Guidelines for Data Acquisition, Quality and Curation for Observational Research Designs (DAQCORD).

ABSTRACT:

Background

High-quality data are critical to the entire scientific enterprise, yet the complexity and effort involved in data curation are vastly under-appreciated. This is especially true for large observational, clinical studies because of the amount of multimodal data that is captured and the opportunity for addressing numerous research questions through analysis, either alone or in combination with other data sets. However, a lack of details concerning data curation methods can result in unresolved questions about the robustness of the data, its utility for addressing specific research questions or hypotheses and how to interpret the results. We aimed to develop a framework for the design, documentation and reporting of data curation methods in order to advance the scientific r

SUBMITTER: Ercole A 

PROVIDER: S-EPMC7681114 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature