Theoretical framework and visualization research on comprehensive statistical modernization based on multi-source data fusion from a think tank development perspective

Think tanks now face a critical challenge in their development: how to access high-quality statistical outputs for evidence-based decision-making. Statistical agencies serve as data suppliers, while think tanks act as data processors. However, a persistent disconnect exists—manifested as delays in supplier deliveries or processors inability to utilize novel data materials. In this case, comprehensive statistical modernization applies modern information technology, data science methods, and advanced management concepts to build an intelligent, integrated, and high-value statistical ecosystem, completing a systematic transformation and upgrade of the traditional statistical system, which holds significant practical implications for advancing think tank development. However, there are common-seen limitations such as a single dimension for depicting things, a heavy burden of data reporting, and the heterogeneity of different objects leading to data incomparability. To better address these issues, the article systematically reviewed the current literature on multi-source data fusion and modernization of comprehensive statistics, summarized the theoretical basis of modernization of comprehensive statistics, and proposed the comprehensive statistical modernization development theory of multi-source data. Specifically, the theory consists of a multi-source data collection theory, a comprehensive statistical modernization development index establishment theory, and visualization analysis theory, which help to accomplish the evaluation and monitoring of the development status of modernization of comprehensive statistics can be achieved, and provide methodological support and practical reference for think tank development.