A data driven learning approach for the assessment of data quality.

ABSTRACT:

Background

Data quality assessment is important but complex and task dependent. Identifying suitable measurement methods and reference ranges for assessing their results is challenging. Manually inspecting the measurement results and current data driven approaches for learning which results indicate data quality issues have considerable limitations, e.g. to identify task dependent thresholds for measurement results that indicate data quality issues.

Objectives

To explore the applicability and potential benefits of a data driven approach to learn task dependent knowledge about suitable measurement methods and assessment of their results. Such knowledge could be useful for others to determine whether a local data stock is suitable for a given task.

Methods

We started by

SUBMITTER: Tute E 

PROVIDER: S-EPMC8561935 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature