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FAIR data is data which meets the FAIR principles of findability, accessibility, interoperability, and reusability (FAIR). [ 1 ] [ 2 ] The acronym and principles were defined in a March 2016 paper in the journal Scientific Data by a consortium of scientists and organizations.
FAIR data, data which meet standards of findability, accessibility, interoperability and reusability; First article inspection report, a formal method of providing a measurement report for a given manufacturing process
Fair Information Practice was initially proposed and named [5] by the US Secretary's Advisory Committee on Automated Personal Data Systems in a 1973 report, Records, Computers and the Rights of Citizens, [6] issued in response to the growing use of automated data systems containing information about individuals. The central contribution of the ...
The first English use of the word "data" is from the 1640s. The word "data" was first used to mean "transmissible and storable computer information" in 1946. The expression "data processing" was first used in 1954. [6] When "data" is used more generally as a synonym for "information", it is treated as a mass noun in singular form.
CODATA supports the Data Science Journal [6] and collaborates on major data conferences like SciDataCon [7] and International Data Week. [8]In October 2020 CODATA is co-organising an International FAIR Symposium [9] together with the GO FAIR initiative to provide a forum for advancing international and cross-domain convergence around FAIR.
However, data has staged a comeback with the popularisation of the term big data, which refers to the collection and analyses of massive sets of data. While big data is a recent phenomenon, the requirement for data to aid decision-making traces back to the early 1970s with the emergence of decision support systems (DSS).
Data management has recently become a primary focus of the policy and research debate on open scientific data. The influential FAIR principles are voluntarily centered on the key features of "good data management" in a scientific context. [44] In a research context, data management is frequently associated to data lifecycles. Various models of ...
A data commons is an interoperable software and hardware platform that aggregates (or collocates) data, data infrastructure, and data-producing and data-managing applications in order to better allow a community of users to manage, analyze, and share their data with others over both short- and long-term timelines.