Visualizing the quality of partially accruing data for use in decision making

The state of data management across the sciences is getting increasingly complex as data stores build up, and the world of public health is no less affected. Making sense of data is one portion of management, but quality analysis is also an important but slightly understated aspect as well. This 2015 paper by Eaton et al. explains a series of “data quality tools developed to gain insight into the data quality problems associated with these data.” The group concludes “our key insight was the need to assess temporal patterns in the data in terms of accrual lag.”

Please to read the entire article.