Powerful conservation tech tools are gathering more data in the field than ever before. But without equally powerful and effective data management and processing tools, that data - no matter how groundbreaking or interesting - will not be able to reach its full potential for impact.
Data management can sometimes seem intimidating to conservationists, especially those just getting started in the world of conservation tech or experimenting with new data collection methods. While every community member's workflow and preferred data management and processing methods may be different, this group can serve as a resource to explore what works for others, share your own advice, and develop new strategies together.
Below are a few WILDLABS events dealing with datasets collected from various conservation tech tools:
Nicole Flores: How do I get started with Wildlife Insights?
Jamie Macaulay: How do I analyse large acoustic datasets using PAMGuard?
Sarah Davidson: Tools for Bio-logging Data in Conservation
Whatever conservation tech tools you work with, and whatever your preferred data management methods, we hope you'll find something helpful and effective in this group when you become a member!
In this thought piece from Whale Seeker, Malcolm Kennedy considers the strengths of weaknesses of citizen science and AI, both used to analyze large amounts of conservation data, and discusses the importance of data...
19 August 2021
Internet of Elephants is excited to introduce a free data visualisation tool to help researchers and conservation storytellers show animal movement data easily and effectively! Read about the new tool below, and try it...
18 August 2021
Article
Wildlife Insights is excited to announce the public release of their new platform! Read on to learn about all the useful features you'll find on Wildlife Insights, and check out WILDLABS' Tech Tutors episode with...
27 July 2021
Read our interview with early career conservationist and CLP Future Conservationist Award recipient Owino Raymond, who is working with camera traps along the Kenya-Somalia border to understand and reduce conflict...
21 May 2021
A new issue of Methods in Ecology and Evolution from the British Ecological Society is now available for download. In this issue, WILDLABS readers will enjoy research involving conservation dogs and non-invasive...
23 April 2021
National Geographic is offering funding up to up to $50,000 for conservationists conducting research on how the pandemic has impacted wildlife and conservation work. If you are interested in researching aspects of the...
10 March 2021
Article
WildID is excited to share their new camera trap processing and detection tools with WILDLABS! Using machine learning to identify Southern African wildlife species in large quantities of camera trap data, WildID's tool...
8 March 2021
Sol Milne's new paper, Drivers of Bornean Orangutan Distribution across a Multiple-Use Tropical Landscape, is now available. Using drones to detect orangutan nest density in aerial surveys (as shared during our...
12 February 2021
How can remotely monitoring fishing vessels allow us to prevent illegal and unsustainable fishing practices? Check out this blog post from Max Schofield, originally shared on OceanMind, to learn about how AIS (Automated...
2 February 2021
The 2021 Ebbe Nielsen Challenge has opened with the aim of recognizing innovative entries that leverage biodiversity data and tools from the GBIF network to advance open science.
20 January 2021
The Nature Conservancy's 2020 Geospatial Conservation Annual Report is now available to download! Featuring 25 case studies focused on the impact of geospatial science on conservation work, maps showcasing conservation...
17 December 2020
WILDLABS community members are invited to submit an Expression of Interest to Fisheries Innovation Scotland (FIS) to participate in two research projects involving conservation tech's role in the future of sustainable...
8 December 2020
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5 February 2021 7:16pm
Dan's comments about the need for technologists and conservationists to manage and share (properly annotated) data struck a chord with me, it was right at the end of the presentation.
I fired off a point into the chat "could your old background data be my background data?" or something similar, and it got me thinking...
(Firstly, sorry for clouding this issue with my simultaneous "Ian Tuna" joke)
In the context of using AI as described in EdgeImpulse example, lets say - audio.
Lets say Group A are trying to detect the roar of lions, and Group B are trying to detect the grunt of wild pigs, and lets imagine that is in roughly the same area of Africa. I mean they could both send out teams to capture the sound of their target animal, and the sound of NOT their target animal, e.g everything else.
Well if "serengetti sounds" was a known audio track, then all you need is the unique sound of the beast in question, am I right?