Improve health and demographic data ecosystem in India by strengthening data quality as well as the systems that create and manage data; by deepening interests on the importance of good quality data among both producers and consumers and educate consumers to demand data of good quality.
The Data Quality Library is a resource collection of all scientific literature on data quality produced around the world. Become acquainted with books, periodicals, and research articles on data quality from trusted publishers and learn about various research tools.
This Knowledge Centre features publications, blogs, webinars, infographics, andother knowledge products on data quality generated by the activities of NDQF. These resources aim to inform audiences on the importance of data quality and the emerging solutions to address data quality challenges.
Dr. Himanshu K. Chaturvedi is a distinguished senior Scientist (Scientist G) and Director In-Charge at the National Institute for Research in Digital Health and Data Science (erstwhile NIMS), ICMR, New Delhi. His research areas of interest include Health Statistics and epidemiology, geospatial mapping of diseases, assessment of environmental and ecological predictors and statistical modelling of diseases. His major achievements include designing of sampling strategies for large scale national health surveys such as non-communicable diseases, monitoring survey, malaria surveillance study, etc. He has published more than 85 research articles in various reputed national and international journals related to public health. He supervised four PhD Research Scholars and three of them awarded PhD degree in medical statistics. He has been invited as an expert member of many national and international scientific committees, reviewer of many SCI journals, and an academic editor of an international journal (PLOS One).
Dr. Niranjan Saggurti is Director of the Population Council’s office in India. He provides strategic and technical leadership to Council’s work filling important knowledge gaps for policymakers and program managers – building evidence on what works and why. He has 20 years of experience in public health and policy-oriented research in sexual and reproductive health, migration, alcohol, gender-based violence, community mobilization and the intersection of these issues. He has published several papers in peer-reviewed journals on these topics. He currently serves as research advisor on several committees of the governmental and non-governmental organisations.
NDQF and its partners have developed two data quality assessment tools. The first one is an outlier detection tool, capable of detecting potential outliers in a dataset. The second one developed by IIIT, Delhi is data quality labelling tool, designed to provide a comprehensive quantitative assessment of the quality of a dataset.
