Survey-based investigation, feature extraction and classification of Greek municipalities maturity for open source adoption and migration prospects

Abstract While FOSS solutions have attracted a significant amount of attention, alongside with necessary and growing IT related expenditure for the digitalization of public administration, authorities face the question of whether migration to such solutions is feasible and/or worthwhile. The purpose of the presented work is to analyze existing domain research and extract key features, grouped in three major areas (namely Readiness, Ease of Use and Gain from migration), that should be investigated prior to a migration attempt. Following and building upon an extensive survey on Greek municipalities, the latter are categorized via the k-means non-supervised machine learning method to 3 levels of maturity regarding candidate participation in relevant projects. A combined scoring approach, based on similar features of the target FOSS solution as well as the aforementioned municipality categorization, is presented in order to detect a priori good candidate combinations (municipality and software) for minimizing a migration project risk. The method is validated through the aforementioned survey on municipalities with confirmed FOSS usage, indicating that selection in the proposed organized manner can aid in harvesting FOSS benefits. Furthermore, it is compared against a popular maturity model method (BPMMM) in order to comment on the applicability and classification process.