Yes, OpenLR offers comprehensive documentation and open-source tools for implementation. Key resources include the official white paper, a Java-based reference implementation, and practical guides such as the HOWTO.md on GitHub. These resources cover encoding, decoding, and integration workflows to support both beginners and experienced developers.This box suggests the current best answer
Short Summary Answer
Yes, OpenLR offers comprehensive documentation and open-source tools for implementation. Key resources include the official white paper, a Java-based reference implementation, and practical guides such as the HOWTO.md on GitHub. These resources cover encoding, decoding, and integration workflows to support both beginners and experienced developers.
Stakeholder Relevance / Rationale
Public Authorities: Access to well-documented, transparent technology supports procurement and compliance.
Content Providers: Facilitates integration into existing data pipelines through clearly defined formats and tools.
Service Providers: Accelerates development and integration with support from reference code and best-practice examples.
OEMs: Enables rapid prototyping and integration into in-vehicle systems using proven libraries and flow diagrams.
Detailed Explanation
Types / Versions / Formats
ISO standard: ISO 21219-22 – TPEG2-OLR Standard
Core Documentation: The OpenLR White Paper explains the encoding/decoding process, location types, formats (binary/XML), and algorithmic flow.
GitHub Repository: Includes the official Java-based reference implementation with encoder/decoder modules, test data, and CLI tools.
HOWTO.md: Step-by-step guide for implementing OpenLR in your own systems: View here.
Use Cases
Custom Software Development: Developers can use or adapt the Java library to suit their platform (e.g., re-implement in C++, Python).
Integration with Map Engines: Compatible with tools like OpenStreetMap, GraphHopper, and OSRM.
Real-time Applications: Suited for transmitting dynamic location data efficiently between systems.
Technical Considerations
Encoder/Decoder Design: Requires both sides of the system to implement correct encoding and decoding logic.
Diagrams and Pseudo-Code: Included in the white paper and repository to support alternative language implementations.
No Hosted API: OpenLR is a library/specification—not a cloud service—so self-hosted integration is necessary.
Decision Guide
| Need | Resource/Tool |
|---|---|
| Understand the OpenLR concept | OpenLR White Paper |
| Understand the ISO TPEG2-OLR formats | |
| Understand the ISO TPEG2-OLR encoding | |
| Understand OpenLR encoding in DATEXII | |
| Implement OpenLR in Java | GitHub Repository |
| Implement OpenLR in python | |
| Follow hands-on instructions | HOWTO.md Guide |
| Explore dynamic location usage | INRIX Documentation |
| Re-implement in another language (e.g., C++) | Use flow diagrams and algorithm logic from white paper and GitHub |
Implementation Notes
There is no “plug-and-play” API; integration requires embedding the encoder and decoder into your own systems.
Ensure that test data is validated across both encoding and decoding ends to confirm map alignment.
Community forums and forks may offer additional language implementations or platform-specific tips.
References & Tools
OpenLR White Paper (PDF) and OpenLR_Decoding_bits_and_bytes v1.0,1 (PDF)
- DATEXII OpenLR™ (Point, linear and area location)
- TN-ITS integration: to become EN TS 16157, Part 14: TN-ITS (work-item in CEN TC278 W7, publication expected Q1 2026)
- TISA Github
- OpenLR Python Documentation
- StackOverflow: OpenLR Binary v3 discussion
