The aim of this paper is to perform research, propose a concept and identify conventional and emerging data sources that will be used as a base for quality data-driven decision-making in the area of urban mobility management in small/medium-sized cities. Conventional data sources have been identified and required data sets have been defined using existing standardized data protocols. In order to take advantage of emerging unconventional data sources, two potential data sources were identified that could be used for urban traffic management. These data sources include crowdsourcing data from smart city sharing economy service application and data from the mobile network operator. Since these data sources are not defined by existing standards, an exchange scope and format has been defined between data source and data consumer in order to enable data flow. The concept was tested at the prototype level and at the data exchange level during the research project in the City of Rijeka.