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Verity Ledger : a protocol for improving data quality and ensuring data authenticity in publicly-built open datasets

Author(s)
Macias, Israel R.
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Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Miho Mazeereuw.
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MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
In recent years, there has been a heightened interest in the sharing economy for open data. One example is the Open Street Map (OSM) where people contribute to open repositories of street data for the public to use. These datasets are rich as a result of being constructed from data that the public created, rather than static information such as fact data. OSM is a system that relies on public contributions to continue to build and update its map, but therein lies a few critical problems. For one, there is no real incentive for the public to contribute aside from good will. This limits the size that the data set can grow to and its usefulness. Second, for these datasets (and even publicly available data in general), anyone who uses the data must trust the entity that provides it. This introduces an authenticity problem. There is no guarantee that the data owner is trustworthy. Lastly, because of the reliance on truthful contributors, there is no guarantee that the data is of good quality, posing an issue for those using the data. The Verity Ledger is a decentralized solution to these problems and is built as a ledger of database transactions with validators and contributors participating in data exchange. Based on an Open Representative Voting (ORV) protocol for consensus, Verity is constructed with each of the aforementioned public dataset issues in mind, using the ORV protocol to solve each of them. This thesis presents the overall architecture of the system and how they are integrated together to function in a decentralized manner.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020
 
Cataloged from the official PDF of thesis.
 
Includes bibliographical references (pages 53-54).
 
Date issued
2020
URI
https://hdl.handle.net/1721.1/127472
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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