Hosting a data challenge is a fun way to crowdsource the wisdom of data scientists and machine learning experts around the world. Incentivize participants to build products on top of your data, explain insights, or provide useful models for your business. Plus, it's a whole lot cheaper than hiring an in-house data science team!
1. Establish the business problem you want to solve. The first step in building a data solution is understanding what you want to solve. For example, you may want to be able to predict the drought risk in an area to help price parametric insurance, or predict the price of ETH to optimize Uniswap LPing. 
2. Curate the dataset(s) that participants will use for the challenge. The key to hosting a good data challenge is to provide an exciting and through dataset that participants can use to build their solutions. Do your research to understand what data is available, whether it be free from an API, available for download, require any transformations, etc. For the first challenge, it is alright if the created dataset is a static file. However, it is best to ensure there is a path to making the data available from a dynamic endpoint so that entires can eventually be applied to current, real-world use cases.
3. Decide how the judging process will occur. This includes how long to make review period, how to score submissions, and how to decide any prizes will be divided among participants
4. Work with Ocean Protocol to gather participants for your data challenge. Creating blog posts and hosting Twitter Spaces is a good way to spread the word about your data challenge.
