NFDI4DS Gateway and Portal
Research output: Journal contributions › Conference abstract in journal › Research › peer-review
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In: Proceedings of the Conference on Research Data Infrastructure, Vol. 1, 07.09.2023.
Research output: Journal contributions › Conference abstract in journal › Research › peer-review
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TY - JOUR
T1 - NFDI4DS Gateway and Portal
AU - Usbeck, Ricardo
AU - Taffa, Tilahun Abedissa
AU - Veliz, Rudy Alexandro Garrido
AU - Abdullah, Rana
AU - Shams, Najeebullah
AU - Wentzel, Bianca
AU - Chen, Zongxiong
AU - Schimmler, Sonja
N1 - Conference code: 1
PY - 2023/9/7
Y1 - 2023/9/7
N2 - ©NFDI4DataScience (NFDI4DS) is a consortium to support researchers in all stages of the research data lifecycle to conduct their research in line with the FAIR principles. The developed infrastructure targets researchers from a wide range of disciplines in data science and AI. We present the ideas of the NFDI4DS gateway and the NFDI4DS portal. Two approaches to navigate digital objects (articles, data, machine learning models, workflows, scripts/code, etc.) from various NFDI4DS resources such as the ORKG, the DBLP database, and other research knowledge graphs (KGs). Transparency, reproducibility, and fairness will be fostered by a step-wise integration of existing and newly developed services into the overall system. With this paper, we want to engage with the community and understand the needs and challenges of researchers in various disciplines regarding data science and AI. Therefore, we will discuss the currently developed prototypes and outline our plans for future development steps.
AB - ©NFDI4DataScience (NFDI4DS) is a consortium to support researchers in all stages of the research data lifecycle to conduct their research in line with the FAIR principles. The developed infrastructure targets researchers from a wide range of disciplines in data science and AI. We present the ideas of the NFDI4DS gateway and the NFDI4DS portal. Two approaches to navigate digital objects (articles, data, machine learning models, workflows, scripts/code, etc.) from various NFDI4DS resources such as the ORKG, the DBLP database, and other research knowledge graphs (KGs). Transparency, reproducibility, and fairness will be fostered by a step-wise integration of existing and newly developed services into the overall system. With this paper, we want to engage with the community and understand the needs and challenges of researchers in various disciplines regarding data science and AI. Therefore, we will discuss the currently developed prototypes and outline our plans for future development steps.
KW - Informatics
KW - Enabling RDM
KW - Linking RDM
KW - Fair
KW - FDO
KW - Business informatics
UR - https://www.tib-op.org/ojs/index.php/CoRDI/issue/view/12
UR - https://www.mendeley.com/catalogue/52b2ee09-6b05-3593-89b5-142724b82688/
U2 - 10.52825/CoRDI.v1i.391
DO - 10.52825/CoRDI.v1i.391
M3 - Conference abstract in journal
VL - 1
JO - Proceedings of the Conference on Research Data Infrastructure
JF - Proceedings of the Conference on Research Data Infrastructure
SN - 2941-296X
T2 - 1st Conference on Research Data Infrastructure
Y2 - 12 September 2023 through 14 September 2023
ER -