DIA (Decentralised Information Asset) is an open-source oracle platform that aims to provide a reliable and verifiable bridge between off-chain data from various sources and on-chain smart contracts. This platform seeks to create an ecosystem for open financial data in a financial smart contract ecosystem, bringing together data analysts, data providers, and data users. DIA is the governance token of the platform and is based on the ERC-20 Ethereum protocol. The project aims to be a comprehensive source of financial data, addressing the issue of outdated, unverified, or hard-to-access data in the world of finance and cryptocurrency.

DIA operates by sourcing, supplying, and sharing trustworthy data. It incentivizes users to maintain the flow of open-source, validated data streams to the oracles. The DIA governance token is used to fund data collection, data validation, voting on governance decisions, and to encourage the development of the platform. Users can contribute DIA tokens to encourage new data to appear on the platform. DIA is a standard ERC-20 token, which means it requires Ethereum to function, inheriting all its strengths and weaknesses.

DIA can be used to build a variety of financial DApps (Decentralized Applications). It provides a reliable and verifiable bridge between off-chain data from various sources and on-chain smart contracts. This makes it possible to create applications that require access to real-world data, such as prediction markets, insurance contracts, and various types of financial derivatives. DIA also provides a platform for data analysts, data providers, and data users to collaborate and share data, fostering a community around open financial data.

DIA was founded in 2018 by a group of individuals including Paul Claudius, Michael Weber, and Samuel Brack. The token supply was introduced during the bonding curve period from August 3 through August 17, 2020, during which 10.2 million tokens were distributed. The total DIA token supply is limited with 200 million coins minted. The project aims to be a comprehensive source of financial data, addressing the problem of outdated, unverified, or hard-to-access data in the world of finance and cryptocurrency.

DIA, or Decentralized Information Asset, operates under a decentralized governance model. This model is designed as an inter-dependent system where specialists exchange expertise to ensure clear strategic direction, relevance, and improved functionality. The core of DIA's governance framework is the Decentralized Autonomous Organization (DAO), which is responsible for managing and overseeing DIA and its treasury. Token holders play a pivotal role in the decision-making process, as their votes determine the allocation of resources, strategic direction, and project support. Key aspects of DIA's governance framework include voting mechanisms, proposal submission, delegation and representation, incentives and rewards, and transparency and accountability. This governance model intends to facilitate decentralized decision-making, community involvement, and equitable representation, with the goal of fostering an environment that allows stakeholders to contribute to DIA's development and progress.

DIA addresses the issue of potential manipulation or inaccuracies in the data provided by oracles through a multi-layered approach. One aspect is that DIA sources data from multiple on-chain and off-chain sources, reducing the risk of relying on a single, potentially faulty, data source. Another aspect is DIA's use of a combination of on-chain and off-chain oracles, which aims to maintain the verifiability and consistency of its data. On-chain oracles are directly connected to the blockchain and can be used to retrieve data from on-chain sources such as smart contracts or other blockchain networks. Off-chain oracles, on the other hand, retrieve data from external sources such as APIs or websites and feed it into the blockchain through smart contracts. Moreover, DIA has implemented several layers of security, including outlier detection algorithms to identify anomalous data points, liquidity and volume filters for decentralized exchange (DEX) sources, and manual mitigation protocols and alarms for quick action in case of unexpected issues.

The DIA oracle platform strives to provide a broad spectrum of data and information that can be accessed and verified. This encompasses token market price feeds, derived from multiple high-volume markets, and NFT floor price feeds, which aim to provide multi-source and trade-based accurate pricing for NFT collections. The platform also offers LST price feeds, utilizing a fair-value based pricing approach that takes into account the collateral ratio. DIA's on-chain randomness is another feature that can be leveraged to build DeFi and GameFi dApps. The platform also facilitates the construction, deployment, and monitoring of custom oracles. DIA's data feeds aim to offer full customization in terms of the mix of sources and methodologies, frequency, and more.

DIA is involved in the process of integrating off-chain data into on-chain smart contracts by sourcing, validating, and sharing verified and transparent data feeds for traditional and digital financial applications. DIA collects data points from various off-chain and on-chain sources. These sources include various types of exchanges, Metaverses, NFT marketplaces, Decentralized Finance (DeFi) systems, Traditional Finance (TradFi) systems, and more. The data is pulled directly from their smart contracts and APIs. The raw data undergoes a process of sanitization and further processing. Once the data is cleansed and further processed, it is stored inside a flexible, open-source, and unchangeable database. The processed data is accessible both off-chain and on-chain.

Yes, DIA (DIA) has been involved in numerous partnerships and collaborations. These collaborations span across various sectors within the blockchain and DeFi space. For instance, DIA has partnered with several DeFi platforms such as Starlay Finance, Beamswap, and SiO2 Finance, aiming to provide them with transparent and reliable asset price oracles. DIA has also collaborated with NFTfi platforms like Zumer Protocol and Starfish Finance, with the intention of offering them NFT Floor Price oracle services. In the GameFi sector, DIA has partnered with Orbital Apes: Rumble and Arka Finance, striving to provide them with oracle services. Moreover, DIA has collaborated with educational institutions like the University of Arizona James E. Rogers College of Law and Macomb Community College, with the goal of offering courses and creating further education opportunities. These partnerships and collaborations demonstrate DIA's intention to offer data services within the DeFi industry.

Yes, individuals or organizations have the ability to contribute their own AI models to DIA. This process, often referred to as "fine-tuning" an existing AI model with specific data, is observed in the field of artificial intelligence and machine learning. Organizations may use their own data to train AI systems, with foundation models serving as a starting point. This approach aims to provide context and seeks to mitigate potential risks, such as inaccuracy and intellectual property infringements. The use of personal data for AI model training is subject to applicable data privacy laws. This involves considerations such as the legal basis for training AI models using publicly available data, the process of informing data subjects about the use of their publicly available personal data for AI model training, and the conditions under which AI models can be trained on special categories of personal data.

DIA (DIA) strives to support the development of ethical AI practices by implementing an artificial intelligence strategy and establishing a governance model. This model is intended to guide the development and standardization of AI technology, with an aim to align with ethical AI principles. DIA also collaborates with other intelligence community agencies to identify gaps that could potentially be addressed through this strategy. In addition, DIA is working on standardizing the operationalization of new capabilities, identifying talent and skill gaps, and working on platforms. The aspiration is to use AI responsibly and ethically, with accountability measures in place to address potential mistakes. This approach may be of interest to medical device manufacturers and other industries that are considering the use of AI in their operations.