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FAIR Vocabularies in Population Research

Authors: IUSSP-CODATA Working Group On FAIR Vocabularies; , Alter;

FAIR Vocabularies in Population Research

Abstract

IUSSP and CODATA co-sponsored a working group to study how population research can benefit from the rapidly developing standards and technologies associated with the FAIR principles that all data should be “Findable, Accessible, Interoperable, and Reusable” by both humans and machines (Wilkinson et al., 2016). Demography is an empirically focused field with a long tradition of widely shared, easily accessible, data collections. FAIR vocabularies, which allow machines to associate data with concepts, can save researchers hours of tedious work by automating processes of data discovery and harmonization. The report introduces readers to international standards for documenting data (metadata) that underlie international infrastructures for producing and disseminating demographic data, and it recommends enhancing these services through application of the FAIR principles. The report builds on the “Ten Simple Rules for making a vocabulary FAIR” (Cox et al., 2021), prepared by a group formed at a workshop convened by CODATA and DDI to describe how a FAIR vocabulary will work with international standards for documenting and sharing social science data. The working group calls for IUSSP to create a FAIR Vocabulary of Demography. Online vocabularies including demographic terms already exist, and most of them define key terms in ways incompatible with demography. Population research will be at a disadvantage without an authoritative FAIR vocabulary of its own. Fortunately, a new FAIR Vocabulary of Demography can build upon IUSSP’s long history of support for dictionaries of demography in multiple languages.

Keywords

FAIR Vocabularies, IUSSP, Terminologies, CODATA, Demography, FOS: Sociology, FAIR, Population Science

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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