Towards Understanding Mobility in Museums

Abstract

Data mining techniques can provide valuable insight to understand mobility in museums. However, the results of such techniques might not be easily understood by the museum staff. In this paper, we propose a graph-based approach to model museum exhibitions, sensor locations, and guiding tasks. We further discuss how route-based trajectory mining can be adapted to work with this graph model and which challenges need to be addressed to cope with the graph dynamics and the continuous flow of sensor data. Based on the demands of two target groups, curators and visitors, three applications are proposed: a museum graph editor, a mobile museum guide, and a curator decision support. We propose an architecture for a platform that provides context information and data mining results to such applications. We claim that our proposed platform can cover many aspects and demands that arise in the museum environment today.