About the dataset
About the dataset:
We have made the following datasets available to you:
Catch Notes Data: The data contains catch notes collected by the Norwegian Fishing Directorate from 2000 to today for vessels larger than 15 meters. The notes consist of information about the catch that is manually logged during landing, e.g., when it was caught, where it was caught, what equipment was used, the species distribution of the catch etc. There are approximately 130~data fields and around one million notes each year
Monthly averages of salinity data from 2015 to present day is provided from the SMAP Salinity V4 dataset. Salinity (in combination with temperature) affects the growth rate of microalgae. This can potentially affect the migration patterns of fish. Eight-day running averages are also possible to obtain if needed (https://salinity.oceansciences.org/data-smap-v4.htm).
Moon Phase Data:
The moon phase data consists of dates and exact times of full moon from 1900 to 2050. Lunar phases affect the migration and behaviour of fish due to water levels changing. Therefore, it is potentially possible to use this data source for modelling of the movement of fish. The dataset is published at https://www.kaggle.com/datasets/lsind18/full-moon-calendar-1900-2050.
Sea surface temperature (SST) from 1981 to present has been collected by National Oceanic and Atmospheric Administration (US). It contains daily estimates of SST globally. The data was collected from satellite observations, and consists of daily data at 0.25 degree latitude x 0.25 degree longitude resolution. We have included the subset of data from 2000 to present day. The dataset is published at:https://www.psl.noaa.gov/data/gridded/data.noaa.oisst.v2.highres.html.
All datasets can be found and downloaded here: https://tinyurl.com/54w5bvxa
If you have any questions, please email Birte Hansen (email@example.com)
We invite you to submit your answer to the following tasks:
Task 1: Build a model that can predict which coordinates a vessel should prioritize in order to maximize the likelihood of catching a type of fish of your choosing (haddock or mackerel is most valuable for our industry partners). The prediction can be based on historical data.
Task 2: Create a report of your analysis that can be read by experienced fishermen; an user-friendly visualization that a captain can read to make a assessment of where the vessel should search for fish the next day
Task 3: Make a Sustainable Fishing Plan; a weekly plan that suggests the routes the fisherman should follow to optimize fish caught and fuel consumption
To compete for the prize awards all tasks are mandatory. Submission of only one sub-task is allowed, but will not be eligible for winning any of the prizes.