Results 31 to 40 of about 444,200 (304)
FAIR Data Maturity Model. Specification and Guidelines [PDF]
, 2020 Findability, Accessibility, Interoperability and Reusability – the FAIR principles – intend to define a minimal set of related but independent and separable guiding principles and practices that enable both machines and humans to find, access ...
FAIR Data Maturity Model Working Group
core +1 more source
Internet Archaeology, 2023 Making archaeological data available for the scientific community received a major boost through the ARIADNE Infrastructure projects that began in 2013.
Gerald Hiebel +3 more
doaj +1 more source
Workflow Recommendations for Enabling FAIR Data in the Earth, Space, and Environmental Sciences [PDF]
, 2018 As a part of the Enabling FAIR Data project led by the American Geophysical Union, the "Workflow Recommendations Between Data Repositories and Publishers" Targeted Adoption Group adopted and adapted work developed originally by the THOR project, funded ...
Patricia Cruse +2 more
core +1 more source
Das FAIR Data Maturity Model. Spezifikation und Leitlinien [PDF]
, 2020 Die FAIR-Prinzipien „Findability, Accessibility, Interoperability and Reusability“ (Auffindbarkeit, Zugänglichkeit, Interoperabilität und Nachnutzbarkeit) zielen darauf ab, ein Minimum an verwandten, aber unabhängigen und trennbaren Leitlinien und ...
RDA FAIR Data Maturity Model Working Group
core +1 more source
Interview Questions to Assess Current Plans and Implementations of the FAIR Principles by Data Repositories in Earth, Space, and Environmental Sciences [PDF]
, 2018 <p>As a part of the Enabling FAIR Data project led by the American Geophysical Union, the Repository Guidance Targeted Adoption Group discussed and designed an interview protocol to understand the ways that data repositories in the Earth, ...
Michael Witt +5 more
core +1 more source
FAIR-IMPACT project response to "FAIR Assessment Tools: Towards an "Apples to Apples" Comparisons" [PDF]
, 2023 At the end of 2022, the FAIR Metrics subgroup of the EOSC Association Task Force on FAIR Metrics and Data Quality published “FAIR Assessment Tools: Towards an "Apples to Apples" Comparisons” which describes some work done and suggestions for future ...
Jonquet, Clement +4 more
core +1 more source
Representative & Fair Synthetic Data
CoRR, 2021 Algorithms learn rules and associations based on the training data that they are exposed to. Yet, the very same data that teaches machines to understand and predict the world, contains societal and historic biases, resulting in biased algorithms with the risk of further amplifying these once put into use for decision support.
Paul Tiwald +2 more
openaire +2 more sources
Virus Outbreak Data Network [PDF]
, 2021 Heeft als doel om een (wereldwijd) implementatie netwerk op te zetten om wereldwijde data omtrent COVID-19 'FAIR' (findable, accessible, interoperable and reusable) te maken zodat deze data door mensen en machines (AI) gebruikt kan worden.
GO FAIR
core
oblassers/fair-data-science: FAIR Data Science Experiment [PDF]
, 2017 <p>First release of the FAIR Data Science proof of concept experiment.</p ...
oblassers
core +1 more source
OSSDIP: Open Source Secure Data Infrastructure and Processes Supporting Data Visiting
Data Science Journal, 2022 Meeting the conflicting goals of protecting and maintaining control over sensitive data while also allowing access by third parties constitutes a significant challenge.
Martin Weise +3 more
doaj +1 more source