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Project deliverable Open Access

FAIR-EASE_D2.1_Environmental Data Infrastructures_Services Description Report

Tjerk Krijger; Enrico Boldrini; Roberto Roncella; Fabrizio Papeschi; Alexandra Kokkinaki; Gwen Moncoiffe; Véronique Chaffard; Peter Thijsse


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    <dct:description>&lt;p&gt;For many societal and scientific challenges of the present, access to multi-disciplinary data resources and services is key. The FAIR-EASE (FE) project presents a technical framework that tries to cross boundaries of domain-specific (meta)data standards that would allow for developing overarching services where scientists from different domains can collaborate. This project focuses on three different multi-disciplinary Use Cases (UCs) that specify the needs and requirements for their research.&amp;nbsp;&lt;/p&gt; &lt;p&gt;One of the components of the FE technical framework will be the FE Interdisciplinary Data Discovery and Access Service (IDDAS) that will provide users with an easy and FAIR service for discovery and access to multidisciplinary and aggregated data sets. These data resources are managed and provided by a range of existing environmental data infrastructures that operate in different domains such as Biodiversity, Atmosphere, Solid Earth and Ocean. The data infrastructures that are included in this project are based on the needs and requirements set by the UCs.&amp;nbsp;&lt;/p&gt; &lt;p&gt;The federation of data resources provided by the data infrastructures should facilitate the sharing of multi-disciplinary datasets with users and allow for interaction with the FE Data Lake (WP4) and Earth Analytic Lab (EAL - WP3) that will grant users access to analytical and visualisation services and applications.&amp;nbsp;&lt;/p&gt; &lt;p&gt;For each of the data infrastructures chosen by the UCs to include in this project, this Deliverable D2.1 includes an analysis of their current data discovery and access mechanisms, as well as a first analysis of metadata models and semantics used. The content of this report is important for a common understanding of the data infrastructure landscape, and will e.g. provide the URLs that the IDDAS metadata harvester (based on GEODAB) will use.&lt;/p&gt;</dct:description>
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