Recent advancements in data collection have expanded the tools available for urban science, economic, and real estate research. The integration of diverse data sources has supported the development of ``smart city'' initiatives in city governance and driven the adoption of data-centric strategies in business applications.

This paper presents an overview of big data sources used in urban science and urban economics, with the goal of directing and enriching future research in these and other fields. We structure our discussion around data origins and analytical methods, discussing geographic information maps, GPS and CDR, textual repositories, social media, credit card transactions, street imagery, sensor readings, volumetric data, street patterns, transportation metrics, public records, historical data, business analytics, real estate transactions, and crowdsourced inputs. While aiming to provide an overarching perspective, we also touch upon common challenges in urban big data research, especially those unique to data collection, analysis, and inference.