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Translations Japanese – https://doi.org/10.18908/a.2019112601 (added 31.01.2020). Preamble One of the grand challenges of data-intensive science is to facilitate knowledge discovery by assisting humans and machines in their discovery of, access to, integration and analysis of, task-appropriate scientific data and their associated algorithms and workflows. Here, we describe FAIR – a set of guiding
Cite as: Data Citation Synthesis Group: Joint Declaration of Data Citation Principles. Martone M. (ed.) San Diego CA: FORCE11; 2014 https://doi.org/10.25490/a97f-egyk Translations Japanese – https://doi.org/10.11502/rduf_rdc_jddcp_ja (added 31.01.2020). >>> Endorsement List Preamble Sound, reproducible scholarship rests upon a foundation of robust, accessible data. For this to be so in practice as
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