I’m building OpenLIMS, an open-source Laboratory Information Management System using Django, React, PostgreSQL, Redis, Docker, and GitHub Actions.
The goal is to create a developer-friendly and configurable LIMS for small labs, research groups, and biotech teams that want to move away from spreadsheets and manual sample tracking.
Current features include:
Sample management
Inventory locations and containers
Custom fields for different lab workflows
Event/audit logging
File attachments for samples
Docker-based local setup
React frontend
Basic reports and system status pages
CI with GitHub Actions
It is still early and not validated for regulated production use, but I’m trying to build it with production-style patterns like audit trails, role-based access control, configurable workflows, and clear documentation.
I’d appreciate thoughts from people working in lab automation, LIMS, bioinformatics, or lab software:
What core LIMS workflows should I prioritize next?
What would make this useful for a small research lab?
What integrations would matter most: instruments, barcode scanners, CSV import/export, ELN, or something else?
Haha, I didn’t realize the name had that much history — maybe it is cursed
That’s good to know though. I’ll look into the older OpenLIMS projects and make sure I understand what happened with them. I’m still early, so I’m not opposed to renaming if it avoids confusion and gives this project a cleaner identity. Appreciate the heads-up!
This is cool! I guess my feedback is that there are a lot of these projects lately, and it’s probably very hard to get people to use something new.
I think the biggest value add for open source projects like this is creative new architecture solutions that solve specific problems, rather than a wholesale new LIMS system that tries to solve everything.
For instance, if you think you have a really good way to handle chain of custody attribution, share that with a write up! Discuss integration with different vendors and supplier APIs etc. I think specialization is key here, many people can spin up an entire LIMS system that works decently, but how many people have thought really hard about solving specific problems within that domain, and solving them really well? Certainly far fewer.
I agree — positioning it as a full LIMS is probably too broad early on. I’m going to narrow the focus around specific problems like chain of custody, audit trails, sample attribution, and instrument/data ingestion.
I really like your point about writing up the architecture for one hard problem instead of just promoting the whole system. Appreciate the thoughtful feedback.