Data Providers

The blockchain ecosystem has given rise to various mechanisms through which data can be considered accurate. Traditional decentralized oracle networks [4] (DONs) have demonstrated that distributing the sourcing of information from multiple Data Providers and aggregating them into a single report or data point eliminates centralized points of failure, compromise and tampering. However, the TSN is established to leverage private, niche or entirely custom data sets that may not be available from various data sources. To enable access to this data while maintaining the ethos of decentralization, the approach is to uphold verifiability from the point of data sourcing to its utility and finalized state within the TSN. Even though private or niche data sets will always originate from a “trusted” data source, typically the data publisher, governance and network participation allow for oversight of data sources and data sets, keeping the TSN, and contributors credibly neutral. This enforces standard verification techniques among the various network participants and maintains data integrity across the TSN.

When it comes to Data Providers, TSN nodes can be classified into two distinct models: Rest API and Origin Signed models. Third-party integrators that are not publishing the dataset, but rather are leveraging an external source to acquire the data set are required to operate a node that supports facilitating the Rest API. First-party data providers, entities whose sole purpose is to publish the data for relevant industry insights, leverage the Origin Signed model which requires Data Providers to cryptographically sign the data throughout processes that extract and load it into the TSN.

Data Providers are entities that facilitate first or third-party data ingestion into their respective TSN Adapters. Essentially, using Adapters, any entity holding information and capable of communicating with others can become a Data Provider. For Data Providers with access to private data sets, privacy-preserving processes such as access authentication are to be managed off-chain, while Adapters can be configured to support any type of data verification and validation on-chain.

“Trusted Data” as a Heuristic

In agreeance with entities [5] focussed on innovating within the realm of verifiability in real-world data for use within blockchain applications, evaluating and distinguishing “trusted data” follows a process of logical assumptions based on the data source, and its lineage from the point of sourcing to verification and utility within blockchains.

The logical assumptions that are formulated to assess the trustworthiness of data provided by a service entity are predicated on the following conditions:

  1. Primary Purpose and Data Provenance: Is the entity's main function to provide data, and is the data sourced directly (first-party)? Entities fitting this criterion include government-backed APIs or private companies specializing in industry-specific data aggregation and delivery.

  2. Value Correlation: Is the entity’s data validity and accuracy directly correlated with the value of their service? This condition differentiates entities prioritizing data volume for broad insights from those offering high-quality data crucial for sensitive operations, such as those in financial markets.

  3. Capitalisation and Incentives: Is the entity sufficiently capitalized such that the financial incentive for maintaining data accuracy surpasses the temptation to falsify data? This consideration effectively excludes entities that serve as both trusted data providers and RWA issuers, where there is no mechanism to demonstrate non-collusion between these roles.

When referencing entities within these preconditions, we are specifically referring to original first-party publishers, meaning that Data Providers within the context of TSN would leverage these data sources on the basis that they sufficiently fit the criteria for being “trusted”.

Although it is unlikely that many trusted data sources will meet all preconditions, this framework facilitates human-in-the-loop decision-making regarding the risk profile of a verifiable data pipeline and its designated "trusted" data sources within the TSN. Leveraging ‘untrusted’ data sets, community-led governance plays a pivotal role in endorsing specific data sources as "trusted" providers, thereby reinforcing the integrity and reliability of the data underpinning the protocol.

Participation Fees

For Data Providers to join the network they will need to stake an arbitrary amount of TRUF tokens in the Governance Portal. In return, they will receive veTRUF tokens allowing them to participate in the governance of the overall protocol, to authenticate and adjudicate protocol direction and health.

Rather than using gas for the TSN app-chain, data providers pay a chain access fee to provide service and commit new data to the TSN. Data Providers are then whitelisted and data sets are logged and stored across the TSN. Any new source of data created becomes accessible to new network participants.

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