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Novelty Network

Open Access, decentralized journal with In-built reputation system

Created on 4th August 2019

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Novelty Network

Open Access, decentralized journal with In-built reputation system

The problem Novelty Network solves

With the current state of academic journals globally publishing a research paper is heavily centralized
with only three major academics journal publishers (Elsevier, Springer, Wiley)
having a monopoly on deciding and publishing papers in their periodic journals
with over 72% scientific publications locked up behind a paywall.
We aim to provide a different incentive model for academicians
that rewards them by both building up their reputation as well as getting capital investments.

With Novelty Network we attempt to provide a decentralized publishing platform
with open access. Enabling peer aggregated reputation of papers and authors through
weight based votes represented by an ERC721 token.
Even though we use NFT's they are still tradeble and can be bought off someone
therefore still somewhat fungible. We offset that by increasing the weightage of
a vote if they are only transferred i.e voted by one paper author to another author's paper
otherwise the vote weight is reset to minimum hence incentivise users to keep
the token within the system.
The mechanism rewards both the original authors,the peer reviewers by showing there
approval by voting on a paper and also other authors who's previous work is citied
by any other new paper, creating a network effect.

Challenges we ran into

We had a few problems with minting new ERC721 tokens while keep it secure so that not just anyone could mint new tokens
and also with calling the safeTransferFrom function with figuring out the user flow of whether to get them to approve our contract to transfer the token or have them directly transfer the token and then update our state based on that, we ended up chosing the former. We overcomed these bugs good old debuggin with console.log's and trial & error as well as going back and reading the concepts and documentation to figure out what were we're going wrong or what assumption we're making

Discussion

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