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The vocabulary consists of 3 categories\u2014<jats:styled-content style=\"fixed-case\">R<\/jats:styled-content>esearch <jats:styled-content style=\"fixed-case\">D<\/jats:styled-content>ata <jats:styled-content style=\"fixed-case\">P<\/jats:styled-content>ractices, <jats:styled-content style=\"fixed-case\">D<\/jats:styled-content>ata, and <jats:styled-content style=\"fixed-case\">C<\/jats:styled-content>uration\u2014with 187 terms validated through empirical studies of scientific data practices in the <jats:styled-content style=\"fixed-case\">E<\/jats:styled-content>arth and life sciences. The present article covers the <jats:styled-content style=\"fixed-case\">DPCV<\/jats:styled-content>ocab development process and examines applications for mapping relationships across the 3 categories, identifying factors for projecting curation costs and important differences in curation requirements across disciplines. As a tool for curators, the vocabulary provides a framework for charting curation options and guiding systematic administration of curation services. It can serve as a shared terminology or <jats:italic>lingua franca<\/jats:italic> to support interactions and collaboration among curators, data producers, system developers, and other stakeholders in data infrastructure and services. 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