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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

Category: Uncategorized

Nano Course Snakemake

Next week, on April 23 Johannes Köster will give the Nano Course on Snakemake. The course is online. Please use our wiki to get the link to the Zoom session.

Author Christopher LazikPosted on 16/04/202107/09/2022Categories Uncategorized

Nano Course Software Carpentry- Software Engineering Principles for Scientific Software

Next week on April 21 & 22 we welcome Stephan Druskat to held the upcoming Nano Course “Software Carpentry- Software Engineering Principles for Scientific Software” on version control with Git and collaboration with GitHub/GitLab. To get the Zoom link, members of FONDA can use our internal wiki.

Author Christopher LazikPosted on 14/04/202109/09/2022Categories Uncategorized

RTG Good Scientific Practice

Our RTG on good scientific practise will be held by Hans-Peter Eckle next month on May 5, 6 and 7. They will take place online, so use our Wiki to get the toom link.

Author Christopher LazikPosted on 05/04/202105/09/2022Categories Uncategorized

FONDA Wiki

FONDA has its own wiki now. Follow the link to take a look: https://wikis.hu-berlin.de/fonda/Main_Page

Author Christopher LazikPosted on 17/03/202101/09/2022Categories Uncategorized

FONDA RTG Evaluation Workshop April 2021

Next month on April 5 we will meet virtually for the RTG Evaluation Workshop. Be sure to find the zoom link on our Wiki.

Author Christopher LazikPosted on 05/03/202105/09/2022Categories Uncategorized

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

Positions in FONDA: Portal to submit expressions of interest

FONDA has many open positions on the PhD and Post-Doc level. Please see the overview of open positions and submit expressions of interest using the FONDA portal at https://hu.berlin/fonda-portal-2020.

Author Matthias WeidlichPosted on 21/07/202008/02/2022Categories 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.
Read More …



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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