NFDI4DS Infrastructure and Services
Abstract: NFDI4DataScience (NFDI4DS) is a consortium founded to support researchers in all stages of the research data lifecycle in order to conduct their research in line with the FAIR principles. The infrastructure developed targets researchers from a wide range of disciplines working in the field of data science and artificial intelligence. NFDI4DS contributes to systematically understanding the needs and challenges of researchers in various disciplines regarding data science and artificial intelligence, keeping in mind ethical, legal and social aspects. The identified needs will be addressed by support structures such as educational videos and challenges. Transparency, reproducibility and FAIRness will be improved by integrating existing and newly developed services into the NFDI4DS infrastructure, and by systematically adding all digital objects (articles, data, machine learning models, workflows, scripts/code, etc.) to the NFDI4DS research knowledge graph. This paper presents the goals of NFDI4DS, and gives an overview on what the consortium is going to contribute to the data science and artificial intelligence communities. It focuses on existing and newly developed services and their integration.
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@inproceedings{DBLP:conf/gi/SchimmlerWBDKMK23,
author = {Sonja Schimmler and
Bianca Wentzel and
Arnim Bleier and
Stefan Dietze and
Saurav Karmakar and
Peter Mutschke and
Angelie Kraft and
Tilahun Abedissa Taffa and
Ricardo Usbeck and
Zeyd Boukhers and
S{\"{o}}ren Auer and
Leyla Jael Castro and
Marcel R. Ackermann and
Thomas Neumuth and
Daniel Schneider and
Ziawasch Abedjan and
Atif Latif and
Fidan Limani and
Raia Abu Ahmad and
Georg Rehm and
Sima Attar{-}Khorasani and
Matthias Lieber},
editor = {Maike Klein and
Daniel Krupka and
Cornelia Winter and
Volker Wohlgemuth},
title = {{NFDI4DS} Infrastructure and Services},
booktitle = {53. Jahrestagung der Gesellschaft f{\"{u}}r Informatik, {INFORMATIK}
2023, Designing Future - Zuk{\"{u}}nfte gestalten, Berlin, Germany
September 26-29, 2023},
series = {{LNI}},
volume = {{P-337}},
pages = {919--924},
publisher = {Gesellschaft f{\"{u}}r Informatik, Bonn},
year = {2023},
url = {https://doi.org/10.18420/inf2023\_103},
doi = {10.18420/INF2023\_103},
timestamp = {Thu, 23 Jan 2025 21:41:51 +0100},
biburl = {https://dblp.org/rec/conf/gi/SchimmlerWBDKMK23.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}