Decentralized publishing as a cascade of information filters modeled by TCRs

[himalayajung]

WIP

Decentralized publishing as a cascade of information filters modeled by TCRs

Decentralized publishing as a giant information filter
Research is an analytical process to produce information from data. And publishing is the process of managing this research-produced information for its efficient propagation or dissemination. In other words, we can model decentralized publishing as a giant information filter as shown in the figure below.

During publishing, following key actions are taken on research results (i.e. information) to make them more useful:

• formatting: makes it easy to consume
• quality control: provides a proxy way to gauge the quality of a publication. For example, researchers generally view publications in journals with higher index factors as more trustworthy
• segregation: makes it easy to query. For example, brain imaging research results go to NeuroImage while advances in genetics go to Nature Genetics

The key characteristics of an information filter are:

• provides some value to the consumers
• right incentive structure among the filter creators/maintainers (information curators) and consumers (information producers and consumers) to justify its value creation for its sustainability

Decentralized publishing as a cascade of smaller information filters
When we look closer, the giant information filter in the figure above is a cascade of smaller information filters. Although these information filters share common theme i.e. to filter information, they have different use cases e.g. a list of best posters in CRISPR, a list of groundbreaking ideas in AI, a publishing channel (journal) for applied research results in medical imaging.

For example, the decentralized publishing (Idea-Hub) based on Proof-of-Idea https://github.com/open-science-org/wiki/blob/master/Proof_of_Idea.pdf is basically a cascade of information filters (see Layer 0 to Layer 4 in the figure below).

Modeling an information filter as a TCR
The end product of any information filter is a curated list which has some value to the consumers and the curators have some incentives for curation. This is very similar to token curated registries (TCR).
https://medium.com/@ilovebagels/token-curated-registries-1-0-61a232f8dac7. To quote Mike Gouldin, "Token-curated registries are decentrally-curated lists with intrinsic economic incentives for token holders to curate the list’s contents judiciously". This similarity makes a reasonable case to model information filters as TCRs. With this design, decentralized publishing will be a cascade of TCRs where each TCR will have its unique properties suited for its specific use.

Publishing Channel
A group of researchers can spun out a brand new TCR if they want to start a publishing channel.