The images produced by camera traps alone are useless. We need to keep accurate records of how the data were collected, labelled, and manipulated if we are to achieve the goal of synthesizing data from multiple projects. Thus, metadata is simply “data that provides information about other data”.
The benefits of ‘standardizing’ the metadata associated with camera traps, or other sensors of biodiversity, are hopefully clear - it should facilitate the rapid and robust exploration, analysis and sharing of information on wildlife populations. Ultimately resulting in more robust, repeatable, and timely research and management decisions.
The convention we use in this course is the data standards used by Wildlife Insights.
Their standard format is composed of four different elements:
- Project data
proj.csva dataframe containing key information about the project itself, e.g. how the cameras were deployed and what the target features were.
- Image data
img.csva dataframe containing all of the information contained within each image. This information is typically added by humans, but increasing we are using artificial intelligence to speed up this process.
- Deployment data
dep.csva dataframe listing the activity of the camera traps involved in your study, and any issues encountered during deployments which may influence their analysis
- Camera data
cam.csva dataframe all the cameras deployed in the project
Below we give a quick summary and explanation of each.
First, read in the data files:
Let’s look at each one in turn.
The project files contains a general description of the project. It should give someone a helicopter overview of your project, and provide the data usage guidelines.
|Investigate medium-large bodied mammal habitat use in response to human recreation spatially and temporally
|Seismic line restoration treatements and controls
|University of British Columbia
|Beirne, Christopher, Catherine Sun, Erin R. Tattersall, Joanna M. Burgar, Jason T. Fisher, and A. Cole Burton. Multispecies modelling reveals potential for habitat restoration to re‐establish boreal vertebrate community dynamics. Journal of Applied Ecology 58, no. 12 (2021): 2821-2832.
This file contains the image labels - what is in each picture and its properties. Each image you have processed is linked to at least one row in the detection data. Multiple rows may exist if there are multiple species in a camera trap image, or if you are identifying multiple unique individuals.
This is the camera deployment data - where the deployment occurred, when it started, when it ended and other relevant information about each unique deployment.
An inventory of all the cameras used in the project. Ideally, each camera would be represented in the deployment data. This technically isn’t 100% necessary to analyse your dataset, although there are some scenarios where it might help.
These are simply the minimum sheets you require - we derive a lot of other useful data frames when moving from raw camera data to analyzable camera data. See the Creating analysis dataframes section for further examples.
Forrester, T. et al. An open standard for camera trap data. Biodivers. Data J. 4, (2016).
Meek, P. D., et al. “Recommended guiding principles for reporting on camera trapping research.” Biodiversity and conservation 23.9 (2014)