Towards assessing the quality of volunteered geographic information from OpenStreetMap for identifying critical infrastructures
Benjamin Herfort, Melanie Eckle, João Porto de Albuquerque, Alexander Zipf
Identifying the assets of a community that are part of its Critical Infrastructure (CI) is a crucial task in emergency planning. However, this task can prove very challenging due to the costs involved in defining the methodology and gathering the necessary data. Volunteered Geographic Information from collaborative maps such as OpenStreetMap (OSM) may be able to make a contribution in this context, since it contains valuable local knowledge. However, research is still due to assess the quality of OSM for the particular purpose of identifying critical assets. To fill this gap, this paper proposes a catalogue of critical asset types, based on the analysis of different reference frameworks. We thus analyze how good the emergent OSM data model is for representing these asset types, by verifying whether they can be mapped to tags used by the OSM community. Results show that critical asset types of all selected sectors and branches are well represented in OSM.