A data quality strategy to enable FAIR, programmatic access across large, diverse data collections for high performance data analysis

A data quality strategy (DQS) is useful for researchers, organizations, and others, primarily because it allows them "to establish a level of assurance, and hence confidence, for [their] user community and key stakeholders as an integral part of service provision." Evans et al. of the Australian National University, recognizing this importance, discuss the implementation of their DQS at the Australian National Computational Infrastructure (NCI), detailing their strategy and providing examples in this 2017 paper. They conclude that "[a]pplying the DQS means that scientists spend less time reformatting and wrangling the data to make it suitable for use by their applications and workflows—especially if their applications can read standardized interfaces."

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