The decision support for beekeepers challenge will focus on honey bees. What are the relevant relationships with environmental factors, and how can they be translated into a tool that helps beekeepers to optimise choosing hives locations? This also may be relevant for agriculture, and crop growers who depend on pollinators.
If the suitability is low, the question becomes what can be done about it. For example: different mowing strategies by municipalities, tree planting strategies to optimise gestation throughout the season, temporarily moving hives or, if necessary, supplying temporarily provide additional feeding options to bridge critical periods.
We also want to look at the question of whether honeybee population dynamics could imply things on the quality of the local environment. This is also important for wild bee species.
Besides environmental factors, interesting dimensions to take into account are:
- time factor: bees need feed from spring to autumn. What is the availability of feed throughout the season?
- the weather: depending on the weather, plants and trees bloom or not (eg too dry as the heather in The Netherlands this year), sooner or later (trends show that spring starts earlier every year in the Netherlands), etc.
A valuable result of the hackathon might be that a beekeeper would be able to click on a location, and then sees a certain score for suitability. For example:
- a low score, with explanatory parameters such as low plant gestation in autumn. The user then knows for a healthy honey bee population that he either needs to improving gestation in the fall, move hives or add other feeding options.
- a high score, with an underlying explanation. Maybe even an indication of how many hives the region can hold.
It would also be really cool if the user can also add relevant insights and experiences in a particular location, give feedback on the score, help detail the vegetation, or even allow access to data on how much honey he yielded and the number of colonies he/she keeps. This type of data help to validate and further improve the decision support model.