, notably the policies and statements of the Scientific Committee on Antarctic Research (SCAR), the International Arctic Science Committee (IASC), the Sustaining Arctic Observing Networks (SAON) initiative, the Arctic Spatial Data Infrastructure, and the Southern Ocean Observing System (SOOS). The document examines the state and recent developments of global and important regional data policies, as well as technological and institutional developments that should or might be considered when forming new polar data policies. Based on this examination, we conclude by identifying a number of data management principles that can be regarded as essential to the management of polar research data and can be incorporated in all polar data policies in such a way that they are aligned with each other and with overarching global and regional data policies.

This document presents progress in adopting or adapting existing data management policies to the PaNOSC data policy framework. This deliverable has been coordinated by CERIC-ERIC and ELI and prepared in collaboration with all the PaNOSC partners. In May 2020, the PaNOSC data policy framework was delivered to the European Commission as a deliverable of the PaNOSC project. It was published on zenodo (DOI 10.5281/zenodo.3826040) and is also accessible via the PaNOSC website. Now, after two years from the beginning of the project, ELI and CERIC are going to adopt the data policy and the other partners are adapting their existing policies to be compatible with the PaNOSC Data Policy framework. This document aims to provide a clear picture of the status of this process and what the next steps are for each partner in order to get the data policies endorsed by their management and operating in the real scientific data management workflow.

ExPaNDS deliverable D2.3: Final data policy framework for photon and neutron RIs, considers how data policies for research infrastructures providing photon and neutron facilities should be framed, in particular in the light of supporting open science and FAIR data. It builds on and revises the initial policy framework presented in ExPaNDS deliverable D2.1: Draft extended data policy framework for photon and neutron RIs. To produce the final, revised version of our data policy framework, ExPaNDS undertook a series of detailed consultation meetings with all ten of our partner PaN RIs. Drawing extensively on quotes from the write ups of those conversations, this report presents the themes that emerged from the consultation, focusing especially on those that featured most often and most strongly. Based on the consultation feedback, we present a revised version of the ExPaNDS data policy framework, which now proposes 21 elements for RIs to consider when formulating data policy. Overall, the consultation provided an opportunity to engage deeply in discussion with ExPaNDS partners about data policy and policy making. The consultation feedback and the level of engagement with the consultation process itself highlight ExPaNDS partners’ strong interest in data policy. There is a clear recognition that having an appropriate data policy is fundamental to supporting good research data management. While some differing views exist, ExPaNDS partners express consensus on key fundamental aspects of the data policy framework, especially the importance of a high level commitment to FAIR data. There is also the strong recognition that flexibility in a data policy framework is vital to accommodating the diversity found across national PaN RIs. As well as incorporating the final version ExPaNDS data policy framework as a key output, our report concludes with two overarching points: Data policy diversity will remain across ExPaNDS partner facilities Data policy is a powerful and important tool for national PaN RIs. It is clear from the consultation feedback that the ExPaNDS data policy framework is already having an impact on facilities’ plans for future work, especially around ensuring that key implementations are in place to support FAIR data. Further work within ExPaNDS, for example, around PIDs, metadata, and FAIR assessment, will provide guidance to support these activities.

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.

A set of Guidelines on how to implement a research data policy at Photon and Neutron (PaN) sources and at Research Infrastructures (RI) in general. The document is organised as a set of annotated guidelines based on the experience of six PaN institutes who have either already implemented a data policy or are in the process of implementing a data policy. The 6 institutes are - ESRF, ILL, EuXFEL, ESS, CERIC-ERIC and ELI. They are all members of the PaNOSC project.

Increasing the availability of research data for reuse is in part being driven by research data policies. While the number of research funders, journals and institutions with some form of research data policy is growing, the landscape is complex and therefore the implementation and implications of policies for researchers can be unclear, confusing and sometimes even contradictory. The RDA Data Policy Standardisation and Implementation IG was established to help address these challenges. Initially the Group focussed on Developing a Research Data Policy Framework for All Journals and Publishers and with journal adoptions of the framework growing, the Group is now focussing on alignment between publishers and funders. This session provided an overview of the joint session held at RDA P17 of the Research Funders and Stakeholders on Open Research and Data Management and Practices IG, the Data Policy Standardisation and Implementation IG and the FAIRsharing WG. The focus of this RDA VP17 session was to provide an overview of a joint project to examine funder-publisher policy alignment and provide recommendations on how to improve alignment., Session held as part of the Research Data Alliance VP17 Regional Virtual event

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.

