Environmental scientists, especially those conducting studies in remote areas such as the Arctic, can benefit from assessing data quality from autonomous sensors in near-real time. The Data Assessment Run-Time (DART) framework was developed to allow environmental scientists to specify and verify data properties associated with autonomous sensors. Data properties are logical statements about data values associated with sensors and their relationship with other sensor output or properties derived from historical data. The properties can be verified at near-real time, i.e., as the data are being collected in the field, or through post-processing routines after the data has been collected. This paper describes a case study that evaluates the specification of data properties associated with hyperspectral sensor data and how the DART framework was used to verify these data in both near-real time and through post-processing.