Quantifying the evolving topical structure of science across journals, countries, regions, and research domains

Abstract: Timely and comparable indicators of the evolving structure of science are increasingly needed for research policy and strategic planning. We present a reproducible and scalable framework for quantifying the topical prevalence and recent dynamics of scientific activity using open scholarly metadata from OpenAlex. The approach combines a unified topic ontology with simple trend estimators derived from short time series, enabling consistent comparisons across journals, countries, regions, and domain-focused corpora. We illustrate the methodology through representative case studies spanning generalist journals, national output, metropolitan research ecosystems, and structural biology. Across these examples, the framework captures both system-level normalization effects and fine-grained specialization patterns. Because the pipeline is fully general and based on open data, it can be readily extended to continuous, multi-scale monitoring of the scientific landscape. The proposed methodology provides a compact and interpretable quantitative layer that can complement expert assessment in science policy, research evaluation, and strategic decision-making.