Idea: Wikipedia like graph db for curated content 1) An API framework with an ORM of sorts around the existing graph dbs ( it could be Gremlin based ). This w

Idea: Wikipedia like graph db for curated content 1) An API framework with an ORM of sorts around the existing graph dbs ( it could be Gremlin based ). This would allow queries on levels of nodes ( tutorials -> { python | ruby } -> { django | flask } , etc. Another dimension would be { beginner | intermediate | hard }. An important search dimension might be the popularity of the curator (submitter), the upvoters and downvoters, etc. The API would allow RESTful retrieval of nodes, and based on permissions granted to the user allow operations such as voting, modification, creation and deletion. Wikipedia like data could be public domain, but the API itself could be self-hosted on private servers allowing for enterprises to have their own internal wiki of sorts. Licensing should allow extension of the API if needed for premium revenue models that might allow users to create 'n' relationships on a server that is a kind of bookmarks, can keep private graphs, clones/forks of existing graphs/sub-graphs with annotations, etc. Or contributors may contribute code to extend features on the open source platform as well. 2) A web/mobile UI that would leverage this API and create the UX around searching, for example, a) cross-indexing wikipedia and storing as graphs and allow different search algorithms to be built. b) a knowledge graph of maths ( similar to the ones at khan academy ) and linking in the URLs / videos based on dimensions such as target age, content length, language, pre-requisites, etc.