Noggin is a personal knowledge management layer which allows to map knowledge to data, then use it with purpose.
We foresee a future in which users wield computing power to manage and optimize their skills and knowledge. Through Noggin, a user can focus in what he values most, avoid stagnation, and have better situational awareness.
Noggin also provides (voluntarily user-provided) a grand cache of data for organizations and companies to access: they can hire the optimal employees applying strategies in the candidate’s dataset, for example.
It is a way for machines to visit a layer unbeknownst to them, the knowledge layer, and integrate it inside the dense, worldwide data network.
A Noggin track is composed of nodes and unions.
Nodes can be interpreted as concepts, skills to acquire, or knowledge to be learned.
They relate nodes: grouping them, make one depend on the other, link them through a common characteristic.
Nodes and unions both can have data associated with them (metadata), declaring what they are and how they compare with the rest.
The node-union system is quite flexible. Depending on the metadata associated with a node, it can be declared as higher-difficulty in comparison with another one. Or it can be a concept, instead of a skill.
We want to implement a program to easily create and modify Noggin tracks. It will be the starting point for the whole ecosystem, and it will help refine the standard of the Noggin model, for it to be simple and easy to extend.
Everything you know is a lot. It is important for applications which handle knowledge to be clever: don’t force to add one node after another, painstakingly. Let there be shortcuts.
The Noggin editor and the rest of track interactions must therefore be easy, useful, agile. Furthermore, APIs and a community can make this epic goal feasible, automating parts of track creation and making it possible to share knowledge tracks.
This introduction is a very limited view of what Noggin may achieve. Think of how a system like this can be improved upon, what uses it could have that nobody thought of. Tell us your ideas!