This presentation was given as part of the FAIRsFAIR-CODATA-RDA Data Steward Training Series which was held virtually on 11 December 2020 with the National University of Costa Rica. The session explored issues to be considered when developing Research Data Management policies and related support services. The session aimed to ensure that participants were: • able to develop realistic and well scoped RDM policies • aware of free resources that are available to help build capacity for RDM service delivery and support This presentation was prepared using materials that have been developed and/or adapted by the Digital Curation Centre (DCC). Attributions to reused open content are provided where relevant in the slides., This presentation was prepared using materials that have been developed and/or adapted by the Digital Curation Centre (DCC). Attributions to reused open content are provided where relevant in the slides.

This report describes the Data Management Plan (DMP) for the CarE-Service Project. The report aims at establishing the policy framework for information management and confidentiality within the CarE-Service consortium, the members of the Consumers’ and Stakeholders Committees, as well as external stakeholders. The policy framework for data management includes principles ensuring the effective management and confidentiality of data, information and records throughout the related authorities and responsibilities. The main purpose of the data/information management policy is to protect both electronic and paper-version of data/information from any unauthorized use and access with a clear role and responsibilities of those who manage the data/information, while ensuring the greatest possible access of data/information, consistent with legislation and relevant EU/consortium policies. Detailed information will be provided on the procedures that will be implemented for data collection, storage, protection, retention and destruction and confirmation that they comply with national (eg. Bundesdatenschutzgesetz (BDSG) for Germany) and EU legislation (Regulation (EU) 2016/679 (General Data Protection Regulation)). The DMP describes the data management life cycle for the data to be collected, processed and/or generated by CarE-Service Horizon 2020 project. As part of making research data findable, accessible, interoperable and re-usable (FAIR), the DMP includes information on: the handling of research data during & after the end of the project what data will be collected, processed and/or generated which methodology & standards will be applied whether data will be shared/made open access and how data will be curated & preserved (including after the end of the project).

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.

Research Infrastructures within the Photon and Neutron science community have a significant track record in publishing and implementing data policies to support the access and use of experimental data generated by the user. Recent developments within European science policy, in particular the drive towards supporting FAIR data in the European Open Science Cloud has meant that it is timely to review and revise these data policies. The PaNOSC project has developed a new PaNOSC Data Policy Framework with the contribution of ExPaNDS partners. The aim of this Deliverable 2.1: Draft extended data policy framework for photon and neutron research infrastructures is to reflect upon and extend that work. We review the FAIR data policy landscape at European and national levels, consider the current state of data policy adoption and implementation at ExPaNDS partner facilities, and examine existing FAIR ecosystem data policy recommendations, in particular, from the Turning FAIR into reality report and the recent FAIRsFAIR Deliverable 3.3: Policy enhancement recommendations In response, we make twenty-six recommendations of our own that serve to translate these recommendations to the local level of photon and neutron research infrastructures. As the report’s key output, we present thirty elements that should inform a data policy framework for photon and neutron research infrastructures. These focus on enabling FAIR data and are those elements about which RIs need to make choices — both on the level of commitments that they themselves are prepared to make as well as with regards to the obligations that they will place on users. We conclude with some next steps that will inform the final version of this deliverable: D2.3 Final data policy for photon and neutron research.&nbsp

