Alloha: A Data Science Web Framework for Tunable QF
{"type": "project", "title": "Alloha: A Data Science Web Framework for Tunable QF", "logoImg": "bafkreih2zo5gbxrbjqk2wgaptlxuusdgw4rirjq2zkbk7w4iaxq2x65utm", "website": "https://github.com/CommonsBuild/alloha/tree/ygg", "bannerImg": "bafkreifqstsac5r364l73vflxmovan67t7v63uut6wce6utmdrmlt6jmzq", "createdAt": 1695078924474, "userGithub": "linuxiscool", "credentials": {}, "description": "Alloha is an open source web based data science framework for designing, exploring, and evaluating public goods funding mechanisms. The work draws inspiration from the paper \"A flexible design for funding public goods\" and is a software implementation of the concepts discussed in that paper. The work is driven by data visualization, creating interactive plots for each data structure in the fdfpg framework.\n\nAdditionally, the project implements the concept of 'Tunable QF' in which the weights of donations can be boosted according to token holdings of donors or other qualifying credentials. The TEC is using this technique to boost the weight of TE subject matter experts. But the tool can be used generally for processing of donation datasets.\n\nThe development of this application is being partially funded by the Token Engineering Commons.\n\nThe author is seeking supplementary funding to be able to continue the work and develop the framework into an open source web application.", "logoImgData": {}, "bannerImgData": {}, "projectGithub": "commonsbuild", "projectTwitter": "tecmns"}