Schema Version: 1.1.0 (Draft)

GenuineIN Learning & Employment Record
(LER) Schema

About GenuineIN

GenuineIN is a global digital identity and credentialing platform focused on creating interoperable, verifiable, and lifelong profiles for individuals. By leveraging emerging standards in decentralized identity, GenuineIN empowers learners, professionals, institutions, and organizations to issue, manage, and share trusted records across borders and platforms.

As a member of the growing ecosystem of self-sovereign identity (SSI) adopters, GenuineIN contributes to a future where personal achievements, qualifications, and capabilities are digitally portable, tamper-evident, and user-controlled.

Interoperable

Share trusted records across borders and platforms with ease.

Verifiable

Leverage tamper-evident, digitally portable credentials.

User-Controlled

Empowering individuals with self-sovereign identity (SSI).

The GenuineIN LER Model

The GenuineIN LER schema defines a structured, extensible, and standards-based data model to represent individual life experiences and achievements. This model is compliant with the W3C Verifiable Credentials Data Model, enabling interoperability across decentralized and federated ecosystems.

GenuineIN supports 15 types of LERs, reflecting the diversity of an individual's learning and career journey:

Education
Experience
Certification
Course
Internship
Training
Participation
Project
Research
Publication
Test Score
Recognition
Volunteer
Membership
Sports

Vision & Purpose

The primary vision of the GenuineIN LER schema is to:

  • Promote data interoperability across educational institutions, employers, credentialing agencies, and international bodies
  • Support verifiable digital credentials that are tamper-resistant, portable, and privacy-preserving
  • Align with global initiatives such as the European Learning Model (ELM), Open Badges 3.0, Comprehensive Learner Record (CLR), and the T3 Innovation Network
  • Enable integration with decentralized identity systems using DIDs, VCs, and JSON-LD as foundational primitives

By doing so, GenuineIN contributes to a future-ready ecosystem for cross-border recognition of learning and work.

Standards Alignment

  • W3C Conforms to the W3C Verifiable Credentials and Decentralized Identifiers (DIDs) specifications.
  • JSON Designed to be compatible with JSON Schema, OpenAPI, and LD-Signatures.
  • PRIVACY Enables selective disclosure, Zero-Knowledge Proofs (ZKPs), and revocation support.

Versioning and Availability

This document is open for public feedback and contributions via the GenuineIN GitHub Repository.