DDD is the digital token symbol for the Scry.info project. Scry.info is a blockchain-based platform for quantitative data provision and trading, aiming to provide a digital contract engine for an intelligent blockchain society, enabling developers and individuals to find data sources from sports, entertainment, transportation, weather, finance, agriculture, genetic models, etc., and encouraging more global community developers, multinational organizations, companies, and individuals to participate in the cluster intelligence certification of blockchain data nodes by contributing data sources.

Vision of the Project

SCRY.INFO aspires to offer a digital contract engine for an intelligent blockchain society, allowing developers and individuals to access data sources from various fields including sports, entertainment, transportation, weather, finance, agriculture, genetic models, etc., and encourages global participation of community developers, multinational organizations, companies, and individuals in the cluster intelligence certification (Using Authentication in Certification agreement Based Swarm Intelligence) by contributing data sources to the blockchain data node network.

Application Scenarios

1. Shared Real Data Service for All Prediction Market Applications
In the current blockchain ecosystem, prediction applications represent a significant market, yet many of these applications often need to independently introduce real-world data into the blockchain. Due to the focus on application development, its difficult for other applications to share the data introduced by any one prediction market application. This not only leads to wastage of blockchain resources but also results in insufficient accuracy of voting outcomes due to the small user base of individual prediction applications.
SCRY.INFO proposes a unified public data service concept aimed at breaking down the data barriers between each prediction application. For instance, if a prediction application As data can be provided to application B upon payment of adequate fees, using SCRYCOIN for settlement, this data can also be utilized by business reports, opinion polls, and other types of applications. The protocol ensures the rights of all participants through regulated transaction fees.
2. Information Market for Data Providers and Data Consumers
How can we facilitate the interoperability of data to maximize its value?
SCRY.INFO provides data providers with a flexible mechanism: apart from supplying specific data requested by data seekers, they can also independently publish data. Through SCRY.INFO, this data can be marketed to the entire marketplace: any data seeker can obtain data and verification services by paying a one-time query fee to the data provider and the data notary. This ensures the independence of data providers and reduces their reliance on existing data consumers.
Data consumers constitute a broad group, such as providers of business reports, who typically require a large amount of verifiable data in their reports. SCRY.INFOs data trading model perfectly meets this demand.
For example: Suppose a data provider A creates a supply agreement contract Y and passes the notarization process. At this point, report provider B needs the data from Y for their own report contract Z. B pays the query fee, queries the data from Y, and saves it in their Z contract, ensuring that the validation function in Z includes code that calls the verification API in Y. In the future, if B needs to prove the source of the data in the Z contract, the verifier only needs to call the validation code provided by Z.
3. Business Intelligence Voting and Hot Marketing Tool
Business intelligence voting and market hot spot marketing surveys are industries heavily reliant on data. For instance, a business entity might want to survey peoples opinions on the color of their brands winter clothing from previous years to inform this years design. Traditionally, there are several approaches; distributing flyers, which is labor-intensive and inefficient; initiating votes on their official website with incentives, but low participation due to low website visibility; purchasing data from centralized third-party institutions, which is costly and lacks authenticity.
SCRY.INFO aims to provide efficient services, such as:
Business entities can initiate a public voting contract (bounty-style) on SCRY.INFO, inputting options, descriptions, upper limits for voters, and valid voting ratios, then publish it. Participants in the SCRY.INFO ecosystem, noticing the bounty, directly enter the notarization phase to vote on the set options. After successful voting, participants receive the bounty (SCRYCOIN), and NGOs receive sample data, achieving a win-win situation. Moreover, brands can review the results in subsequent years, accumulating user intent trend tables on an annual basis, providing reliable data guidance for future market-oriented policies.
4. Notarial Services for Individuals and Enterprises
Furthermore, the data protocols provided by SCRY.INFO, after special settings, can offer notarial services for real-life matters like property notarization and wills. These services not only possess traditional functions but also have unique advantages. Firstly, these electronic agreements have the decentralized and immutable characteristics of blockchain, which are particularly crucial for notarial purposes; secondly, the protocols themselves are citable, enabling direct use of these notarizations in a logically verifiable and reviewable format, something traditional notarial services struggle to achieve.
The specific usage involves first constructing a delegated supply agreement contract, setting data writers and data notaries in whitelist mode, specifying the identities of data writers and data notaries. Then, data writers and data notaries attach their signatures for this contract when writing and notarizing data, respectively. Upon submission of the contract, a multi-party signed notarial record is generated.
Technically, since it is a blockchain centered around data storage, how to store data becomes the most critical technological challenge they need to overcome.
SDBC is a new decentralized data storage blockchain. Currently, small data is placed on ETH, while larger data is indexed on IPFS, but these third-party storages do not entirely meet SCRY.INFOs requirements for data storage and query behavior. They plan to develop a blockchain more suitable for SCRY.INFOs querying operations, capable of providing greater storage capacity, enhanced data security, and faster query speeds for SCRY.INFOs foundational services.
To meet their data storage demands, there are several key objectives during development:
1) Ensuring the integrity of stored data: By storing data in blocks located across the network nodes, Merkle Tree is used for integrity verification, with optimizations for storage and queries.
2) Security of data storage: Different security levels are set for signing data inserted (using DSA, RSA, ECDSA, etc.), as well as multi-party signature forms. Merkle Tree is used to verify the legality of nodes. Cryptographically secure pseudo-random number generators (CSPRNG) generate private keys, and elliptic curve algorithms produce corresponding public keys. They plan to use a transformed version of the public key as the identifier for each node, i.e., the public key becomes an address form after SHA processing: Base58 (identification + public key + head4 (SHA256 (SHA256 (public key))) etc.
3) Providing SQL-like simplified operation commands for complex business queries: Offering a lightweight distributed relational data storage and processing similar to Azure cloud databases. They plan to adopt the SCRYO-Top query algorithm based on the three-dimensional bucketing Bloom filter table (TF). Experimental results show that this algorithm avoids repeated access to data objects and efficiently processes large-scale data queries with low false-positive rates. Compared to NRA and BPA, overhead significantly decreases when the attribute list exceeds four attributes, making it suitable for query processing applications aimed at large-scale data.

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