Price-Time Priority Queues for User Data Asset Trading
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current advertising systems lack transparency and accountability, failing to transform user data into tradable assets, leading to inefficiencies and privacy issues, as users have no control over their data and are subjected to price discrimination, with no viable market structure for fair exchange of user attributes.
Innovation Solution
A system that transforms user attributes into tradable assets by creating a virtual community where users can control and trade advertising attribute specification units as forward contracts, using price-time priority queues, ensuring transparency and accountability through blockchain audit and transparent pricing mechanisms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If user data is collected by web browsers and technology companies without user control, then companies can monetize user attributes through advertising, but users lose control over their data and are subjected to price discrimination and privacy abuse
Solution Approach 1:
Users are empowered to self-manage their data attributes through a marketplace interface where they can view, select, license, and revoke access to their personal attributes. The system provides self-service tools for users to control who accesses their data and under what terms, eliminating the need for companies to unilaterally collect and monetize user data without consent.
Solution Approach 2:
A data marketplace intermediary platform is introduced between users and data consumers. This intermediary facilitates transparent transactions by matching data supply with demand, enforcing licensing terms, and ensuring fair compensation to users. The marketplace structure prevents direct exploitation while enabling efficient data utilization through standardized contracts and pricing mechanisms.
2Adaptability or versatility
If technology companies monopolize user data collection and advertising exchanges, then they can set hidden agendas in prioritization, but this creates inequality and prevents fair exchange for user data
Solution Approach 1:
The monopolistic data exchange is segmented into a distributed marketplace where multiple independent participants (users, data consumers, intermediaries) operate autonomously. User data attributes are segmented into discrete licensable units that can be independently traded, preventing any single entity from controlling the entire data ecosystem and enabling transparent, auditable transactions.
Solution Approach 2:
The traditional model is inverted: instead of companies collecting user data and then offering it back to users in advertising, the system allows users to directly license their data attributes to companies. This reversal of the data flow empowers users as the primary data controllers and creates inherent transparency through market-based pricing and explicit licensing agreements.
3Productivity
If user attributes are not transformed into tradable assets with market structure, then data exchange lacks efficiency and accountability, but creating such a market requires complex legal and technical transformations
Solution Approach 1:
User data attributes are transformed from static personal information into dynamic tradable assets with standardized market parameters including pricing, licensing terms, duration, and scope of use. The system introduces financial parameters (price, bid, ask, spread) and legal parameters (licensing terms, compliance requirements) that enable efficient market-based data exchange while maintaining accountability through structured contracts.
Solution Approach 2:
The marketplace infrastructure provides universal functionality for all types of user attributes and data consumers. A single standardized platform handles diverse data types (personal information, behavioral data, device attributes) through common mechanisms for listing, bidding, licensing, and enforcement, reducing complexity through standardization rather than requiring separate systems for different data categories.
4Speed
If advertising attribution specifications are not transformed into forward commodities with price-time priority queues, then there is no efficient matching between advertisers and users, but implementing such transformation creates market structure complexities
Solution Approach 1:
The traditional mechanical matching process between advertisers and users is replaced with an automated electronic marketplace system using price-time priority queues. Bids and asks are automatically matched based on price and timestamp, eliminating manual or algorithmic matching complexities while enabling high-speed automated transactions. The system substitutes complex matching algorithms with simple, transparent queue-based mechanics similar to stock exchanges.
Data Source
AI summary
Implementations of various methods and systems to transform socket communication streams combined with vaulted user characteristic data over an advertising trading exchange with price time priority queues.