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.

2013, Brase, Jan

Science is global, it needs global standards, global workflows and is a cooperation of global players. But science is carried out locally by local scientists that are part of local infrastructures with local funders. DataCite is an international consortium, founded in 2009 of currently 17 institutions from 12 countries worldwide. Its mission is to allow a better re-use and citation of data sets. Over 1 million datasets have been registered with a DOI name as a persistent identifier, so they can be published as independent scientific objects to allow stabile citation of data. Citable data sets can be crosslinked from journal articles, their usage and citations can be measured therefore helping scientists gain credit for making their data available. DataCite offers a central metadata repository with additional linked data service for persistent access to RDF metadata.

2021-11-09, Taller, Nelli, Dreyer, Britta, Burger, Felix, Hagemann-Wilholt, Stephanie

Folien für den virtuellen Workshop "Herbst TIB DOI Konsortium online Workshops - Metadaten Best Practice".

2022-11-09, Taller, Nelli, Burger, Felix, Franken, Julian

Folien für den virtuellen Workshop "Herbst TIB DOI Konsortium online Workshop - IGSN, ConfIDent und Metadatenschemata 4.5 und 5.0".

2020, Stocker, M., Darroch, L., Krahl, R., Habermann, T., Devaraju, A., Schwardmann, U., D’onofrio, C., Häggström, I.

Instruments play an essential role in creating research data. Given the importance of instruments and associated metadata to the assessment of data quality and data reuse, globally unique, persistent and resolvable identification of instruments is crucial. The Research Data Alliance Working Group Persistent Identification of Instruments (PIDINST) developed a community-driven solution for persistent identification of instruments which we present and discuss in this paper. Based on an analysis of 10 use cases, PIDINST developed a metadata schema and prototyped schema implementation with DataCite and ePIC as representative persistent identifier infrastructures and with HZB (Helmholtz-Zentrum Berlin für Materialien und Energie) and BODC (British Oceanographic Data Centre) as representative institutional instrument providers. These implementations demonstrate the viability of the proposed solution in practice. Moving forward, PIDINST will further catalyse adoption and consolidate the schema by addressing new stakeholder requirements.

2023, Bertelmann, Roland, Buys, Matthew, Kett, Jürgen, Pampel, Heinz, Pieper, Dirk, Scholze, Frank, Sens, Irina, Burger, Felix, Dreyer, Britta, Glagla-Dietz, Stephanie, Hagemann- Wilholt, Stephanie, Hartmann, Sarah, Schrader, Antonia C., Schirrwagen, Jochen, Summann, Friedrich, Vierkant, Paul

[No abstract available]

2022, Burger, Felix

Damit eine veröffentlichte Ressource die FAIR-Prinzipien erfüllen kann, bedarf es qualitativ hochwertiger Metadaten, welche nicht nur die Ressource selbst, sondern auch mit ihr in Verbindung stehende Objekte beschreiben. Diese Verknüpfungen werden vom Poster anhand des DataCite-Metadatenschemas dargestellt. Der Fokus liegt hierbei auf dem Property "relatedIdentifier". Mittels ausgewählter Beispiele werden die FAIR-Kategorien illustriert und Anregungen geliefert, sowie exemplarische Herausforderungen und Fragestellungen bei der DOI-Metadatenvergabe vorgestellt.

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

2020-11-13, Taller, Nelli, Dreyer, Britta, Burger, Felix

Folien für den virtuellen Workshop "TIB DOI Konsortium: Was ändert sich und wie geht es weiter?".

2023-05-02, Wehrhahn, Dawn, Kehm, Nicole

Folien zum Thema Retrodigitalisierung für den virtuellen Workshop "Frühlings TIB DOI Konsortium Workshop - Retrodigitalisierung und Langzeitarchivierung".