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    Publication of Atmospheric Model Data using the ATMODAT Standard
    (Stuttgart : E. Schweizerbart Science Publishers, 2022) Ganske, Anette; Heil, Angelika; Lammert, Andrea; Kretzschmar, Jan; Quaas, Johannes
    Scientific data should be published in a way so that other scientists can benefit from these data, enabling further research. The FAIR Data Principles are defining the basic prerequisite for a good data publication: data should be Findable, Accessible, Interoperable, and Reusable. Increasingly, research communities are developing discipline-specific data publication standards under consideration of the FAIR Data Principles. A very comprehensive yet strict data standard has been developed for the climate model output within the Climate Model Intercomparison Project (CMIP), which largely builds upon the Climate and Forecast Metadata Conventions (CF conventions). There are, however, many areas of atmospheric modelling where data cannot be standardised according to the CMIP data standard because, e.g., the data contain specific variables which are not covered by the CMIP standard. Furthermore, fulfilling the strict CMIP data standard for smaller Model Intercomparison Projects (MIPs) requires much effort (in time and manpower) and hence the outcome of these MIPs often remains non-standardised. For innovative model diagnostics, preexisting standards are also not flexible enough. For that reason, the ATMODAT standard, a quality guideline for atmospheric model data, was created. The ATMODAT standard defines a set of requirements that aim at ensuring the high reusability of atmospheric model data publications. The requirements include the use of the netCDF file format, the application of the CF conventions, rich and standardised file metadata, and the publication of the data with a DataCite DOI. Additionally, a tool for checking the conformity of data and metadata to this standard, the atmodat data checker, was developed and is available on GitHub under an open licence. By using the more flexible ATMODAT standard, the publication of standardised datasets is simplified for smaller MIPs. This standardisation process is presented as an example using the data of an aerosol-climate model from the AeroCOM MIP. Furthermore, the landing pages of ATMODAT-compliant data publications can be highlighted with the EASYDAB logo. EASYDAB (Earth System Data Branding) is a newly developed quality label for carefully curated and highly standardised data publications. The ATMODAT data standardisation can easily be transferred to data from other disciplines and contribute to their improved reusability.
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    A short guide to increase FAIRness of atmospheric model data
    (Stuttgart : E. Schweizerbart Science Publishers, 2020) Ganske, Anette; Heydebreck, Daniel; Höck, Daniel; Kraft, Angelina; Quaas, Johannes; Kaiser, Amandine
    The generation, processing and analysis of atmospheric model data are expensive, as atmospheric model runs are often computationally intensive and the costs of ‘fast’ disk space are rising. Moreover, atmospheric models are mostly developed by groups of scientists over many years and therefore only few appropriate models exist for specific analyses, e.g. for urban climate. Hence, atmospheric model data should be made available for reuse by scientists, the public sector, companies and other stakeholders. Thereby, this leads to an increasing need for swift, user-friendly adaptation of standards.The FAIR data principles (Findable, Accessible, Interoperable, Reusable) were established to foster the reuse of data. Research data become findable and accessible if they are published in public repositories with general metadata and Persistent Identifiers (PIDs), e.g. DataCite DOIs. The use of PIDs should ensure that describing metadata is persistently available. Nevertheless, PIDs and basic metadata do not guarantee that the data are indeed interoperable and reusable without project-specific knowledge. Additionally, the lack of standardised machine-readable metadata reduces the FAIRness of data. Unfortunately, there are no common standards for non-climate models, e.g. for mesoscale models, available. This paper proposes a concept to improve the FAIRness of archived atmospheric model data. This concept was developed within the AtMoDat project (Atmospheric Model Data). The approach consists of several aspects, each of which is easy to implement: requirements for rich metadata with controlled vocabulary, the landing pages, file formats (netCDF) and the structure within the files. The landing pages are a core element of this concept as they should be human- and machine readable, hold discipline-specific metadata and present metadata on simulation and variable level. This guide is meant to help data producers and curators to prepare data for publication. Furthermore, this guide provides information for the choice of keywords, which supports data reusers in their search for data with search engines. © 2020 The authors