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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
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    Towards OSGeo best practices for scientific software citation: Integration options for persistent identifiers in OSGeo project repositories
    (Genf : Zenodo, 2017) Löwe, Peter Heinz; Neteler, Markus; Goebel, Jan; Tullney, Marco
    As a contribution to the currently ongoing larger effort to establish Open Science as best practices in academia, this article focuses on the Open Source and Open Access tiers of the Open Science triad and community software projects. The current situation of research software development and the need to recognize it as a significant contribution to science is introduced in relation to Open Science. The adoption of the Open Science paradigms occurs at different speeds and on different levels within the various fields of science and crosscutting software communities. This is paralleled by the emerging of an underlying futuresafe technical infrastructure based on open standards to enable proper recognition for published articles, data, and software. Currently the number of journal publications about research software remains low in comparison to the amount of research code published on various software repositories in the WWW. Because common standards for the citation of software projects (containers) and versions of software are lacking, the FORCE11 group and the CodeMeta project recommending to establish Persistent Identifiers (PIDs), together with suitable metadata setss to reliably cite research software. This approach is compared to the best practices implemented by the OSGeo Foundation for geospatial community software projects. For GRASS GIS, a OSGeo project and one of the oldest geospatial open source community projects, the external requirements for DOI-based software citation are compared with the projects software documentation standards. Based on this status assessment, application scenarios are derived, how OSGeo projects can approach DOI-based software citation, both as a standalone option and also as a means to foster open access journal publications as part of reproducible Open Science.