SourceCred

SourceCred makes the labor of individuals more visible and rewardable as they work together in a project or community. Taking inspiration from Google’s PageRank algorithm, SourceCred uses both objective and subjective measures to accurately capture and update an individual contributor’s impact on a project.

In traditional organizations, contributors to a project are at the mercy of their manager or boss to determine their value. This system of value determination occurs at set intervals and isn’t flexible or transparent.  When contributors add more value than anticipated, all of the extra value accrues to their manager. In DAO structures, it can be challenging to keep track of the contributions of all members and to agree on the relative value of different contributions. This only becomes more difficult as a DAO scales. 

SourceCred attempts to solve this problem via a compensation algorithm that relies on both subjective and objective measurements. Coordinape and SourceCred are similar tools, but Coordinape relies solely on subjective measurements.

SourceCred maps all participants and contributions in a graph, illustrating how contributions and participants in a project are connected to each other. Each contribution a participant makes is represented as a separate “node” in this graph. 

This data is used to create a Cred Score for each node using a modified PageRank algorithm.  The DAO decides which contributions will "mint" Cred, making them a source of new Cred.

Participants earn Cred by contributing to a project. A participant's Cred score reflects how valuable their contributions were.  As an example, consider a Discourse forum post. The post is itself a contribution, and it generates Cred for its author, but it also generates Cred for any post to which it replies and/or for any posts or users that it references.

A key tenet for SourceCred is to let communities decide what they value. This is done through “weights” and these are established when setting up SourceCred.  There are two kinds of weights:  

• Node weights: Determine how much Cred is minted at a given node. For example, if you want every “like” of a post in a forum to mint some Cred, you could set a positive node weight on the likes given to forum posts.
• Edge weights: Determine how Cred flows once it is in the graph. Suppose we have a Discourse post with exactly two edges: one edge to the author of the post and one edge to a person mentioned by the post. Should the author or the person that mentioned it receive more Cred? If you think they should both get equal Cred, you could leave both edges with a default weight of 1×. However, if you think that the author should get twice as much Cred, you could assign the authorship edge a weight of 2×, or give the reference edge a weight of 0.5×.

Participants are rewarded with digital currency, called Grain, based on their Cred score.  Grain is redeemable for USDC, a stable coin worth $1.