Wildbook Release Notes - June 2020

The News Room
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Release notes for June 2020

Hey everyone! Here are the details of the major work completed over the last month.

New Wiki!
As part of ongoing efforts to improve your self-service resources, we’ve put together a Wildbook Wiki. It’s incomplete, but we’re working on building out the content as quickly as possible. Any comment you can leave us on the wiki or the support forums about anything you need help with will be first priority for inclusion.

For all Wildbooks

  • Improved the * interface for adding labeled keywords to media assets that have no associated keywords yet.
  • Added bulk import support for Encounter.identificationRemarks, Encounter.informOthers, and Encounter.livingStatus.
  • Prevent double imports and provide status updates of uploads using the bulk importer.
  • For biological samples, set SexAnalysis.sex to be a dropdown input, ensuring greater consistency in sex reporting.

Lynx Wildbook updates
Updated Lynx Wildbook interface to ensure maximum data security between different organizations.

African Carnivore Wildbook updates
Added a multi-tier labeler to work with wild dog tails.

Kitizen Science updates

  • Allowed for route creation by admin.
  • Allowed for route assignment to user.
  • Support time zone recognition of reported routes.

Zebra Wildbook updates
Added measurement and labeled keywords for historical data import.

DragonSearch updates
Updated the home page leaderboards for more relevant and impressive statistics.

Bug fixes
WB-560: phantom encounters no longer display in the matching results.
WB-544: annotation bounding boxes are correctly placed over the animal.
WB-536: detections move automatically to ID.
WB-522: top level navigation works from visual matcher page.
WB-488: spot mapping no longer in conflict with latest Chrome and Firefox browser updates.
WB-475: no longer generating duplicate detections in IoT.
WB-279: all encounters can now be deleted.

Coming Soon
We’re currently alpha-testing a manual annotation tool, which allows researchers to create their own annotations when detection misses an animal. This will be available to the community at large as soon as testing finishes!