The Data Quality Co-op platform uses a shared infrastructure for measuring data integrity to help address data quality challenges, inconsistencies and disruptions.

Therefore, the platform aggregates, analyses and benchmarks data quality signals across studies, suppliers and time, according to the Data Quality Co-op. 

The Data Quality Co-op said that its platform was inspired by clearinghouses used in finance, advertising and customer reviews, and said that the platform would learn from quality signals inputted over time to help improve research outcomes.

Key capabilities on the platform include supplier benchmarking, custom filters and dashboards survey-level data exports and automated vendor scorecards.

The platform also aggregates in-survey and outside-survey data from across the market research industry – including on issues such as bot detection, open-end analysis and identity resolution – to create a unified view of quality.

Bob Fawson, co-founder at Data Quality Co-op, said: “It’s becoming increasingly difficult to determine if data is collected from qualified people.

“We created DQC to give the industry a common language, independent standards for quality, and proactive solutions – so that everyone from procurement teams to researchers and suppliers can operate with more confidence and less guesswork.”