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FONDA – Foundations of Workflows for Large-Scale Scientific Data Analysis

FONDA – Foundations of Workflows for Large-Scale Scientific Data Analysis

DFG Collaborative Research Center 1404 at Humboldt-Universität zu Berlin

  • About FONDA
    • General Information
      • Phase I: PAD
      • Phase II: SUM
    • Organization
    • Scientific Advisory Board
    • Mercator Fellows
    • Equal Opportunity Resources
  • Research Areas and Subprojects
    • Research Area A: DAW Specification
      • A1: Query-driven Validation of Distributed DAWs
      • A2: Energy-Aware Optimization of Workflows in Bioinformatics
      • A3: Hardening Computational Materials-Science Workflows against Human Errors
      • A5: Workflows for Annotation-Efficient Machine Learning in Biomedical Imaging Research
      • A7: Semantic Composition and Validation of Interacting DAWs in Computational Materials Science
    • Research Area B: DAW Execution
      • B1: Carbon-aware Multi-site Workflow Scheduling Under Uncertainty
      • B4: Proactive Network, I/O, and Storage Steering for Multiple DAWs on Shared Infrastructures
      • B5: Transparent Multi-Site Data Analysis Workflows for Earth Observation
      • B6: End-to-end Energy Profiles of ML-based Data Analysis Workflows
      • B7: Efficient DAW Execution Using Incremental Data for Monitoring Forest Disturbances
    • Research Area C: DAW Design
      • C1: Collaborative Design of Exploratory DAWs in Neuroscience
      • C2: Early Workflow Design: From Collaborative Scientific Problem-Solving to DAW Specifications
      • C3: User Centered Design for Data Analysis Workflow Languages
    • Area S: Central Service and Administration Projects
      • S1: Testbeds and Repositories
      • S2: Integrated Research Training Group
    • Teams
      • T6: Reference Stack for DAW Infrastructures
      • T7: Large-Language Models for DAW Design and Maintenance
      • T8: The Workflow Clinic
      • T9: Reproducibility Badging
  • Participants
    • Principal Investigators
    • Scientists
  • Publications
  • |News|
  • BER Data Science

FONDA Winter Retreat 2023

FONDA got together for the last retreat in 2023. We met in Wandlitz from November 9 to November 10.

Author Christopher LazikPosted on 12/11/202314/12/2023Categories Uncategorized

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About FONDA

FONDA investigates methods for increasing productivity in the development, execution, and maintenance of Data Analysis Workflows for large scientific data sets. We approach the underlying research questions from a fundamental perspective, aiming to find new abstractions, models, and algorithms that can eventually form the basis of a new class of future infrastructures for Data Analysis Workflows.
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Contact

For more information, please contact our Coordinator Tobias Price.

FONDA’s Research Areas

  • Overview of Resarch Areas and Subprojects in FONDA
  • Research Area A: DAW Specification
  • Research Area B: DAW Execution
  • Research Area C: DAW Design
  • Area S: Central Service and Administration Projects
  • Teams

Principal Investigators in FONDA

  • Overview of Principal Investigators and Participating Institutions
  • Prof. Ulf Leser
  • Prof. Tilmann Rabl
  • Prof. Patrick Hostert
  • Prof. Odej Kao
  • Prof. Nicole Schweikardt
  • Prof. Matthias Weidlich
  • Prof. Lars Grunske
  • Prof. Kerstin Ritter
  • Prof. Knut Reinert
  • Prof. Henning Meyerhenke
  • Prof. Dagmar Kainmüller
  • Prof. Claudia Draxl
  • Prof. Björn Scheuermann
  • Dr. Florian Schintke
  • Prof. Martin Herold
  • Prof. Jan Mendling
  • Prof. Matthias Boehm
  • Prof. Thomas Kosch
  • Malte Dreyer
  • Prof. Fatma Deniz
  • Prof. Anna-Lena Lamprecht
  • Dr. Tilmann Hickel
  • Dr. Pasquale Pavone
  • Prof. Alexander Reinefeld (FONDA I)
  • Prof. Christoph T. Koch (FONDA I)
  • Prof. Birte Kehr (FONDA I)
  • Prof. Volker Markl (FONDA I)
  • Prof. Timo Kehrer (FONDA I)
  • Prof. Peter Eisert (FONDA I)

Imprint
  
Privacy Statement

  • About FONDA
    • General Information
      • Phase I: PAD
      • Phase II: SUM
    • Organization
    • Scientific Advisory Board
    • Mercator Fellows
    • Equal Opportunity Resources
  • Research Areas and Subprojects
    • Research Area A: DAW Specification
      • A1: Query-driven Validation of Distributed DAWs
      • A2: Energy-Aware Optimization of Workflows in Bioinformatics
      • A3: Hardening Computational Materials-Science Workflows against Human Errors
      • A5: Workflows for Annotation-Efficient Machine Learning in Biomedical Imaging Research
      • A7: Semantic Composition and Validation of Interacting DAWs in Computational Materials Science
    • Research Area B: DAW Execution
      • B1: Carbon-aware Multi-site Workflow Scheduling Under Uncertainty
      • B4: Proactive Network, I/O, and Storage Steering for Multiple DAWs on Shared Infrastructures
      • B5: Transparent Multi-Site Data Analysis Workflows for Earth Observation
      • B6: End-to-end Energy Profiles of ML-based Data Analysis Workflows
      • B7: Efficient DAW Execution Using Incremental Data for Monitoring Forest Disturbances
    • Research Area C: DAW Design
      • C1: Collaborative Design of Exploratory DAWs in Neuroscience
      • C2: Early Workflow Design: From Collaborative Scientific Problem-Solving to DAW Specifications
      • C3: User Centered Design for Data Analysis Workflow Languages
    • Area S: Central Service and Administration Projects
      • S1: Testbeds and Repositories
      • S2: Integrated Research Training Group
    • Teams
      • T6: Reference Stack for DAW Infrastructures
      • T7: Large-Language Models for DAW Design and Maintenance
      • T8: The Workflow Clinic
      • T9: Reproducibility Badging
  • Participants
    • Principal Investigators
    • Scientists
  • Publications
  • |News|
  • BER Data Science
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