The FAIR Data-Ready LIMS

Legacy LIMS data hampers innovation and scale due to lack of interoperability. Labs need to integrate their data with other systems for various purposes, but most informatics systems do not support seamless migration, leading to information silos, data integrity risks, and time-consuming searches.
Labbit, built on FAIR data principles and a non-relational knowledge graph database, ensures easily findable, accessible, interoperable, and reusable data.



Data and its metadata need to be easy to find by humans and computers.




Once data is found, there is a way to access it, including authentication and authorization.




Data is in a form that allows it to be integrated with other data without any extra transformation required.




Data is optimized for reuse so that results can be replicated or datasets can be combined to discover new insights.

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Effortless integration

Combine data from diverse sources for a comprehensive view of laboratory operations and uncover new information to drive continued innovation. 


Improved quality and reliability

 Ensure consistent data representation with a informatics system that employs a unified data, metadata, and provenance model. 


Flexible querying

 Perform queries across diverse datasets without being constrained by predefined schemas to ensure that data collected today will be useful in the future, even if its use is not yet fully understood.


Adaptive models

 Accommodate data structures as they evolve with Labbit's graph-based model that is in your full control in the configuration layer, simplifying validation scope for regulated applications.



 Preserve data integrity with immutable data storage, preventing unwanted data modifications.


Chained histories

 Access and analyze high-fidelity historical data for a comprehensive understanding of your lab's operations and performance.



 Track the origin and lineage of data, enhancing transparency and data trustworthiness.


Semantic interoperability

Leverage RDF's semantic capabilities for seamless data exchange and integration between systems, eliminating the need for data cleanup and normalization, particularly in AI and ML applications.


Open data, open science

Make data and configuration elements from Labbit readily available for use on code-sharing platforms or other collaboration tools.



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