Science and technology fields and higher education institutions with mathematically trained contributors: Metadata analysis of IEEE papers

Recently, the shortage of mathematically trained individuals who can integrate mathematical knowledge and skills with other types of knowledge and skills and thereby contribute to innovation has become apparent. To find clues for solving this problem, we identify scientific and technology fields (STFs) that require mathematically trained contributors and identify higher education institutions (HEIs) that provide students an opportunity to develop the mathematical knowledge needed in the STFs. We perform this by analyzing a large amount of metadata of papers in IEEE journals, which is easily accessible via the Scopus API. The metadata contains author's affiliation information, which is useful for identifying HEIs with a mathematical faculty. For example, if an author's affiliation information contains terms related to mathematics such as “Department of Mathematics” or “Dept. of Math.,” the author can be considered to have had advanced mathematical training. We demonstrate that 1) the contributions of mathematically trained individuals to research fields covered by published IEEE papers have continued to increase, 2) their contributions are particularly important to micro-STFs such as information theory, reliability, fuzzy systems, and neural networks, and 3) the degree of their contributions to the various STF-focused journals differs between HEIs.