with a sampling of 5 minutes, but soon it was noticed that with overcast skies, we miss some features within our light curves. Therefore in the next step the frequency was increased to a reading once per minute. This seems to be a good value for most applications and a good compromise between data storage, data handling and valuable information. But since we want to measure all possible variations that can occur, we even increased the sampling rate to a reading every 7 seconds which corresponds to a frequency of 0.143 Hz. The device measures accurately at that high frequency and so far we did not encounter any problems due to integration time limitations. We are able to detect lightning, fireworks and other short-term events. Moreover, with higher sampling it is possible to quantify the influence of the curfew in Vienna even in cloudy nights, when the light curves are much more disturbed.

### Automated data storage and publishing

All our data are logged and stored automatically at each monitoring station. From there every five minutes a synchronization script uploads the data to the University’s web server for data mirroring and data publishing leading to “real-time” data visualization on our 