Last week at Slush 2022 – the world's leading startup event, we witnessed innovations for the future linked to ecosystems, data economy, Web 3.0 and Metaverse. The common thread across the event was about our journey towards a data-driven future by extracting maximum value from data. But to tap the potential of data, industries must first address the challenges limiting its secure exchange.

Secure data exchange is imperative

The challenges include data security and privacy concerns, siloed data, regulatory requirements, data monetization complexity and missing collaboration in an ecosystem. These are limiting the digital transformation journeys of all the industry verticals, including telecom, smart cities, logistics, energy and healthcare. To tackle this, a secure data exchange is imperative which can enable data democratization and drive the data value chain. A blockchain-based marketplace can provide a platform to securely exchange data and drive the development of B2B2X ecosystems. This can further unlock innovative use cases for monetizing data and transforming industry verticals.

The possibilities are enormous. With some diverse examples, we can see how different industries can extract value differently from the blockchain data marketplace.

IoT data monetization

Communication service providers (CSPs), tower companies and neutral hosts are gathering loads of data from the sensors or assets on the towers. This includes both weather and non-weather data, useful for sectors including agriculture, emergency services, insurance, smart cities, marine operations, road route management, airport security and delay management. Catering to these sectors, a blockchain-based marketplace can catalyze the exchange of data for monetization by providing a secure collaboration platform through which diverse types of data from multiple systems and IoT-enabled infrastructure – like pollution and environmental data and video feeds from camera systems – can be exchanged.

These CSPs, tower companies and neutral hosts can harness environmental data and sell forecasting intelligence to customers. They can also facilitate research by bringing together several companies and organizations including cities, government authorities, market research companies and universities to collaborate and conduct techno-economical live research on environmental data.  

Secure data exchange for ecosystem collaboration

In the logistics sector, companies are looking for a solution to enable trusted secure data exchange between supply chain participants. The traditional process is complex with multiple steps and involves many different parties. Moreover, each of the participants has its own ‘system silos’ and the lack of interoperability means there is no way of having a unified real-time view of end-to-end supply chain operations, introducing significant delay and associated cost in the process. This calls for a mechanism to facilitate trusted traceable data exchange among supply chain participants.

Through open APIs, participants can publish data directly from their systems onto the blockchain data marketplace based on permissioned access. The participants can benefit from improved supply chain transparency. Transactions can be validated and automatically settled through smart contracts increasing operational efficiency. The result could be reduced cost across supply chain operations while also enabling faster turnaround for shipping cargo load/unload operations.

Federated AI/ML orchestration on bigger or immovable data sets

COVID-19 highlighted the need for information sharing at speed and scale as governments and health officials scrambled to gain a global picture of the unfolding pandemic. A big question was how to make data accessible and usable without compromising privacy, security or data sovereignty laws. In the healthcare sector, there are situations where whole institutions, jurisdictions or even nations have vast pools of data that could be of value to others but can’t be shared for legal or regulatory reasons.

That calls for a completely different approach: federated AI and machine learning techniques that allow the analytics to “reach in” to the data set, work with it in situ and extract just the outcomes of the analysis for other parties to then work with. This can be readily achieved with the use of open application programming interfaces (APIs). When it comes to medical research, the bigger and more diverse the data set, the better. Patterns can be spotted sooner, effective approaches isolated quickly and critical outcomes shared rapidly. The result could be faster development of new public health measures that save lives.

Nokia Data Marketplace for the data-driven future

Understanding the wide variety of information needs, we at Nokia have developed a single platform that can support vertical ecosystems, auditable transactions and federated AI/machine learning with open APIs: the Nokia Data Marketplace. It supports secure data exchanges and business transactions and uses AI models trained across distributed data sets to enable truly data-driven digital transformation in a whole range of sectors and industries.

As industries need faster access to desired data to respond faster and more effectively in a competitive landscape, the Nokia Data Marketplace powered by blockchain can drive the development of diverse ecosystems and fuel the data economy.