This box suggests the current best answer
Prior revisions of answers
Proposal 2/3, updated
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, finalisation expected Q4 2025)
- TISA Github
- OpenLR Python Documentation
- StackOverflow: OpenLR Binary v3 discussion
Comments
Who | What | Decision | |
|---|---|---|---|
| 1 | TH / Aziya | Add OpenLR decoding Bits and Bytes explainer document OpenLR_Decoding_bits_and_bytes_v1.0.1.pdf | |
| 2 | |||
| 3 |
Processed comments meeting July 9th
Who | What | Decision | |
|---|---|---|---|
| 1 | TH | Add TN-ITS CEN standard to be, DATEXII standard OpenLR | Included: EN TS 16157, Part 14: TN-ITS |
| 2 | ST | More python encoder/ decoders to check for links / inclusion in references https://openlr-python.readthedocs.io/en/latest/ | To be mentioned, TH included it in Q3 decision guide and references and tools section |
Proposal 1
Proposal text (MS Copilot generated) | ChatGPT | ChatGPT Plus - OpenLR Guru |
|---|---|---|
Yes, there is comprehensive implementation documentation available for OpenLR. Here are some key resources: GitHub RepositoryThe OpenLR GitHub repository contains the reference implementation of OpenLR. It includes modules for encoding and decoding OpenLR locations, as well as tools for map access and data handling [1]. HOWTO.mdThe HOWTO.md file in the GitHub repository provides detailed instructions on how to encode and decode OpenLR locations on digital maps [2]. INRIX DocumentationINRIX offers documentation on Dynamic Location Referencing, which includes information on OpenLR. This resource provides insights into the implementation tools available, such as the Java-based encoder/decoder and map access layer [3]. These resources should help you get started with implementing OpenLR in your projects. | 1. Official OpenLR Documentation (by TomTom)📄 OpenLR White Paper (Core Specification)
📍 Link: https://www.openlr.org/docs/OpenLR-whitepaper.pdf ✅ 2. OpenLR Reference Implementation (Java Library)📦 Official GitHub Repository
📍 GitHub: https://github.com/TomTom/openlr ✅ 3. OpenLR Encoder/Decoder Flow Diagrams
This helps if you're implementing OpenLR in a language other than Java (e.g., C++, Python, JavaScript). ✅ 4. Community/Examples
❗Note: No "Plug-and-Play" Web API
Bonus: Alternatives and ExtensionsIf your use case goes beyond what the core OpenLR offers, you might consider:
| Yes, there is detailed implementation documentation for OpenLR you can follow. Here's a summary of what's available and how you can use it: 📘 Official Documentation Sources1. OpenLR Whitepaper (v1.5) – Core Specification
📄 Your uploaded file: 2. Reference Implementation on GitHub (TomTom)Repo: github.com/tomtom-international/openlr
🧪 Testing Tools
🧰 What You’ll Need to ImplementTo integrate OpenLR:
✅ Additional HelpYou can also explore:
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