When dealing with large data sets (e.g. Terrabytes of PAM data) I first try to get an overview, e.g. using compressed spectrograms, say 1 spectrogram per day, or week (keyword Log-Term-Spectral-Average LTSA).

This gives me an overview on what to expect. In paricular it gives me time and spectral information on the species I'm interested in. This results also a rough auditing of the data set.

The next step is to zoom into a particular time to have more details and to verify if this is really the species I'm looking for. At the same time I can determine the parameter I need for an automatic detector (e.g. PAMGuard).

After that I would run the detector on the selected data snippet to obtain first results. I would then analyse the detections (discuss with experts) to assess if the detector is setup properly and the results are OK. I will be spending sufficient time on this part as it will condition the overall result.

Finally, if the detector analysis part is satisfactory and I understand the consequences of the parameter settings, then I'm ready to run the detector over the whole data set.

Concluding, I would like to stress that running software (here porpoise detector) on a large data set without first testing it, re-testing it with different parameters, and verifying the results is a recipe for waste of time or even failure.

OK, that is why you ask for a course, fair enough, but I'm a fan of learning by doing.

When dealing with large data sets (e.g. Terrabytes of PAM data) I first try to get an overview, e.g. using compressed spectrograms, say 1 spectrogram per day, or week (keyword Log-Term-Spectral-Average LTSA).

This gives me an overview on what to expect. In paricular it gives me time and spectral information on the species I'm interested in. This results also a rough auditing of the data set.

The next step is to zoom into a particular time to have more details and to verify if this is really the species I'm looking for. At the same time I can determine the parameters I need for an automatic detector (e.g. PAMGuard).

After that I would run the detector on the selected data snippet to obtain first results. I would then analyse the detections (discuss with experts) to assess if the detector is setup properly and the results are OK. I will be spending sufficient time on this part as it will condition the overall result.

Finally, if the detector analysis part is satisfactory and I understand the consequences of the parameter settings, then I'm ready to run the detector over the whole data set.

Concluding, I would like to stress that running software (here porpoise detector) on a large data set without first testing it, re-testing it with different parameters, and verifying the results is a recipe for waste of time or even failure.

OK, that is why you ask for a course, fair enough, but I'm a fan of learning by doing.

When dealing with large data sets (e.g. Terrabytes of PAM data) I first try to get me an overview, e.g. using compressed spectrograms, say 1 spectrogram per day, or weak (keyword Log-Term-Spectral-Average LTSA).

This gives me an overview on what to expect. In paricular if gives me time and spectral information on the species I'm interested in. This results also in a rough auditing of the data set.

The next step is to zoom into a paricular time to have more details and to verify if this is really the species I'm looking for. At the same time I can determine the parameter I need for an automatic detector (e.g. PAMGuard).

After that I would run the detector on the selected data snippet to obtain first results. I would then analyse the detections (discuss with experts) to assess if the detector is setup properly and the results are OK. I will be spending sufficient time on this part as it will condition the overall result.

Finally, if the detector analysis part is satisfactory and I understand the consequences of the parameter settings, then I'm ready to run the detector over the whole data set.

Concluding, I would like to stress that runing software (here porpoise detector) on a large data set without first testing it, re-testing it with different parameters, and verifying the results is a recipe for wast of time or even failure. OK, that is why you ask for a course, fair enough, but I'm a fan of learning by doing.

When dealing with large data sets (e.g. Terrabytes of PAM data) I first try to get an overview, e.g. using compressed spectrograms, say 1 spectrogram per day, or week (keyword Log-Term-Spectral-Average LTSA).

This gives me an overview on what to expect. In paricular it gives me time and spectral information on the species I'm interested in. This results also a rough auditing of the data set.

The next step is to zoom into a particular time to have more details and to verify if this is really the species I'm looking for. At the same time I can determine the parameter I need for an automatic detector (e.g. PAMGuard).

After that I would run the detector on the selected data snippet to obtain first results. I would then analyse the detections (discuss with experts) to assess if the detector is setup properly and the results are OK. I will be spending sufficient time on this part as it will condition the overall result.

Finally, if the detector analysis part is satisfactory and I understand the consequences of the parameter settings, then I'm ready to run the detector over the whole data set.

Concluding, I would like to stress that running software (here porpoise detector) on a large data set without first testing it, re-testing it with different parameters, and verifying the results is a recipe for waste of time or even failure.

OK, that is why you ask for a course, fair enough, but I'm a fan of learning by doing.