These 5 blockchain startups are taming the data jungle

A list of the most promising blockchain projects that aim to revolutionise the way we create, access and use data in an increasingly data-driven economy

In today’s economy, data is more valuable and at the same time more plentiful than ever. Every day, 2.5 quintillion bytes of data are generated, and with the growth of the Internet of Things (IoT), this number will continue to grow. So far, very little of this data is used to its full potential. There are many reasons for this, such as:

  • The majority of data is kept in isolated silos with incompatible data structures.
  • A lot of data is unrefined or inaccurate, while refining and verification processes are inefficient and expensive.
  • Sensitive personal data can often not be used due to privacy concerns.

A recent McKinsey study revealed that better access to data could help unlock $3 to $5 trillion in global economic value. Our own project, DIA, will play a crucial role in this process by making reliable, open-source financial and digital asset data available to everybody. Nevertheless, we need to bear in mind that there is plenty of other data that needs to be democratised to build a future economy that is more fair and transparent across all sectors.

Fortunately, there are other exciting startups that are helping us to do just this. From healthcare to data analytics — what follows is a list of the most inspiring projects that aim to revolutionise the world of data through blockchain:

DATAEUM

Dataeum is an Estonian startup that is building a crowdsourcing platform on blockchain to collect global physical data. Much like DIA, Dataeum aims to incentivise a community of data collectors with platform-native tokens to add data to the platform or to verify existing data. The data collection process is realised through a smartphone app, which allows collectors to add accurate visual data about anything in the physical world such as stores, petrol stations and traffic signs. Data contributors are paid with the platform’s XDT tokens, which are also employed for purchasing data on Dataeum’s decentralised marketplace.

The mobile app that facilitates the data collection process has already been up and running for two years and has been tested in cities such as London, Paris and Barcelona. The application employs image recognition technology, AI (Artificial Intelligence) as well as AR (Augmented Reality) features, which allow the automatic and intuitive recognition of any visually accessible data such as benches, vending machines and taxi stands.

DIRT

Just like DIA and Dataeum, DIRT combines crowdsourcing with blockchain technology. The Californian startup is creating a transparent, open-source protocol to validate decentralised information. The key element of the DIRT protocol is a staking mechanism, which works in a similar way as the one employed on the DIA platform. Every contributor needs to stake tokens when suggesting new data. If the data is correct, it is shared openly on a decentralised platform and the contributor is rewarded with platform-native tokens. The data might not be accepted by the community however, as other people can challenge the accuracy of submitted information by staking tokens. In such cases, whoever supplies the correct information is rewarded with the stake in question, while disputes will be resolved by the community through a stake voting process.

Through the described mechanics, the DIRT protocol will enable the creation of so-called token curated registries (TCRs), which ensure the accuracy of gathered information by making the persistence of inaccurate data in the network economically irrational.

DATAVLT

DATAVLT is a Singaporean startup that integrates blockchain technology with data analytics. The company aims to make data analytics affordable to any business by creating a platform that employs a structured, open-source approach to aggregating, correlating and managing information. In contrast to DIA, DATAVLT does not employ crowdsourcing to gather data but aims to improve the analysis process of existing data sets. Nevertheless, they address a similar problem: Just like financial data is often only accessible to large banks and investors, proper data analytics is not affordable to many smaller companies.

It is the goal of DATAVLT to make complex data analytics more accessible to a broad range of businesses. To achieve this, they employ blockchain technology, AI and machine learning, which make it possible to secure, track and validate data and at the same time cut costs and processes. This cost efficiency allows them to provide affordable data analytics services to businesses of any size, especially SMEs.

MEDIBLOC

Data in healthcare has huge potential but privacy concerns and data silos have so far made it difficult to effectively use patient data for research purposes. There are numerous startups that aim to solve this problem through the use of blockchain technology. One of the most promising ones is Medibloc. The South Korean company plans to create an open-source healthcare data platform built on blockchain, which compiles a complete history of all patient medical information.

Although their business model is very different from DIA’s, the two share a common goal: the democratisation and improvement of data. With Medibloc, patients remain in full control over their data and assign access permissions to medical institutions for research and other purposes. At the same time, the startup addresses the problem of data silos by integrating data from various institutions, which will harness the full potential of patient medical records for research purposes.

DIA

DIA (Decentralised Information Asset) is an open-source, crowd-driven financial information platform powered by blockchain that will enable the supply, sharing and use of digital asset and other financial data. DIA aims to democratise financial data by providing an equal level of information to everybody in the financial space.

Data seekers looking for a particular set of data on the platform can submit a request ticket that is linked to a bounty. Developers can then build scrapers to access the requested data and upload the corresponding code on Github. If the underlying methodology of the code is accurate and accepted by the community, the bounty is paid to the developer in DIA tokens. If it is suspected to be wrong, data analysts can challenge the submitted code through a staking process and earn the bounty linked to the ticket. Once the code is accepted by the community, it will be made available on the DIA platform, which allows dApps and other stakeholders to access historic financial data free of charge, while the access to live data streams and specific APIs can be purchased with DIA tokens. For more detailed information on the DIA platform have a look at our introductory article.

Check out Coinhub, our first DApp with decentrally sourced and maintained crypto data.


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