A revision and analysis of the comprehensiveness of the main longitudinal studies of human aging for data mining research

Human ageing is a global problem that will have a large socio-economic impact. A better understanding of ageing can direct public policies that minimize its negative effects in the future. Over many years, several longitudinal studies of human ageing have been conducted aiming to comprehend the phenomenon, and various factors influencing human ageing are under analysis. In this review, we categorize the main aspects affecting human ageing into a taxonomy for assisting data mining research on this topic. We also present tables summarizing the main characteristics of 64 research articles using data from ageing-related longitudinal studies, in terms of the ageingrelated aspects analysed, the main data analysis techniques used, and the specific longitudinal database mined in each article. Finally, we analyse the comprehensiveness of the main databases of longitudinal studies of human ageing worldwide, regarding which proportion of the proposed taxonomy’s aspects are covered by each longitudinal database. We observed that most articles analysing such data are using classical (parametric, linear) statistical techniques, with little use of more modern (non-parametric, non-linear) data mining methods for analysing longitudinal databases of human ageing. We hope that this article will contribute to data mining research in two ways: first, by drawing attention to the important problem of global ageing and the free availability of several longitudinal databases of human ageing; second, by providing useful information to make research design choices about mining such data, e.g. which longitudinal study and which types of ageing-related aspects should be analysed, depending on the research’s goals.