name: Decentralized Identifiers to Enable Trusted Machine Economy
about: Data Marketplace, Trusted Machine Economy
title: Decentralized Identifiers to Enable Trusted Machine Economy
labels: ''
assignees: 'N/A'
Transacting IoT data must be different in many respects in order to build much-needed trust in IoT-enabled Data Marketplaces, trust that will be key to their sustainability. Data generated internally to an organization is usually not enough to remain competitive, improve customer experience, and optimize strategic decision-making. However, there is still no transparent and reliable marketplace for data trading with fair price. Furthermore, the verification of the machines (e.g. sensors) for data collection becomes another crutial issue. As a result, an innovative type of platform with the introduction of distributed legder technology (DLT) has emerged, in order to transform data into profits with better trust basic.
According to Forbes, the data we produce per day reaches incredible 2.5 quintillion bytes and the pace would accelerate with the emerging IoT ecosystem. In the near future, more 200 billion the sensors will leave overall records of users' lives by 2020. While the amount of data is huge enough to create value, data is gradually reputed as "the oil of the digital world." The successes of Alphabet, Facebook and Amazon are futher changing our cognitions of profitable business models in current world.
Not surprisingly, data storage and marketplace turn into new challenges. However, current data storage and marketplace, featured as centralized modes, still face up substantial costs and huge risks. More urgently, the issues of security and transparency not merely remain, but further deteriorate.Therefore, it is critical to propose an innovative type of data marketplace platform with distributed legder technology (DLT) to transform data into profits with better trust basic.
Looking at IoT-enabled mobility, for example, a car equipped with LIDAR (light detection and radar), a gyroscope and an accelerometer can accurately detect bumps and potholes on the road. Those data sets could be extremely useful for municipal governments as well as companies in fields such as car insurance, navigation applications, and road maintenance. This would however rely on incentive for this data to be shared. In this example, the entities to benefit from access to the data are not in a position to collect this data on their own.
Efforts are also ongoing to predict the development of potholes even before their formation. Provided that a sufficient number of cars are equipped with adequate sensors to generate the necessary data, local authorities could improve road safety, decrease road maintenance costs, and limit the need to compensate road users for damage following insurance claims.
The demand for external data arises from continuous innovation and related value creation. IoT-enabled environments entice ‘innovation adaptation’ as projects can gradually generate additional value based on marginal improvements to existing infrastructures, provided the high scalability potential of related architectures especially if using open standards for IoT (e.g. oneM2M).
New infrastructure installations, such as smart electric vehicle charging stations that leverage data from energy markets and other sources, are good examples where cross-domain data will be crucial for commercial sustainability.
Inspired by the concept of The Streaming Data Payment Protocal (SDPP), BiiLabs proposes a new type of data marketplace platform based on MAM Channel, DID Auth and Smart Contract. Meanwhile, differing from SDPP, our implementation puts not merely the trading records but also the transaction process on the distributed ledgers. This way can efficiently enhance the degree of transparency, since all interactions with smart contracts will be writen on-chain.
In other words, users tranport the encrypted data to smart contracts for storage via MAM channel, and simultaneously make a verifiable Auth-compliant request to the platform in claim of “being tradable.” Later, the verified data will enter data marketplace to be traded. What’s more, the platform will complete matching and trading without human intervention in the whole process, and finally meet both providers’ and consumers’ expectations.
The ecosystem consists of three mechanisms: data recording, matching and data trading, which are similar to most trading platform. The tasks of the platform can be divided into two parts: seller filtering and system maintenance. The former one aims to avoid data bias by previous selection, while the later one intends to confirm the system stability with continued technical supports. Also, according to the mechanism, sellers will only receive the pay from the buyers until transactions are confirmed, or the fee will be temporally stored Ethereum Chain.