Introducing Distributed Data Vending, A Compliant Way to Share Sensitive Data

  • The advent of blockchain infrastructures paves the way for a new domain of data vending, allowing individual data owners to directly benefit from sharing proprietary data that is both compliant with regulators and immutable. In the era of big data, vast amounts of data have been used to improve decision making for industries, namely through building personalized recommender systems, and targeted advertisements. As a result, organizations that collect and aggregate data at scale stand to profit enormously in the process. However, as data stakeholders, the users from whom the data is collected from rarely get their share of dividends despite significant contributions to the fortune. In fact, in most cases, organizations regard collected data as their private assets and prevent the data from being shared even for research purposes, which could otherwise contribute to the advancement of our society.

    In combination with Dr. Jiayu Zhou and Fengyi Tang as leads of Michigan State University and Dr. He Zhu and Ning Nan (Founder) of BitOcean, the Chief Scientist of VeChain, Dr. Ziheng Zhou, has published a Distributed Data Vending on a Blockchain whitepaper proposing a solution for allowing proprietary data to be securely exchanged via a blockchain. This whitepaper was offered as a continuation of the VeResearch program which Michigan State joined on January 31st, 2018.

    This VeChain exclusive system is already being developed in-house and by enterprises for upcoming dApps and coin issuances.

    Data vending is the exchange of private data between individual data providers (owners) and data consumers via a protected system that uniquely adapts to uses cases. The purpose of distributed data vending is to enable data providers to use existing blockchains as infrastructure to list the data securely and apply to regulations and compliance needs. Data consumers then retrieve data from the blockchain and complete the purchase. The entire data exchange process is done without trusted third parties involved.

    Illustration of the proposed distributed data vending (DDV) framework. DDV enables private data to be exchanged through smart contracts

    In this paper, the team demonstrates a framework for distributed data vending through a combination of data embedding and similarity learning. The paper illustrates the structure through a practical scenario of distributing and aggregating electronic medical records on the blockchain. Extensive empirical results are shown to demonstrate the effectiveness of the framework.

    Illustration of work flow for the proposed distributed data vending (DDV)

    Electronic health records (EHR) systems are now deployed in most hospitals across the United States. In recent years, medical histories in EHR have been used to build data-driven models to improve healthcare resource management. Analyses of the EHR data often reveal valuable insights into the underlying pathophysiology of numerous complicated diseases. These discoveries are invaluable to the development of drugs and treatments. However, the patients who own the data and contribute to research outcomes are rarely rewarded for their contributions, despite the hiking up of healthcare costs which accompany the rise of healthcare information exchange in recent years. On the other hand, many research institutions, such as universities, have a tough time accessing existing health data due to strict regulations such as HIPAA and bureaucracy, even though individuals are willing to share their medical histories, primarily when they are incentivized to do so.

    Distributed data vending can transform many domains such as healthcare by encouraging data distribution from owners and its aggregation. The use of distributed data vending will be a key gateway for VeChainThor adoption across multiple markets and will be one of the pioneering advancements seen by society through the technologies that blockchains enable.

    VeChain has developed an extensive applicational toolkit for developing solutions such as DDV and EdgeChain to power the advancements made by VeResearch and third parties. The real collaboration of businesses, data, and research enables applications such as VeVID and DDV to revolutionize the way that the world shares and advances.

    We are excited to demonstrate the power and authority DDV and VeChainThor will have in these markets in the coming months.

    To view the entire Distributed Data Vending proposition, please read it Here.

Log in to reply