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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

Easier and reusable Data Analysis for the Natural Sciences

See our new short description of the research we will be doing in FONDA.

Author Ulf LeserPosted on 03/08/202008/02/2022Categories 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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