FAIR Data

The data in legacy LIMS is not truly interoperable, hampering innovation and scale.
 
Labs today produce rigorously quantified and well contextualized data. But with the explosion of innovation in the life sciences, they must now be able to integrate that data with other systems, whether to simply bring in a qualified list of reagents or to import a biobank dataset for a validation study. Unfortunately, most informatics systems available do not store data in a way that facilitates seamless migration into other systems leading to information silos, risks to data integrity, and time consuming searches, all of which impact your lab's ability to quickly innovate and scale.

Use Labbit

The inherently FAIR laboratory informatics system

Labbit is the only solution built from the ground up on FAIR data principles.

Built on a non-relational knowledge graph database its data is easily findable, accessible, interoperable, and reusable.

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Findable

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

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Accessible

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

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Interoperable

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

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Reusable

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

With a truly interoperable FAIR-compliant system, labs can eliminate the time and work associated with transferring data between systems, re-platforming, and connecting to other data sources.

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.

 

Immutability

 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.

 

Provenance

 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.

 

 

RESOURCES

RDF Knowledge Graph Databases: A Better Choice for Life Science Lab Software

Every laboratory that uses informatics software is using a database to store and access the data produced by their laboratory. But what laboratory managers might not be aware of is that the underlying type of database can impact how effectively a laboratory can innovate and scale.

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