Self Profile

Cutting-edge project developed on the Self Framework, which aims to revolutionize the way individuals manage their personal data. The platform provides a wide range of features that enable users to collect, store, and manage their personal data in a safe and efficient way. SelfProfile provides the most comprehensive and secure solution for individuals to manage their data, allowing them to maintain control over their personal information while still being able to utilize it for various purposes.

Features and Core Concepts


The Self Profile uses the OWL2 ontology language to structure its decentralized digital identity and personal data. OWL2 was chosen for its expressive power, enabling the representation of rich and complex knowledge about various domains. This allows the Self Profile to effectively capture the nuances and relationships among different pieces of personal information, offering a flexible and adaptable data structure. 


One of the key features of Self Profile is its ability to integrate with other data providers and services. This is achieved through the Self Framework SDK for third-party integration, allowing for the development of custom solutions leveraging the power of Self Profile's data management capabilities.


The Self Framework offers an account guardianship option for situations where users may require additional oversight or protection, such as minors or individuals with limited decision-making capacity. Guardians can be granted specific permissions to manage and monitor the user's Digital Identities and associated Self Profile data, providing an added layer of security and control.

Linking profiles

One of the key features of Self Profile is the ability to connect profiles. This can be particularly useful for families who might need to share healthcare records, travel documents, financial information, and other types of data that are relevant to the entire family.


Secure, privacy-preserving authentication methods that do not rely on centralized identity providers, ensure that users have full control over their digital identities.


SelfFramework commitment to international interoperability ensures that users can maintain control over their data, regardless of where they are or what platform they are using. Self Profile will be implemented as a browser plugin or mobile app, making it easily accessible to users on various platforms. Self Profile adheres to IPSF- InterPlanetary File System for maximum compatibility.

Security and Self Sovereignty

All data is stored on Self Network in an encrypted format. Encrypting the declaration graph data before storing it on IPFS ensures that users' personal information remains private and secure, even in a public, decentralized storage system. Users can selectively share any portion of their Self Profile data with third parties while maintaining control over who has access to their information.

Data insights

Self Profile utilizes machine learning algorithms designed to analyze large amounts of data and identify patterns and relationships that may not be immediately apparent to humans to help them gain valuable insights and make informed decisions. Machine learning algorithms can also be used to personalize the user experience. By analyzing user behavior and preferences, Self Profile can provide tailored recommendations and suggestions


Data marketplace

SelfProfile's data marketplace is a unique way to earn money for your data. It is designed to connect users with researchers looking for specific data types, such as demographic information, shopping habits, or health data. Users can get paid for sharing their data and help advance scientific understanding by participating in the data marketplace.

The data marketplace is designed with privacy and security in mind. All data is anonymized and encrypted to protect user privacy, and users have full control over which data they choose to share and with whom. Additionally, all researchers must agree to a strict set of guidelines and ethical standards before they are allowed to access user data