TY - CHAP

T1 - NFDI4DS Infrastructure and Services

AU - Schimmler, Sonja

AU - Wentzel, Bianca

AU - Bleier, Arnim

AU - Dietze, Stefan

AU - Karmakar, Saurav

AU - Mutschke, Peter

AU - Kraft, Angelie

AU - Taffa, Tilahun A.

AU - Usbeck, Ricardo

AU - Boukhers, Zeyd

AU - Auer, Sören

AU - Castro, Leyla Jael

AU - Ackermann, Marcel R.

AU - Neumuth, Thomas

AU - Schneider, Daniel

AU - Abedjan, Ziawasch

AU - Latif, Atif

AU - Limani, Fidan

AU - Ahmad, Raia Abu

AU - Rehm, Georg

AU - Khorasani, Sima Attar

AU - Lieber, Matthias

N1 - Conference code: 53

PY - 2023/12/4

Y1 - 2023/12/4

N2 - 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.

AB - 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.

KW - NFDI

KW - NFDI4DS

KW - Research Data Infrastructures

UR - http://www.scopus.com/inward/record.url?scp=85181128596&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/aeef32be-854c-3f08-9b99-86cf2576e3ed/

M3 - Article in conference proceedings

AN - SCOPUS:85181128596

SN - 9783885797319

T3 - Lecture Notes in Informatics (LNI), Proceedings

SP - 921

EP - 926

BT - INFORMATIK 2023 - Designing Futures

A2 - Klein, Maike

A2 - Krupka, Daniel

A2 - Winter, Cornelia

A2 - Wohlgemuth, Volker

PB - Gesellschaft für Informatik e.V.

T2 - 53. Annual Meeting of the German Informatics Society (GI) - INFORMATICS 2023

Y2 - 26 September 2023 through 29 September 2023

ER -