From data to information A start document for setting up a functional blueprint that makes data generated with automatic bat detectors available for a broad use

Bat research has developed significantly in the past decades. New technologies and the enhanced practicality of new generations of ultrasound or bat detectors contributed to this development. Bat detectors are all about making ultrasound audible and/or recordable. Basically bat detectors have evolved from tuneable heterodyne detectors (narrow band, HET), via frequency division (broad band, FD), time expansion (broad band, TE) to real time ultrasound recording (RT). Especially the last technique innovates bat research through the employment of bat detectors that use automatic triggering and real time recording. Development of high speed soundcards and/or high frequency digitizing of sound have made digital recording in real time possible. Automated triggering has made the employment of standalone bat detectors possible. This automated RT equipment records ultrasonic sounds automatically in reaction on a pre-set trigger (frequency + sound level at certain frequencies). The system is not dependent on a human reacting to an ultrasound event with an active recording, thus creating new opportunities for standardised methods for active and long term data collecting regarding species presence and/or bat activity on a global scale. Involvement of appropriately trained and coordinated volunteers in surveys using broadband RT bat detectors creating increased species coverage and objectivity of species identification, embody the future in developing comprehensive bat monitoring programmes (Barlow et al., 2015). Automatic bat detectors however, generate big amounts of data, especially when combined with large scale utilization in e.g. citizen science projects.

Our goals are: 1) To carry out an analysis of problems and opportunities, 2) with a team of people that have experience in processing big amounts of data/analysing sounds files of bats, 3) in which bottlenecks in the data use, data processing and data presentation will be identified and prioritized, 4) and the relevant questions and proposals of solutions of the bottlenecks will be formulated