Data Empowerment for Intelligent Decision-Making: A Data-Driven Online Intelligent Analysis Platform for Institutional Research Levels

In the context of the digital intelligence era, the volume of scientific research data has surged dramatically, driving a fundamental transformation in research management activities toward intelligent and information-based approaches. Based on an in-depth analysis of the management needs of scientific research institutions, this paper designs and implements a data-driven online intelligent analysis platform for institutional research performance, aiming to provide decision support and reference for scientific governance. The platform integrates big data and artificial intelligence technologies, utilizing methodologies such as bibliometrics and data mining to consolidate multi-source data. By incorporating hierarchical segmentation, it meets the diverse management requirements of users at different organizational levels and supports flexible and comprehensive business decision-making. Taking the Shandong Academy of Sciences as a case study, the paper illustrates the practical workflow of quantitative assessment and decision optimization of scientific outcomes across macro, meso, and micro levels. Driven by data analytics, the platform advances the scientific rigor, standardization, and transparency of research management, offering valuable insights and experiences for the digital and intelligent transformation of scientific governance.