Open Science for a Global Transformation: CODATA coordinated submission to the UNESCO Open Science Consultation UNESCO is preparing aRecommendation on Open Scienceto be adopted by Member States in 2021. To contribute to this process, UNESCO launched aglobal consultation gathering inputs from all regions and all interested stakeholders, through online consultations, regional and thematic meetings and numerous debates on implications, benefits and challenges of Open Science across the globe. Input via an online consultation was requested by 15 June andCODATAwas invited by the UNESCO Open Science team to present a detailed submission. Following exchanges on theCODATA International Discussion list CODATA agreed to coordinate a joint response from a number of data and information organisations. That document—Open Science for a Global Transformation—was submitted to UNESCO on 15 June and, following minor editorial adjustments, is now published here. Open Science is best characterised as the necessary transformation of scientific practice to adapt to the changes, challenges and opportunities of the 21st century digital era to advance knowledge and to improve our world. This requires changes in scientific culture, methodologies, institutions and infrastructures. These changes are already present in many research domains and institutions, where their transformative effects can be witnessed, but they are unevenly distributed. One of the purposes of Open Science viewed as a call for transformation, is to ensure that ‘no-one is left behind’. Open Science for a Global Transformation was prepared by an expert group, coordinated byCODATA and including representatives from theISC World Data System (WDS),GO FAIRand theInternational Council for Scientific and Technical Information (ICSTI) These global data and information organisations have responsibilities for policy advice and promoting collaborations in relation to data and information; they are advocates of Open Science and are convinced of its necessity and benefits. The organisations believe—fundamentally—that it is important to win hearts and minds, to significantly transform science policy and practice, in order to facilitate the application of the technologies and methodologies associated with Open Science to improve our world and address global challenges. Open Science requires policy interventions and investments to ensure equitable participation and access to its benefits and to mitigate some negative consequences. The perspective brought by these organisations lays particular emphasis on maximising appropriate access to (re-)usable data. The Expert Group comprised: Paul Arthur Berkman, Founding Director, Science Diplomacy Center, Professor of Practice in Science Diplomacy, Fletcher School of Law and Diplomacy, Tufts University; Associated Fellow, United Nations Institute for Training and Research (UNITAR); Member of the CODATA Data Policy Committee. Jan Brase, head of the Research and Development at the State and University Library, Göttingen; President of ICSTI. Richard Hartshorn, Professor, School of Physical and Chemical Sciences, University of Canterbury; Secretary General of the International Union of Pure and Applied Chemistry; member of the CODATA Executive Committee. Simon Hodson, Executive Director, CODATA. Wim Hugo, Director of Strategy, ISC World Data System. Sabina Leonelli, Turing Fellow and Professor in Philosophy and History of Science, University of Exeter. Barend Mons, Professor in Biosemantics, Leiden University Medical Center; President of CODATA; Director GO FAIR International Support and Coordination Office. Hana Pergl, Operations Manager, CODATA. Hans Pfeiffenberger, Consultant, scientific data infrastructures and policies, Member of the CODATA Data Policy Committee, founder and member of the advisory board of Earth Systems Science Data.

The document defines the policy and the rules for sharing and accessing data produced by the Italian Long-Term Ecological Research (LTER-Italy) network. The policy aims at ensuring the diffusion of ecological data, making them as much “FAIR” (Findable, Accessible, Interoperable, and Reusable) as possible within the scientific community and the generic public.

This is a general presentation of the IPBES data management policy prepared for the experts of the ongoing assessments.

The 'CODATA Achievements and Activities Report 2019-2020'provides a quick listing of important CODATA activities for 2020and then highlights some keyachievements of 2019.

Background Emerging states, such as Brazil, India, and China (the BICs), have big plans for big data and digitalization. Research has identified distinct policy visions regarding how technological advances can facilitate economic development and improve governance. Analysis This article examines how BIC governments frame data-driven ambitions across the diverse issue areas in which governments plan to use big data, as well as how they frame the role(s) of the government and citizens in the era of big data. Conclusion and implications We find clear differences in discussions of big data across the BICs and across issue areas. Moreover, we show the societal changes that governments seek to effect using big data vary greatly in scope, with Brazil and India seeking more fundamental changes than China. Contexte Les Etats emergents, tels que le Bresil, l’Inde et la Chine (les BIC), ont de grands projets pour Big Data et la numerisation. La recherche a identifie des visions politiques distinctes concernant la facon dont les progres technologiques peuvent faciliter le developpement economique et ameliorer la gouvernance. Analyse Cet article examine la maniere dont les gouvernements BIC definissent les ambitions basees sur les donnees dans les divers domaines problematiques dans lesquels les gouvernements envisagent d’utiliser big data, ainsi que la facon dont ils definissent le ou les roles du gouvernement et des citoyens a l’ere des big data. Conclusion et implications Nous constatons des differences claires dans les discussions sur big data entre les BIC et entre les domaines problematiques. De plus, nous montrons que les changements societaux que les gouvernements cherchent a effectuer en utilisant big data varient considerablement, le Bresil et l’Inde recherchant des changements plus fondamentaux que la Chine.

