Researchers attach GPS loggers on birds' body for collecting trajectories of birds to understand how they navigate themselves, even across a big ocean.
What is the cue and how they use it ? If male and female birds could use different cues, they must have different trajectories.
Can we find the difference of male/female trajectories and discover a new science knowledge ?
This is the task of this competition.
Fieldwork was performed on the population of streaked shearwaters breeding on Awashima Island (38°28′N, 139°14′E), Japan, in a colony that contains approximately 84000 shearwaters.
Parents of this species, Streaked shearwaters (Calonectris leucomelas), attend their nests and feed chicks during the breeding season. The shearwaters feed on fish such as Japanese anchovy in areas up to 1000 km from the breeding colony.
Data loggers (Technosmart Europe) are attached to the leg. Note that the procedures used in the field study for collecting the data were approved by the Animal Experimental Committee of Nagoya University.
Some days after releasing birds, the same birds should be found around the next so that the loggers are retrieved and the data are collected. Note that the trajectories used in this competition have been preprocessed by data cleaning for rejecting incorrect GPS data.
Blue trajelctory is male, red one is female.
Grant-in-Aid for Scientific Research on Innovative Areas from 2016 to 2021
Navigation is a fundamental behavior of animals including human. In navigation, the following three functions are required: the acquisition of dynamically-changing information from external and internal environment, the choice of route and destination based on the information, and the behavioral regulation to reach the destination. We aim for systems science of bio-navigation to understand the “algorithms” for the navigation of animals. To this end, we bring together experts from control engineering, data science, animal ecology, and neuroscience, and jointly work on how to measure, analyze, understand, and verify bio-navigation.
By hosting competitions "Animal Behavior Challenge (ABC)", we hope to boost our understanding the algorithms for animal navigation.
Please visit our website.
This challenge is sponsored by Technosmart (see Prize page). All trajectory data used in this challenge were obtained by GPS loggers of Technosmart.
You may submit 5 submissions every day and 50 in total in the development phase.
Submitted results are evaluated by the accuracy, widely used for binary classification problems.
It is 0 if all predictions are wrong, while 1 if perfect.
There are 275 test trajectory, and classification results should be a 275-line text file, which contains 0 (male) or 1 (female) for each of test trajectory.
Each line has the label of the corresponding test trajectory; that is, line 0 is the label of the test trajectory 000.csv.
Predicted label is binary (character):
Here is an example:
The dataset is available HERE. (the test labels are included as the competition was over)
Classifying GPS trajectories of birds into male or female
A single CSV file (000.csv, 001.csv, ...) contains a trajectory of a trip,
and each line represents the information of a GPS location of a shearwater.
In addition to longitude and latitude, some other information is provided;
elapsed time and local clock time, solar azimuth and elevation angles.
Float values are of the format %.5f, and fields are separated by a single comma.
Here is an example:
A single txt file of ground truth labels of the training set is provided.
Each line has the label of the corresponding training trajectory; that is, line 0 is the label of the training trajectory file 000.csv.
Label is binary (character):
Here is an example:
Thanks to Tehcnosmart, the sponosor of this challenge, winners will recieve the following prizes;
Note that, to recieve the prizes, winners must publish their methods and/or codes available online (for example, as a technical report on arXiv and github) upon request by the organizer.
In addition, the first winner will recieve
This challenge is governed by the general ChaLearn contest rules.
Start: March 1, 2018, midnight
Description: Develop your models and submit prediction results. Scores are shown with randomness (10% of your submission labels are randomly modified for avoiding cheat).
Start: Aug. 1, 2018, midnight
Description: Final phase (no submission, your submissions from the previous phase are forwarded. No randomness is used for evaluation).
Aug. 1, 2018, 11:59 p.m.
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