Networked embedded acoustic sensors and imagers allow scientists to observe biological and environmental phenomena at high sampling rates and multiple scales. Such sampling can create large data sets that often require some form of automated processing to extract useful information. However, to guarantee the accuracy of the data, the scientist must be included in the processing, rather than treating it as a black box, an approach we call interactive environmental sensing. In this paper we describe the challenges of such an approach and motivate it with several examples from bioacoustics, plant phenology and avian biology.