IPBES DATA MANAGEMENT POLICY Version: 1.1 - December 2020 Revision authors version 1.1:Rainer M. Krug, Joy A. Kumagai, Dave Thau, Debora Pignatari Drucker, Aidin Niamir This revision has been reviewed by IPBES task force on knowledge and data, IPBES Secretariat, and has been approved by the IPBES Multidisciplinary Expert Panel, and IPBES Bureau. Version: 1.0 - January 2020 Drafting authors of version 1.0:Rainer M. Krug, Benedict A. Omare, Wouter Addink, Gregoire Dubois, Cornelia Krug, Howard Nelson, Fatima Parker-Allie, Debora Pignatari Drucker, David Thau, Aidin Niamir Editors: Rainer M. Krug, Benedict Aboki Omare, and Aidin Niamir The version 1.0 has been reviewed by:IPBES task force on knowledge and data, IPBES task force on capacity-building, IPBES task force on indigenous and local knowledge, IPBES task force on policy tools and methodologies, IPBES task force on scenarios and models, and IPBES Secretariat To get the latest version of the policy visit http:/doi.org/10.5281/zenodo.3551078 Inquiries should be directed to tsu.data@ipbes.net

The ExPaNDS project is a collaboration between 10 national Photon and Neutron Research Infrastructures (PaN RIs) as well as EGI. The project aims to deliver standardised, interoperable, and integrated data sources and data analysis services for Photon and Neutron facilities, within the context of the European Open Science Cloud (EOSC). As part of its programme, it is considering how to enable and promote the generation and use of FAIR data within facilities’ processes (work package 2), and the harmonisation of tools and processes for data cataloguing and management (work package 3). WP2 and WP3 are conducting a landscape analysis in order to establish a baseline on the current state of the 10 participating institutions on FAIR data policies and data management practises. This activity can be compared with a similar activity which was undertaken within the PaNOSC project, which covers the transnational (ESFRI) facilities in the same domain. This baseline can then be used to steer the subsequent activity of the project and to assess its impact. This report summarises the results of a survey of the 10 participating institutes which was undertaken in December 2019.

The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) is a collaborative, international project to address pressing scientific questions in the central Arctic. The project’s success, and its ultimate impact on science and society, relies upon professional coordination and data sharing across the participants. A transparent Data Policy is essential to achieve MOSAiC science objectives, to facilitate collaboration, and to enable broad use and impact of the MOSAiC data legacy.

This report describes the Data Management Plan (DMP) for the CarE-Service Project. The report aims at establishing the policy framework for information management and confidentiality within the CarE-Service consortium, the members of the Consumers’ and Stakeholders Committees, as well as external stakeholders. The policy framework for data management includes principles ensuring the effective management and confidentiality of data, information and records throughout the related authorities and responsibilities. The main purpose of the data/information management policy is to protect both electronic and paper-version of data/information from any unauthorized use and access with a clear role and responsibilities of those who manage the data/information, while ensuring the greatest possible access of data/information, consistent with legislation and relevant EU/consortium policies. Detailed information will be provided on the procedures that will be implemented for data collection, storage, protection, retention and destruction and confirmation that they comply with national (eg. Bundesdatenschutzgesetz (BDSG) for Germany) and EU legislation (Regulation (EU) 2016/679 (General Data Protection Regulation)). The DMP describes the data management life cycle for the data to be collected, processed and/or generated by CarE-Service Horizon 2020 project. As part of making research data findable, accessible, interoperable and re-usable (FAIR), the DMP includes information on: the handling of research data during & after the end of the project what data will be collected, processed and/or generated which methodology & standards will be applied whether data will be shared/made open access and how data will be curated & preserved (including after the end of the project).

This document provides a quick and accessible list of CODATA activities, deliverables andimpact fromthe past year. It then highlights some important upcoming activities andevents for 2019.

The nature of science is changing from a closed system to an open and sharing one. It affects virtually all components of doing science and research, and shifts in particular the focus from ‘publishing as fast as possible’ to ‘sharing knowledge as early as possible’. Open science is good for: (i) science itself: it improves efficiency and the verifiability of science, it brings transparency, and it allows inter-disciplinarity; (ii) the economy: with wider access to, and increased re-use of scientific in- formation by all, and in particular, by industry and innovative companies; and (iii) society: it brings broader, faster, transparent and equal access for citizens, and contributes to increased societal impact of science and research. The raison d’être for developing an Open Science Framework for South Africa is the recognition by the Department of Science and Technology (DST) that Open Science is a game changer for South Africa insofar as it seeks to create an ecosystem in which scientific re- search is more cumulative, better supported by data, more transparent with faster and more universal access to results, and under- pinned by a greater focus on scientific integrity and the public’s trust in science. The report was produced with the SA-EU Dialogue Facility, by the Expert Task Group on the basis of a series of workshops with South African stakeholders.

