From Data to City Indicators: A Knowledge Graph for Supporting Automatic Generation of Dashboards
This work addresses the problem of data integration and visualization for city planners in Smart Cities, but it is incremental as it applies existing knowledge graph techniques to a specific domain.
The paper tackles the challenge of calculating and comparing city indicators by developing a knowledge graph and ontology to support automatic dashboard generation, demonstrating its implementation in an urban mobility context.
In the context of Smart Cities, indicator definitions have been used to calculate values that enable the comparison among different cities. The calculation of an indicator values has challenges as the calculation may need to combine some aspects of quality while addressing different levels of abstraction. Knowledge graphs (KGs) have been used successfully to support flexible representation, which can support improved understanding and data analysis in similar settings. This paper presents an operational description for a city KG, an indicator ontology that support indicator discovery and data visualization and an application capable of performing metadata analysis to automatically build and display dashboards according to discovered indicators. We describe our implementation in an urban mobility setting.