Data are an integral part of the smart city and are used as input for decision-making, policy formation, and to inform citizens and businesses. Re flecting on our experience of developing software applications which rely on urban data, this article examines the veracity of such data (their authenticity and the extent to which they accurately (in terms of precision) and faithfully (in terms of fidelity, reliability) represent what they are meant to) and how this can be assessed. Open data are often provided with no guarantee about their veracity, continuity or lineage (in terms of documentation that establishes provenance). This allows data providers to share data with undocumented errors, absences and biases. These quality issues can propagate through systems and lead to poor software applications and unreliable 'evidence-based' decisions. In this article, we highlight the janitorial role carried out by data scientists and developers to ensure that data are cleaned, parsed, validated and transformed for use. This process requires eff ort, knowledge and skill but is rarely shared. We propose the inclusion of crowdsourcing mechanisms to record user observations and fixes for improving the quality of data within open government portals.