This is the fourth and final update of this version of the CODATA Prospectus: Strategy and Achievement, now covering the the years 2015-2018. The document summarises CODATA's activities and achievements over that period. This version was brought up to date and presented at the 31st CODATA General Assembly (2018) held at the University of Botswana, Gaborone, Botswana on 9-10 November 2018 following International Data Week.

The DAS policy and statementhas been explicitly co-developed by the Belmont Forum and science publishing community to complement the Data and Digital Outputs Management Plan (DDOMP) requirements being incorporated into all future Belmont Forum Collaborative Research Actions (CRAs) or funding calls. The DDOMP is designed to provide Belmont Forum grantees a framework for practicing good management of transnational and transdisciplinary data throughout their research projects, from the pre-proposal stage to its conclusion. By linking the language and expectations of the DDOMP with the DP3 initiative, funders and publishers will articulate a coherent set of data and research outputs management expectations for researchers, with the ultimate result of improved sharing and re-use of research data The DAS documentis concentrating chiefly on delivering a set of template Data Accessibility Statements (DASs) for guiding Belmont Forum grantees when publishing their research results. The DAS is included as part of a journal article and articulates which data underlie a paper, where the data are available and under what conditions they can be accessed. The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, prevents fraud and thereby builds trust in the research outcomes based on those data amongst decision- and policy-makers, in addition to the wider scientific community and the general public. Even when the underlying dataset cannot be open (for example, for confidentiality, conservation or security reasons), good machine readable metadata and information about the data’s licensing restrictions are important. Furthermore, by supporting data citation, the DAS also provides opportunities to credit the data collectors and curators. &nbsp

****PRE-PRINT**** text only Please find the officialpublication at the reference section on the right hand side (will be publishedMay 2018) A SURF report.SURF is the collaborative ICT organisation for Dutch education and research. SURF offers students, lecturers and scientists in the Netherlands access to the best possible internet and ICT facilities.www.surf.nl/en The idea that data needs to be Findable, Interoperable and Reusable is a simple message which appeals to many. The 15 international FAIR principles were published in 2016. They serve as a guideline for preparing research data for reuse under clearly described conditions by both people and machines. They are intentionally principles and not standards. Various organisations and disciplines have since developed standards, tools and training based on their own interpretation of the FAIR principles.Some domains have already done a great deal of work on this, although not always under the FAIR banner. Other domains do not traditionally use large quantities of research data and are at an earlier stage. The purpose of this report is to build and share expertise on the implementation of FAIR data policy in the Netherlands. The six use cases included in this report describe developments in FAIR data, and different approaches taken, within different domains. For SURF, it is important to gain a better picture of the best way to support researchers who want to make their data FAIR. The use cases are are based on interviews with people involved. They illustrate the move from principles to policy and the development of standards for creating, processing, saving and using FAIR data. &nbsp

Data management plans (DMPs) are becoming commonplace across the globe as a result of funders requiring them with grant proposals, but they are not being employed in ways that truly support the research enterprise. The current manifestation of a DMP—a static document often created before a project begins—only contributes to the perception that they are an annoying administrative exercise. What they really are—or at least should be—is an integral part of research practice, since today most research across all disciplines involves data, code, and other digital components. We are galvanizing the community to reimagine DMPs in this context. One goal is to enhance the DMPTool and DMPonline services, but the larger vision is to improve the experience for everyone involved (researchers, funders, institutions, repositories, libraries, IT...) and support the production of FAIR data. We invite you to read the machine-actionable DMP use cases, contribute your ideas, and take action with us by exploring the resourcelinks below. The project is part of the RDA/US Data Share fellowship sponsored through a grant from the Alfred P. Sloan Foundation #G-2014-13746.

The CODATA Prospectus provides a brief summary of strategy and achievement in 2015-2016: it lays out CODATA's mission and strategy and provides information about the key activities and outputs that contribute to the realising of this strategy. The revised version for Nov 2016, contains some minor additions and updates. The document was prepared for the CODATA General Assembly held in Denver, Colorado on 11 September 2016.