CRC 1404 FONDA (Focusing On Next-Generation Data Analysis)

Institution: Humboldt-Universität zu Berlin Category: Project
Website: https://www.cms.hu-berlin.de/de/ueberblick/projekte/fonda

Short Description

The CMS supports research projects with technical infrastructure and services in the fields of data analysis and high-performance computing. It provides dedicated compute clusters and repositories for the development, monitoring, and execution of data analysis workflows. Target groups are academic researchers and projects conducting complex data analyses. The main benefit lies in providing stable, scalable, and sustainable IT infrastructure for data-intensive research.

General Description

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Thematic Classification

Subject Areas

Computer Science
Natural Sciences
Humanities
Digital Teaching and Examinations
Research Infrastructure
Sustainability
Usability
Cross-location Execution of Data Analysis Workflows

Research Fields

• Data analysis workflows (DAWs)
• Sustainability
• Usability
• Cross-site execution of DAWs
• Energy footprint of DAWs
• High-performance computing (HPC)

Specializations

Sustainability, usability, cross-location execution of data analysis workflows (DAWs)

Keywords

• CRC 1404 FONDA
• Data analysis workflows (DAWs)
• High-performance computing (HPC)
• Test systems and repositories
• Energy footprint of DAWs
• Sustainability
• Usability
• Cross-site execution
• DFG funding
• Research infrastructure

Funding

Funding Provider: -
Funding Program: DFG (Sonderforschungsbereich/Collaborative Research Center)
Funding Reference: CRC 1404 FONDA
Funding Period: 2024–2028
Project Volume: Das Volumen oder "INSUFFICIENT"

Team & Partners

Project Leadership

• Malte Dreyer (Computer and Media Service, Humboldt-Universität zu Berlin)
• Dr. Yagmur Kati (Computer and Media Service, Humboldt-Universität zu Berlin)

Involved Persons

• Dr. Yagmur Kati (Collaborator INF-Project S1)

Affiliated Institutions

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External Partners

DFG (Deutsche Forschungsgemeinschaft)

Project Contents

Goals

• Development, maintenance, and reuse of complex data analysis workflows (DAWs) for large-scale scientific data analysis
• Expansion of the research scope to include sustainability, usability, and cross-site execution of DAWs
• Provision and maintenance of test systems and repositories for the energy footprint of DAWs
• Support through dedicated and shared compute clusters for development, monitoring, and execution of DAWs

Work Packages

• WP S1: Test systems and repositories
• AP: Development and maintenance of repositories for the energy footprint of data analysis workflows (DAWs)
• AP: Integration of measurement data to map the energy footprint
• AP: Provision and maintenance of dedicated and shared compute clusters for development, monitoring, and execution of DAWs

Methods

• Development and maintenance of complex data analysis workflows (DAWs)
• Reuse of complex data analysis workflows (DAWs)
• Mapping the energy footprint of DAWs
• Integration of measurement data into repositories
• Use of dedicated and shared compute clusters
• Research focuses: sustainability, usability, cross-site execution of DAWs
• Collaboration within the Collaborative Research Centre (SFB) through central INF/service project S1
• Implementation of test systems and repositories for research purposes
• Support via High Performance Computing (HPC) – team leadership
• Use of electronic ticketing systems for handling email inquiries
• Use of web and document servers for dissemination of information and publications
• Development and provision of KI tools (Chat, TextTool, Talk to Documents)
• Provision of coding LLMs for development environments
• Conducting training sessions and workshops (e.g. Plone, Moodle, Mahara)
• Use of digital platforms for communication and information dissemination (CMS blog, Moodle, OTRS)

Expected Outcomes

• Development and maintenance of test systems and repositories for data analysis workflows (DAWs) with a focus on the energetic footprint
• Integration and management of measurement data for evaluating the energy efficiency of DAWs
• Provision and maintenance of dedicated and shared compute clusters for the development, monitoring, and execution of DAWs
• Expansion of research competencies in the new areas: sustainability, usability, and site-independent execution of DAWs
• Support of the scientific community through standardized, sustainable, and user-friendly infrastructures for large-scale data analysis

Contact

Contact Person: - Malte Dreyer (Co-Leitung INF-/Service-Projekt) - Dr. Yagmur Kati (Mitarbeit INF-Projekt S1) - Robert Sombrutzki (Teamleitung HPC – High Performance Computing)
Email: cms-benutzerberatung@hu-berlin.de
Project Website: https://fonda.hu-berlin.de/?page_id=315

Recorded: 2026-01-11
Source: https://www.cms.hu-berlin.de/de/ueberblick/projekte/fonda