[DOCS] HELP WANTED revise, modify, and update data science roadmap

[ngiangre]

⚠️ IMPORTANT: Please fill out this template to give us as much information as possible to consider/implement this update.

Summary

We should start enabling interaction with user data. This calls for designing a data science roadmap, creating issues for tasks along the roadmap, and storing code and implementations in the repository for iteration and building functionality. I can't provide a perfect suggestion on how to do this, so we should collaborate on work on and figure this out together!

Motivation

We should start enabling interaction with user data. But how? When a user uses the app, their data is communicated to their GAIA database. See here for more of an overview as well as the blockstack documentation on GAIA. We need to understand how data is stored in their GAIA database, and how we as developers can query their GAIA database. Below is a screenshot from this slide that is the current understanding, steps, and potential tasks/issues to tackle and dissect.

In order to best understand and implement anything, we need to create a test user account and use that to test.

REQUEST 1: Make an issue to create a test blockstack account and post it's credentials.

We would need this so that we as developers can practice connecting to a user's GAIA database as a user. We can use the Blockstack CLI in order to try this out from a user's perspective of connecting to a peresonal GAIA database.

We would also need to practice querying a user's GAIA database as a developer (aka no knowledge of the secret key/credentials). Can this be done? Why not? What needs to be enabled in order to build this functionality? These are all relevant questions that we don't have answers to yet. For this, I think a great starting point will be the Blockstack tutorials on Radiks.

It may take some time to be able to get any type of data into our own Radiks implementation, but once we do then we can think of how to transfer this to our MongoDB.

There's a lot of steps to take, so let's take them one step at a time!

Possible Alternatives

Sitting on our hands...

Additional Context

Regarding the mock data. I think it's great we start start from the 99th percentile of the pipeline and do a learning task. This is the realm most data scientists are familiar with, including myself. However, we need to address the 0->99 percentiles of the pipeline. In order to get to having actual formatted data, we need to get it into our MongoDB. In order to get data into our MongoDB, we need to fetch data from our Radiks implementation. In order to get data from our Radiks implementation, we need to implement it and fetch data from user's GAIA databases. In order to fetch data from user's GAIA databases, we need to construct data models for our fishing (i.e. data query) expeditions as well as figure out if and how that is possible. In order to do that, we need to understand and dissect the interaction with GAIA databases both from the user's and developer's standpoint. There's a lot of steps between these steps and I can't say up front what the actionables and tasks are, but together we can collaborate and figure this out together!