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The Connected Data Architecture (CDA) is the overarching framework that incorporates various layers and models to facilitate integrated data management and analysis. It is the layer to connect any application, whether a website, an app, or a piece of software. The CDA Protocol plays a major part in ensuring secure, on-device orchestration of multi-application tasks without depending on 1000s of APIs. Yes, it's like an invisible Zapier for one's device. This is a patentable technology that we can open-source. The architecture is designed to enable seamless communication, data sharing, and intelligence across different systems and platforms. The key highlights for CDA are as follows:
● edge computing (on-device); NOT on cloud
● secure and private
● central AI layer for context processing
● agentic actions across complex, sequential tasks
The key components of the CDA are as follows:
(A) Central Intelligence Layer (CIL)
User Memory (UM)
private User Memory (p-UM)
shared User Memory (s-UM)
inferred User Memory (i-UM)
Personalized Context Model (PCM)
(B) Agentic Action Models (AAM)
(C) Connected Data Protocol (CDP)
Central Intelligence Layer (CIL)
This layer serves as the core analytical engine of the CDA, responsible for processing and analyzing data gathered from various sources. It enhances decision-making capabilities by providing insights that are tailored to the specific needs of the user.
User Memory (UM):
User Memory is a sub-component of the CIL that stores and manages historical data and user interactions. This component is crucial for personalizing user experiences and improving the accuracy of predictive analytics.
private User Memory (p-UM):
This memory model within the User Memory stores sensitive and personal data that is not shared with other systems or components. It ensures privacy and security, handling data in compliance with data protection regulations.
The user (physically) needs to allow when access needs to be given to the application requiring the data. The system shows the necessary warnings to the user in this case.
Examples: Personal Identifiable Information (PII), Financial Information, Health Records, Security Details (Passwords, PINs), etc.
shared User Memory (s-UM):
The Shared User Memory is designed to store data that might be sensitive but could be shared under specific circumstances that require explicit approval from the Personalized Context Model (PCM). This ensures that sharing decisions are context-aware and respects user privacy and preferences.
Examples: User Addresses, Browsing History, Employment History, Device Usage Data, Location Data, etc.
inferred User Memory (i-UM):
In contrast to the pUM, the gUM contains data that can be accessed by other components within the CDA. This model facilitates collaborative features and functionality, allowing for more comprehensive analytics and insights. The PCM still needs to decide what data needs to be shared to which application, the algorithm can be a little relaxed compared to sUM. This is like cache data, based on the inference drawn from the user’s past activities so that the algorithms can promptly access data without going deep into past data and creating inferences from scratch.
Examples: General Preferences, Activity History, Anonymized User Opinions, etc.
Personalized Context Model (PCM):
The PCM works alongside the User Memory to tailor the analytical models to the specific contexts of individual users. It adjusts the parameters and filters of the intelligence layer based on user preferences, historical interactions, and environmental factors, ensuring that the insights are relevant and actionable.
Agentic Action Models (AAM)
The AAM is focused on enabling proactive actions based on the analytics and insights generated by the CIL. It uses advanced algorithms to predict outcomes and automate responses, effectively acting on the intelligence provided by the Central Intelligence Layer.
Connected Data Protocol (CDP)
This protocol defines the standards and methodologies for data exchange among the different components of the CDA. It ensures that data is transmitted securely and efficiently, maintaining integrity and compliance with data governance standards.
The Connected Data Protocol (CDP) is a collection of open specifications. The specifications consist of protocol APIs, message formats, network design, and reference algorithms. These allow applications to talk to the central process and thus create an immersive and personalized experience for the consumer. As a protocol, CDA is multi-layered, with a structure and organization resembling HTTP.
The CDP consists of several specifications because creating an open network requires the implementation of multiple layers of infrastructure, and each layer has its specifications. The HTTP protocol, for example, would not be able to deliver its functionality without its multiple layers, and the same applies to CDP. Following is the list of layers that CDP follows
Scopes in CDA
The Scopes within the CDA act as a comprehensive category of interactions, actions, and services that a user engages with across various technological ecosystems. It provides a unified reference framework, enabling applications to understand and contextualize diverse user behaviors and service touchpoints. This is pivotal in facilitating interoperability, personalization, and efficient service integration. Below is an elaboration on the types of interactions and services (as of now, we will be adding more) encapsulated within:
Shopping
Includes platforms and interactions related to online shopping, food delivery, and internet marketplaces. These services involve actions such as browsing products, placing orders, tracking deliveries, and managing returns.
Mobility, Logistics and Transportation
Encompasses on-demand mobility services, freight management, and logistics coordination. This category records actions such as booking rides, scheduling deliveries, tracking routes, and managing logistics workflows.
Social Media and Communication
Covers interactions on social platforms and digital communication channels. These services capture actions such as posting content, sharing messages, interacting with followers, and joining communities.
Health and Fitness
Focuses on digital tools and platforms for health tracking, fitness management, and telemedicine. Actions include scheduling consultations, tracking health metrics, managing prescriptions, and accessing health education.
Finance
Represents platforms and services for payments, savings, and investments. Interactions involve making a payment, starting savings goals, etc.
Education and Learning
Represents platforms and services for online learning, skill development, and academic support. Interactions involve enrolling in courses, accessing learning materials, taking assessments, and engaging in virtual classrooms.
Travel and Hospitality
Encompasses platforms and services for travel planning, booking, and hospitality experiences. This category covers everything from transportation arrangements to accommodation and trip management.
Entertainment
Covers platforms and services related to content consumption, gaming, and live events. These interactions include streaming digital media, participating in gaming ecosystems, and engaging with cultural or social events.
Google Sites
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