The guidelines offer tips for applying different machine learning techniques in assessing quality of surveys, on use of technology, and essential checklists in following operational procedures for ensuring data quality
NEW DELHI: The Union government on Wednesday released ‘National Guidelines for Data Quality in Surveys’ to provide comprehensive guiding principles and best practices for mitigating errors and biases that may occur during survey design, data collection and analysis, thereby ensuring data quality in surveys, specifically for demographic, health and nutrition surveys.
The guidelines are the initiative of National Data Quality Forum (NDQF), a multi-stakeholder, collaborative platform housed at the Indian Council of Medical Research-National Institute of Medical Statistics (ICMR-NIMS). The NDQF aims to guide advanced data quality monitoring, process audits and analytics, and capacity building of data collection agencies /producers to improve the quality of demographic, nutrition and health surveys.
M Vishnu Vardhana Rao, director, ICMR-NIMS, said, “Many governmental as well as non-governmental organisations conduct a number of important surveys to collect data on health and nutrition status of citizens of India. These guidelines entitled National Guidelines for Data Quality in Surveys will be a useful resource for those who are involved in planning and execution of surveys and will help improve data quality and evidence-based decision-making."
These guidelines, the government said, will be useful for a wide range of audiences working on health and nutrition viz., government and private data producers and users, national and regional level policymakers, and technical staff at the ministries and organisations, besides academic, research institutions and survey agencies for planning, designing and execution of sample surveys.
The guidelines provides steps to be followed during the three critical phases of field based studies - preparatory, during, and post data collection. They also offer tips for applying different machine learning techniques in assessing the quality of surveys, on use of technology, and essential checklists in following operational procedures for ensuring data quality.
"National Guidelines for Data Quality in Surveys is a much-needed resource for all those undertaking demographic, health and nutrition surveys and will go a long way to improve quality of data collected in the country and elsewhere," V K Paul, Member, NITI Aayog said.