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Modellierung als Nachhaltigkeitsstrategie für Forschungsanwendungen

Authors: Fischer, Anna; Schildkamp, Philip; Demmer, Dennis; Neuefeind, Claes; Mathiak, Brigitte;

Modellierung als Nachhaltigkeitsstrategie für Forschungsanwendungen

Abstract

Die Entwicklung und Bereitstellung von Software-Anwendungen wie z. B. Recherche-Datenbanken, interaktiven Visualisierungen oder digitalen Editionen ist zu einem integralen Bestandteil geisteswissenschaftlicher Forschungspraxis geworden. Um den wissenschaftlichen Anforderungen an die Nachvollziehbarkeit und Reproduzierbarkeit von Forschungsergebnissen gerecht zu werden, stellt sich die Frage, welche Strategien sich eignen, um Anwendungen in den (digitalen) Geisteswissenschaften auf nachhaltige Weise konzipieren, implementieren, bereitstellen und vor fremden Eingriffen schützen zu können. Vor diesem Hintergrund erforscht das DFG-geförderte Kooperationsprojekt SustainLife seit 2018 die Übertragbarkeit von Cloud-Deployment-Verfahren auf die Gegebenheiten und Bedürfnisse von DH-Forschungsanwendungen, um diese langfristig erhalten und bereitstellen zu können. Die Modellierungssprache TOSCA (Topology Orchestration Specification for Cloud Applications) sowie die Open-Source-Implementierung OpenTOSCA nutzen wir dabei als Methode, um existierende Nachhaltigkeitsansätze für Forschungsanwendungen miteinander zu verbinden. In unserem Beitrag möchten wir aufzeigen, dass TOSCA die Diversität von Forschungsanwendungen in den DH auffangen kann und viele Ansätze für deren ressourceneffizienten Erhalt und Betrieb bietet. Weiterhin zeigen wir Anknüpfungspunkte für zukünftige Forschungsarbeiten auf, die den Umgang mit dem OpenTOSCA-Ökosystem und dessen Bereitstellung vereinfachen und verbessern können.

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Keywords

Nachhaltigkeit, Anwendung, Deployment, OpenTOSCA, Modellierung, FORGE2021, Software, TOSCA

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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