A heterogeneous key performance indicator metadata model for air quality monitoring in sustainable cities. (February 2021) - Zhou, Lianjie; Li, Qingquan; Tu, Wei; Wang, Chisheng
Abstract: Due to heterogeneous and inconsistent key performance indicators (KPIs) for the quantitative evaluation of a sustainable city's operational status, it is a great challenge to share multidimensional, multi-source and heterogeneous indicators. We propose a heterogeneous KPI capability representation model (HKPM) in our study. Based on the Meta Object Facility architecture, a nine-tuple multi-hierarchical meta-model is formulated to define the metadata components. Nine specific representation element datasets for specific KPIs are proposed to represent the meta-model. Besides, the KPI classification based on Sustainable Development Goals (SDGs) has been accomplished to support HKPM instantiated in concrete application. Experiments are conducted with the multi-type KPIs to validate the feasibility of HKPM, as shown in public service and Air Quality Index KPI instantiation example. Furthermore, the KPIs can be characterized in different dimensions, which can be modelled in a stereoscopic manner, promoting a comprehensive perception of sustainable cities. Highlights: A heterogeneous key performance indicator (KPI) meta model has been proposed. The KPI encoding heterogeneity in diverse metadata encoding standards have been sheltered via the proposed model. Sustainable Development Goals lay the foundation for the proposed model. The proposed model promotes a comprehensive perception of sustainable cities.