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Publishing Data in the context of ICSU World Data System Mustapha Mokrane Executive Director International Programme Office

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ICSU World Data System ICSUs long-term vision is of a world where excellence in science is effectively translated into policy making and socio- economic development. In such a world, universal and equitable access to scientific data and information is a reality

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2.29 WDS-SC Members and WDS-IPO Staff Scientific Committee 20122015 Bernard Minster (Chair, USA) Michael Diepenbroek (Germany) Franoise Genova (France) Claudia Emerson (Canada) Sandra Harrison (UK) Wim Hugo (South Africa) Jane Hunter (Australia) Vasily Kopylov (Russian Fed.) Guoqing Li (China) Ruth Neilan (USA) Lesley Rickards (UK) Ryosuke Shibasaki (Japan) Ariel Troisi (Argentina) Howard Moore (Ex officio, ICSU) Yasuhiro Murayama (Ex officio, NICT)

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WDS Members Scientific Data Services: Assist organizations in the capture, storage, curation, long-term preservation, discovery, access, retrieval, aggregation, analysis, and/or visualization of scientific data, as well as in the associated legal frameworks, to support disciplinary and multidisciplinary scientific research.

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WDS Membership 57 Regular Organizations that are data stewards and/or data analysis services 10 Networks umbrella bodies representing groups of data stewardship organizations and/or data analysis services (EOSDIS, IODE, IVOA...) 3 Partners Contribute support to WDS Membership (DataCite) 17 Associates Interested in the WDS endeavour

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WDS Membership Regular Members Network Members

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Strategic Plan 20142018 https://www.icsu-wds.org/organization/strategic-plan

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Strategic Targets 1)Make trusted data services an integral part of international collaborative scientific research 2)Nurture active disciplinary and multidisciplinary scientific data services communities 3)Improve the funding environment for Scientific Data Services 4)Improve trust in and quality of open Scientific Data Services 5)Position WDS as the premium global multidisciplinary network for quality-assessed scientific research data

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ST4: Improve the trust in, and quality of, open scientific data services facilitating access to, and use or reuse of datasets through Data Publication Publishing Data 100+ participants at the RDAWDS Publishing Data Interest Group breakout session: Dublin, March 2014

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The Long Tail Fitness for use Total volume of scientific data Managed & published data Large scale monitoring, computed data, and disciplinary data centers Unmanaged & non-published Data from individual scientists, labs, or smaller projects Somewhat managed & open access data

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Fitness for use Total volume of scientific data Bridging domains Publishing workflows Publishing Services Bibliometrics for data Cost recovery models Trusted repositories & services e-Infrastructures Scientific research projects

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Working and Interest Groups Publishing Data IG Workflows WG: Provide generic workflow models for data publication Bibliometrics WG: Approaches & solutions that allow analysis of content & proper citations Cost recovery models WG/IG Services WG: cross-referencing

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Linking data & journals Linking editorial workflows Linking services

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Consortium Research facilities Data repositories Universities Libraries Industry

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Data Publication Services Problem: no common framework for cross-referencing datasets and articles. Solution: a cross-referencing service that connects articles to relevant data. Key benefits: Efficiency, scalability Better quality & accuracy of links Powering new tools and functionalities to the benefit of researchers

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How do data publication services fit into the globally evolving data infrastructures? How will scholarly publishing evolve over the next decade? Impact of data publications? Organizational and technical requirements for the stakeholders? What are the costs? Risks

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Knowledge Network Web-based, interlinked repository of relationships between the actors and entities that make up our research landscape: people, institutions, data services, projects, research disciplines and topics, funding sources, and the like.

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Knowledge Network Interlinked foundational Global Research Infrastructure: Sustainable, Scalable, and Distributed (leading organisations, data centres, and initiatives) Draw on the example of Linked Open Data, and re-use as many services, components, standards, and existing capacity as is possible.

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Knowledge Network

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Leverage existing Infrastructure

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Trusted Digital Repositories/Services WDS & DSA: lightweight certification framework NESTOR seal DIN standard 31644, TRAC criteria ISO standard 16363

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Global Registry of TDRs Re3data/DataBib DataCite Subset of the registry or an independent extension of the registry that aggregates quality and certification properties (WDS, Data Seal of Approval, ISO 16363, etc.) managed by WDS.

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Benefits Researchers: confidence in integrity, authenticity, accessibility, re-usable, meaningful and data services can be safely used Science publishers: identify trustworthy data repositories for article related data and services Data repositories and services: promotion and benchmarking

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Thanks to Wim Hugo (SAEON/NRF) Michael Diepenbroek (PANGAEA) All Co-chairs and contributors of the Working Groups: Eefke Smit, Jonathan Tedds, Suenje Dallmeier-Tiessen, Elizabeth Newbold, Theodora Bloom, Adrian Burton, Hylke Koers, Sarah Callaghan, Kerstin Lehnert, Simon Hodson, Ingrid Dillo

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www.SciDataCon2014.org