Data visualization opportunities

Here we offer Orcasound data products that data scientists and bioacousticians may enjoy visualizing and analyzing. Acoustic bouts define a time series of valuable signals in the Orcasound audio data streams. Human and machine detections indicate when community scientists or automated algorithms hear signals of interest while listening to Orcasound live audio streams.

Acoustic bouts

These are periods of time when interesting signals were detected within the Orcasound live audio streams. Some were detected by human listeners via the Orcasound web app (version 2 launched May, 2020); others were detected by automated algorithms, like OrcaHello (deployed in Sep/Oct, 2020). Each acoustic bout is ultimately defined first through a combination of human and machine detections, often contextualized by observations by local sighting networks, with start and end times usually extended to include weak signals and background noise conditions (before and after the event) through manual inspection by bioacoustic experts.

The primary focus is on SRKW bouts, but our archive includes bouts of signals from Bigg's killer whales, humpback whales, and other soniferous species of the Salish Sea.

• Google spreadsheet of Orcasound acoustic bouts

Human detections

15 May 2021 data clip

Version 2 of the live-listening web app offered an interactive feature to community scientists: a button to select whenever they heard anything interesting. Free text annotations were stored along with a datetime stamp (the time at which the tag was submitted). This is a ~9-month clip of the Heroku-hosted PostgreSQL database that holds these human detections. It was generated and analyzed in a preliminary fashion during a DemocracyLab hackathon associated with Western Governors' University. The students have provided some tips on ingesting and processing these data in the hackathon project Google doc.

• Raw exported data from Heroku dashboard by Scott
  • Dump of full Postgres database (binary)
  • Raw .csv
  • Raw JSON
• Cleaned CSV (removed rows with incomplete fields before 8/30/2019)
• Cleaned CSV in Google sheets

Machine detections

16 Sep 2021 OrcaHello detection table snapshot

• Raw JSON
• Acquired quasi-manually using Microsoft Azure Storage Explorer [Cosmo DB Accounts (deprecated)]
• (CosmoDB = aifororcasmetadatastore; predictions --> metadata --> Documents; query "SELECT * FROM c")
• 3457 total candidates: 2639 moderated; 818 unmoderated.
• 2280 false positives (86%); 347 true positives (13%); 12 unknown (1%).

API access

Un/moderated output from the real-time inference system (Cosmos database via Swagger)

• API for OrcaHello
• OrcaHello dashboard with summary of raw and moderated 60-second candidates