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ARDC FAIR Data 101 self-guided [PDF]
, 2021 FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course.
Brady, Catherine +13 more
core +1 more source
Nature Nanotechnology, 2021 Nanotechnology is a key enabling technology with billions of euros in global investment from public funding, which include large collaborative projects that have investigated environmental and health safety aspects of nanomaterials, but the reuse of accumulated data is clearly lagging behind. Here we summarize challenges and provide recommendations for
Nina Jeliazkova +37 more
openaire +9 more sources
Food for thought: Climate change risk and food (in)security in Tuvalu
Progress in Disaster Science, 2022 Climate change presents a considerable threat to food security of low-lying atoll nations in the Pacific including Tuvalu. It is projected to heavily impact agricultural and fishery sectors in Tuvalu, threatening food chains and the ability of Tuvaluans ...
Saamu Tui, Bapon Fakhruddin
doaj +1 more source
Supporting FAIR Data Management Planning Across Different Disciplines at the University of Sheffield
Data Science Journal, 2023 Recognition is growing sector-wide of the importance of FAIR data management planning in facilitating the sharing and reuse of research outputs.
Jenni Adams, Bev Jones, Helen Foster
doaj +1 more source
Dataset: FAIR Biomedical Research Software (FAIR-BioRS) manuscript [PDF]
, 2023 Data related to our FAIR-BioRS manuscript.
Patel, Bhavesh +3 more
core +1 more source
Dataset: FAIR Biomedical Research Software (FAIR-BioRS) manuscript [PDF]
, 2022 Data related to our FAIR-BioRS ...
Patel, Bhavesh +2 more
core +1 more source
Oblivious Data for Fairness with Kernels
CoRR, 2020 We investigate the problem of algorithmic fairness in the case where sensitive and non-sensitive features are available and one aims to generate new, `oblivious', features that closely approximate the non-sensitive features, and are only minimally dependent on the sensitive ones. We study this question in the context of kernel methods.
Grunewalder, Steffen, Khaleghi, Azadeh
openaire +5 more sources
The FAIR Data Pipeline command line tool [PDF]
, 2021 Command Line Interface for the FAIR Data Pipeline system, this software provides commands necessary for integrating analysis and data processing into the FAIR registry.If you use this software, please cite it using these ...
Zarebski, Kristian +3 more
core +1 more source
Achievements of the ARIADNE Initiative for Archaeological Data Sharing and Research
Internet Archaeology, 2023 The overall objective of the ARIADNE initiative is to help archaeological research and data management communities in Europe and beyond to more effectively share and use data that are dispersed across many institutions and projects.
Guntram Geser
doaj +1 more source
Commitment Statement to Enabling FAIR Data in the Earth, Space, and Environmental Sciences [PDF]
, 2018 <p>As a part of the Enabling FAIR Data project, a community-driven project led by the American Geophysical Union, developed a commitment statement defining for each stakeholder group their role in making data open and FAIR. In specific, moving
Enabling FAIR Data Community (8223777) +1 more
core +1 more source