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Auflistung nach Schlagwort "Scientific workflows"

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  • Zeitschriftenartikel
    Scientific Workflows and Provenance: Introduction and Research Opportunities
    (Datenbank-Spektrum: Vol. 12, No. 3, 2012) Cuevas-Vicenttín, Víctor; Dey, Saumen; Köhler, Sven; Riddle, Sean; Ludäscher, Bertram
    Scientific workflows are becoming increasingly popular for compute-intensive and data-intensive scientific applications. The vision and promise of scientific workflows includes rapid, easy workflow design, reuse, scalable execution, and other advantages, e.g., to facilitate “reproducible science” through provenance (e.g., data lineage) support. However, as described in the paper, important research challenges remain. While the database community has studied (business) workflow technologies extensively in the past, most current work in scientific workflows seems to be done outside of the database community, e.g., by practitioners and researchers in the computational sciences and eScience. We provide a brief introduction to scientific workflows and provenance, and identify areas and problems that suggest new opportunities for database research.
  • Zeitschriftenartikel
    The Collaborative Research Center FONDA
    (Datenbank-Spektrum: Vol. 21, No. 3, 2021) Leser, Ulf; Hilbrich, Marcus; Draxl, Claudia; Eisert, Peter; Grunske, Lars; Hostert, Patrick; Kainmüller, Dagmar; Kao, Odej; Kehr, Birte; Kehrer, Timo; Koch, Christoph; Markl, Volker; Meyerhenke, Henning; Rabl, Tilmann; Reinefeld, Alexander; Reinert, Knut; Ritter, Kerstin; Scheuermann, Björn; Schintke, Florian; Schweikardt, Nicole; Weidlich, Matthias
    Today’s scientific data analysis very often requires complex Data Analysis Workflows (DAWs) executed over distributed computational infrastructures, e.g., clusters. Much research effort is devoted to the tuning and performance optimization of specific workflows for specific clusters. However, an arguably even more important problem for accelerating research is the reduction of development, adaptation, and maintenance times of DAWs. We describe the design and setup of the Collaborative Research Center (CRC) 1404 “FONDA -– Foundations of Workflows for Large-Scale Scientific Data Analysis”, in which roughly 50 researchers jointly investigate new technologies, algorithms, and models to increase the portability, adaptability, and dependability of DAWs executed over distributed infrastructures. We describe the motivation behind our project, explain its underlying core concepts, introduce FONDA’s internal structure, and sketch our vision for the future of workflow-based scientific data analysis. We also describe some lessons learned during the “making of” a CRC in Computer Science with strong interdisciplinary components, with the aim to foster similar endeavors.