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2024 NFDI4DS ConferenceIn-Person Event

→ Europe/Berlin
Hall (Berlin Weizenbaum Institute)

Hall

Berlin Weizenbaum Institute

Hardenbergstraße 32, 10623 Berlin
Description

2024 NFDI4DS Conference

Dear community,

we are excited to announce this year's NFDI4DS conference.

This year we are co-located with the EOSC Symposium and the EOSCxNFDI event in Berlin as well as our 2024 NFDI Science Slam.

The vision of NFDI4DS is to support all steps of the complex and interdisciplinary research data lifecycle, including collecting/creating, processing, analyzing, publishing, archiving, and reusing resources in Data Science and Artificial Intelligence.

The overarching objective of NFDI4DS is the development, establishment, and sustainment of a national research data infrastructure (NFDI) for the Data Science and Artificial Intelligence community in Germany. 

Interested in giving in lightning talk? Please contact us via: nfdi4ds@fokus.fraunhofer.de

Our conference venue is the Weizenbaum Institut within walking distance to Berlin Zoo.

We look forward to seeing you at the event.

Contact
    • 8:30 AM
      Arrival & Coffee
    • 1
      Welcome & Overview
    • 2
      NFDI4DS at a Glance

      Introduction to NFDI4DataScience and it's task areas and working groups

      • a) TA1 Community and Training

        Task Area 1: Community and Training

        Speaker: Anna-Lena Lorenz (TIB)
      • b) TA2 Research Knowledge Graphs

        Task Area 2: Research Knowledge Graphs

        Speaker: Peter Mutschke (GESIS)
      • c) TA3 Infrastructure and Services

        Task Area 3: Infrastructure and Services

        Speaker: Leyla Jael Garcia-Castro (ZB MED)
      • d) TA4 Transfer and Application

        Task Area 4: Transfer and Application

        Speaker: Raia Abu Ahmad (DFKI)
      • e) WG1 Shared Tasks

        Working Group 1: Shared Tasks

        Speaker: Raia Abu Ahmad (DFKI)
      • f) WG2 Metadata

        Working Group 2: Metadata

        Speaker: Peter Mutschke (GESIS)
    • 3
      Collaborators
      • a) OpenAIRE

        OpenAIRE

        Speaker: Natalia Manola (OpenAIRE)
      • b) Cluster of Excellence: Machine Learning - New Perspectives for Science

        Cluster of Excellence: Machine Learning - New Perspectives for Science

        Speaker: Tilmann Gocht (Uni Tübingen)
      • c) FAIR Research Data Management with PIDs: Insights from PID4NFDI

        FAIR Research Data Management with PIDs: Insights from PID4NFDI

        Speaker: Jana Böhm (GWDG, PID4NFDI)
      • d) The BERD Services

        The BERD Services

        Speaker: Ulrich Krieger (Uni Mannheim, BERD@NFDI)
      • e) Introduction to NFDIxCS

        Introduction to NFDIxCS - National Research Data Infrastructure for and with Computer Science

        Speaker: Anh Duc Vu (GI, NFDIxCS)
    • 4
      Questions & Discussion
    • 10:30 AM
      Coffee Break
    • 5
      NFDI4DS Deep Dive 1

      Deep Dive into the NFDI4DataScience Task Areas

      • a) Dive into TA 1 Community and Training
        Speaker: Anna-Lena Lorenz (TIB)
      • b) Dive into TA 2 Research Knowledge Graphs
        Speaker: Peter Mutschke (GESIS)
      • c) Dive into TA 3 Infrastructure and Services
        Speaker: Leyla Jael Castro (ZB MED Information Centre for Life Sciences)
      • d) Dive into TA 4 Transfer and Application
        Speaker: Raia Abu Ahmad (DFKI)
    • 6
      NFDI Science Slam
      • a) Overview of NFDI

        NFDI Overview

        Speaker: Cord Wiljes (NFDI e.V.)
      • b) The Fairytale of Base4NFDI

        The Fairytale of Base4NFDI

        Speaker: Franziska Fritsche (GESIS, Base4NFDI)
    • 7
      Questions & Discussion
    • 12:15 PM
      Lunch Break
    • 8
      NFDI4DS Deep Dive 2

      Deep Dive into NFDI4DataScience Working Groups

      Talks to specialized topics

      • a) Dive into WG 1 Shared Tasks
        Speaker: Raia Abu Ahmad (DFKI)
      • b) Dive into WG 2 Metadata
        Speaker: Peter Mutschke (GESIS)
      • c) FAIR principles for Machine Learning models

        FAIR principles for Machine Learning models

        Speaker: Fidan Limani (ZBW, NFDI4DS)
      • d) Extracting Machine Learning Model and Dataset Mentions from Large Bibliographic Corpora

        Extracting Machine Learning Model and Dataset Mentions from Large Bibliographic Corpora

        Speaker: Sharmila Upadhyaya (NFDI4DS)
    • 9
      Questions & Discussion
    • 10
      Panel Discussion

      Meet our Panelists

      TBD

      Questions and moderation by Sonja Schimmler (Fraunhofer FOKUS & TU Berlin, NFDI4DS)

    • 11
      Outlook & Goodbye
    • 3:00 PM
      Coffee & Departure
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