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Sharing data and code for reuse have become increasingly important in scientific work over the past decade. However, in practice, shared data and code may be unusable, or published results obtained from them may be irreproducible. Data repository features and services contribute significantly to the quality, longevity, and reusability of datasets. This paper presents a combination of original and secondary data analysis studies focusing on computational reproducibility, data curation, anddoi:10.3390/data6020015 fatcat:puufemmjkfelbijf2q65jjkb2i