22 research outputs found

    Anforderungen der Ingenieurwissenschaften an das Forschungsdatenmanagement der Universität Stuttgart - Ergebnisse der Bedarfsanalyse des Projektes DIPL-ING

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    Forschungsdaten sind die Grundlage aller wissenschaftlichen Praxis und der Ausgangspunkt für alle daraus gewonnenen Erkenntnisse. Dieser Wert spiegelt sich allerdings oft nicht im Management von Forschungsdaten wider. Insbesondere in den Ingenieurwissenschaften gibt es Nachholbedarf, was das zweckgerichtete Forschungsdatenmanagement angeht, um die Daten nachnutzbar, nachvollziehbar und nachprüfbar zu machen. Die vorliegende Veröffentlichung fasst die Ergebnisse der Bedarfsanalyse des Projektes DIPL-ING zusammen, welches das Ziel hat, gemeinsam mit Ingenieurwissenschaftlerinnen und Ingenieurwissenschaftler Konzepte für das Forschungsdatenmanagement in den Ingenieurwissenschaften bereitzustellen. Anhand von konkreten Anwendungsfällen aus der technischen Thermodynamik und der Aerodynamik wurden Problembereiche und Anforderungen der Ingenieurwissenschaften an das Forschungsdatenmanagement ermittelt. Spezifische Anforderungen ergeben sich dadurch, dass die Forschung zu einem nicht unerheblichen Teil auf Software und Code beruht, der zum Teil sehr große Mengen an Roh- und auch verarbeiteten Daten generiert und weiterverarbeitet. Ziel ist es, eine sinnvolle interne wie externe Nachnutzung von Forschungsdaten zu ermöglichen. Dafür werden fachspezifische Metadatenstandards benötigt, die den Entstehungsprozess der Daten und Codes dokumentieren können und so sowohl die Suchbarkeit als auch die Verständlichkeit der Daten fördern. Zudem fehlen klare fachspezifische Richtlinien, welche Daten für welchen Zeitraum ökonomisch sinnvoll abgelegt werden sollen. Für die Veröffentlichung der Daten werden Infrastrukturen benötigt, die sowohl mit großen Datenmengen wie auch mit Software und Code umgehen können und eine Qualitäts- wie auch Zugriffskontrolle ermöglichen

    Design and Implementation of the first Generic Archive Storage Service for Research Data in Germany

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    Research data as the true valuable good in science must be saved and subsequently kept findable, accessible and reusable for reasons of proper scientific conduct for a time span of several years. However, managing long-term storage of research data is a burden for institutes and researchers. Because of the sheer size and the required retention time apt storage providers are hard to find. Aiming to solve this puzzle, the bwDataArchive project started development of a long-term research data archive that is reliable, cost effective and able store multiple petabytes of data. The hardware consists of data storage on magnetic tape, interfaced with disk caches and nodes for data movement and access. On the software side, the High Performance Storage System (HPSS) was chosen for its proven ability to reliably store huge amounts of data. However, the implementation of bwDataArchive is not dependant on HPSS. For authentication the bwDataArchive is integrated into the federated identity management for educational institutions in the State of Baden-Württemberg in Germany. The archive features data protection by means of a dual copy at two distinct locations on different tape technologies, data accessibility by common storage protocols, data retention assurance for more than ten years, data preservation with checksums, and data management capabilities supported by a flexible directory structure allowing sharing and publication. As of September 2019, the bwDataArchive holds over 9 PB and 90 million files and sees a constant increase in usage and users from many communities

    Design and Implementation of the first Generic Archive Storage Service for Research Data in Germany

    Get PDF
    Research data as the true valuable good in science must be saved and subsequently kept findable, accessible and reusable for reasons of proper scientific conduct for a time span of several years. However, managing long-term storage of research data is a burden for institutes and researchers. Because of the sheer size and the required retention time apt storage providers are hard to find. Aiming to solve this puzzle, the bwDataArchive project started development of a long-term research data archive that is reliable, cost effective and able store multiple petabytes of data. The hardware consists of data storage on magnetic tape, interfaced with disk caches and nodes for data movement and access. On the software side, the High Performance Storage System (HPSS) was chosen for its proven ability to reliably store huge amounts of data. However, the implementation of bwDataArchive is not dependant on HPSS. For authentication the bwDataArchive is integrated into the federated identity management for educational institutions in the State of Baden-Württemberg in Germany. The archive features data protection by means of a dual copy at two distinct locations on different tape technologies, data accessibility by common storage protocols, data retention assurance for more than ten years, data preservation with checksums, and data management capabilities supported by a flexible directory structure allowing sharing and publication. As of September 2019, the bwDataArchive holds over 9 PB and 90 million files and sees a constant increase in usage and users from many communities

    European standardization efforts from FAIR toward explainable-AI-ready data documentation in materials modelling

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    Security critical AI applications require a standardized and interoperable data and metadata documentation that makes the source data explainable-AI ready (XAIR). Within the domain of materials modelling and characterization, European initiatives have proposed a series of metadata standards and procedural recommendations that were accepted as CEN workshop agreements (CWAs): CWA 17284 MODA, CWA 17815 CHADA, and CWA 17960 ModGra. It is discussed how these standards have been ontologized, and gaps are identified as regards the epistemic grounding metadata, i.e., an annotation of data and claims by something that substantiates whether, why, and to what extent they are indeed knowledge and can be relied upon.European standardization efforts from FAIR toward explainable-AI-ready data documentation in materials modellingsubmittedVersio

    Data Technology in Materials Modelling

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    This open access book discusses advances in semantic interoperability for materials modelling, aiming at integrating data obtained from different methods and sources into common frameworks, and facilitating the development of platforms where simulation services in computational molecular engineering can be provided as well as coupled and linked to each other in a standardized and reliable way. The Virtual Materials Marketplace (VIMMP), which is open to all service providers and clients, provides a framework for offering and accessing such services, assisting the uptake of novel modelling and simulation approaches by SMEs, consultants, and industrial R&D end users. Semantic assets presented include the EngMeta metadata schema for research data infrastructures in simulation-based engineering and the collection of ontologies from VIMMP, including the ontology for simulation, modelling, and optimization (OSMO) and the VIMMP software ontology (VISO)

    Ontologies for Models and Algorithms in Applied Mathematics and Related Disciplines

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    In applied mathematics and related disciplines, the modeling-simulation-optimization workflow is a prominent scheme, with mathematical models and numerical algorithms playing a crucial role. For these types of mathematical research data, the Mathematical Research Data Initiative has developed, merged and implemented ontologies and knowledge graphs. This contributes to making mathematical research data FAIR by introducing semantic technology and documenting the mathematical foundations accordingly. Using the concrete example of microfracture analysis of porous media, it is shown how the knowledge of the underlying mathematical model and the corresponding numerical algorithms for its solution can be represented by the ontologies.Comment: Preprint of a Conference Paper to appear in the Proceeding of the 17th International Conference on Metadata and Semantics Researc
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