RMQi

RMQi, short for Robust Metric for Quality of Information, is a framework and set of metrics intended to quantify information quality across digital content and AI outputs. It defines a composite Quality Index (QI) that combines several dimensions to rate information on a 0 to 1 scale, enabling comparisons across sources, formats, and contexts.

The framework identifies core dimensions: accuracy, completeness, timeliness, relevance, and clarity. It also includes governance and accessibility aspects such as bias, interpretability, and ease of access. Each dimension is scored via a mix of automated indicators and human judgments; weights can be configured for domain relevance. The overall RMQi score is computed as a weighted aggregation of dimension scores, with calibration procedures to ensure cross-domain consistency.

Development and adoption: RMQi emerged from collaborative research and industry initiatives beginning in 2018, with ongoing refinements and open-source evaluation tools. It is used by some information platforms to benchmark content quality, guide filtering and ranking, and support data governance programs. The framework is not universally standardized, and implementations vary by organization; critics note the subjectivity of certain dimensions and the resource costs of evaluation.

See also information quality, data quality metrics, information retrieval.