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The authors also acknowledge the support and collaboration of many other colleagues in their respective institutes, research communities and IT Infrastructures, together with the funding received by these from many different sources. These include but are not limited to the following: (i) The Worldwide LHC Computing Grid (WLCG) project is a global collaboration of more than 170 computing centres in 43 countries, linking up national and international grid infrastructures. Funding is acknowledged from many national funding bodies and we acknowledge the support of several operational infrastructures including EGI, OSG and NDGF/NeIC. (ii) EGI acknowledges the funding and support received from the European Commission and the many National Grid Initiatives and other members. EOSC-hub receives funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 777536. (iii) The work leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 730941 (AARC2). (iv) Work on the development of ESGF's identity management system has been supported by The UK Natural Environment Research Council and funding from the European Union's Seventh Framework Programme for research, technological development and demonstration through projects IS-ENES (grant agreement no 228203) and IS-ENES2 (grant agreement no 312979). (v) Ludek Matyska and Michal Prochazka acknowledge funding from the RI ELIXIR CZ project funded by MEYS Czech Republic No. LM2015047. (vi) Scott Koranda acknowledges support provided by the United States National Science Foundation under Grant No. PHY-1700765. (vii) GÉANT Association on behalf of the GN4 Phase 2 project (GN4-2).The research leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 731122(GN4-2). (viii) ELIXIR acknowledges support from Research Infrastructure programme of Horizon 2020 grant No 676559 EXCELERATE. (ix) CORBEL life science cluster acknowledges support from Horizon 2020 research and innovation programme under grant agreement No 654248. (x) Mirjam van Daalen acknowledges that the research leading to this result has been supported by the project CALIPSOplus under the Grant Agreement 730872 from the EU Framework Programme for Research and Innovation HORIZON 2020. (xi) EISCAT is an international association supported by research organisations in China (CRIRP), Finland (SA), Japan (NIPR), Norway (NFR), Sweden (VR), and the United Kingdom (NERC). This white-paper expresses common requirements of Research Communities seeking to leverage Identity Federation for Authentication and Authorisation. Recommendations are made to Stakeholders to guide the future evolution of Federated Identity Management in a direction that better satisfies research use cases. The authors represent research communities, Research Services, Infrastructures, Identity Federations and Interfederations, with a joint motivation to ease collaboration for distributed researchers. The content has been edited collaboratively by the Federated Identity Management for Research (FIM4R) Community, with input sought at conferences and meetings in Europe, Asia and North America.

This book is a collection of seventeen papers which describe the impact that the ARIADNE project and its successor, ARIADNEplus (2019-2022) have had on the archaeological community, both in Europe and further afield. Each case study has been contributed by organisations involved in the ARIADNE Infrastructure who cover many countries from across Europe as well as Argentina and Japan. These papers were originally presented at the CAA Conference in Krakow, April 2019 and cover aspects such as data management, application of standards and guidelines, the use of CIDOC-CRM and Open Data to name but a few.

This article describes how virtual research environments (VREs) offer new opportunities for researchers to analyse open data and to obtain new insights for policy making. Although various VRE-related initiatives are under development, there is a lack of insight into how VREs support collaborative open data analysis by researchers and how this might be improved, ultimately leading to input for policy making to solve societal issues. This article clarifies in which ways VREs support researchers in open data analysis. Seven cases presenting different modes of researcher support for open data analysis were investigated and compared. Four types of support were identified: 1) ‘Figure it out yourself', 2) ‘Leading users by the hand', 3) ‘Training to provide the basics' and 4) ‘Learning from peers'. The author provides recommendations to improve the support of researchers' open data analysis and to subsequently obtain new insights for policy making to solve societal challenges.

International audience

Public and private organizations increasingly release their data to gain benefits such as transparency and economic growth. The use of these open data can be supported and stimulated by providing considerable metadata (data about the data), including discovery, contextual and detailed metadata. In this paper we argue that metadata are key enablers for the effective use of Linked Open Data (LOD). We illustrate the potential of metadata by 1) presenting an overview of advantages and disadvantages of metadata derived from literature, 2) presenting metadata requirements for LOD architectures derived from literature, workshops and a questionnaire, 3) describing a LOD metadata architecture that meets the requirements and 4) showing examples of the application of this architecture in the ENGAGE project. The paper shows that using metadata with the appropriate metadata architecture can yield considerable benefits for LOD publication and use, including improving find ability, accessibility, storing, preservation, analysing, comparing, reproducing, finding inconsistencies, correct interpretation, visualizing, linking data, assessing and ranking the quality of data and avoiding unnecessary duplication of data. The Common European Research Information Format (CERIF) can be used to build the metadata architecture and achieve the advantages.

The paper introduces into a new Science Gateway, developed in the framework of the European Horizon 2020 project EGI Engage - DARIAH Competence Centre, which started in March 2015 co-funded by the European Union, with the participation of about 70 (research) units in over 30 countries. In this paper the authors focus on trans-disciplinary collaboration in the framework of explorative lexicography in cultural context. On the one hand, they give a short overview of the architecture of the Science Gateway, used techniques, and specific applications and services developed during the DARIAH Competence Centre. On the other they mainly focus on possible added value and changes concerning work flow for Lexicographers and researchers on Lexical resources. This is exemplified on the European network of COST action IS 1305 “European Network of electronic lexicography (ENeL)”.

The report “Selection of Research Data” contains general guidelines on how to determine what research data should be preserved for the long term and what data should not. These guidelines can be used by individual researchers or research groups, researchers who co-operate within a collaboratory, research institutes, university faculties and national or international organisations focusing on a specific scientific/scholarly discipline and bodies funding research. The checklist is also suitable for use by managers of archives, research repositories, and heritage institutions. This study shows the situation in the area of selecting research data, based on a survey of the literature, interviews with key players and the experience gained by DANS and the 3TU Data Centre. The main issues are considered. The most important reasons for preserving research data for the long term have been formulated. The checklist based on these can be used as a guide for creating guidelines for specific scientific/scholarly disciplines. The report also describes the various roles of people involved in selection. Attention is paid to the best moment in the digital life cycle of research data for selecting them.