A Framework for Data Quality

Abstract

This report presents a framework for identifying data quality for all data, summarizes the current state of practice in identifying threats to data quality for the components of the framework, and provides guidance for promoting efective reporting of data quality. Statistical agencies in many countries have extensive, well-established methods for identifying and reporting threats to quality in data collected and designed for statistical purposes, particularly sample surveys. Methods are less well-developed for dealing with threats to quality from sources other than surveys, such as administrative records and readings from sensors, and other data originally collected for nonstatistical purposes.