Property Graph Framework for Geographical Routes in Sports Training

Abstract

Presenting real-world paths in property graphs is a complex challenge of identifying and representing the properties of routes and their environments. These property graphs serve as foundational datasets for generating smart sports training routes, where route features such as terrain, bends, and hills critically influence the route design. This paper outlines a method for identifying key parameters of real-world paths and encoding them into property graphs. The proposed method has significant implications for sports event planning, particularly in designing route-based training that meets specific athletic challenges. The research concludes by presenting a case study in which a property graph that enables cycling route generation was created for the country of Slovenia, and a sample training route was generated.

Keywords

• property graph
• geographical maps
• smart sports training
• data mining
• data fusion
• OpenStreetMap