Labbit: the FAIR-data LIMS that evolves as fast as your science
Support, manage, visualize, and evolve your entire lab workflow lifecycle with an innovative FAIR-ready LIMS — from ideation to operations, iteration, and scaling, all the way from research through clinical production.
Legacy LIMS: hampering true interoperability, innovation, and scalability
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.
However, most informatics systems available today were built when the value of combining data with its context (or metadata) was poorly understood. Such systems suffer from:
Using standardized and flexible data formats is key for interoperability and knowledge transfer. Legacy software, however, might not collect and store data in such formats.
Older systems often poorly integrate with other lab tools and systems. Manual data entry, mapping, and clean-up is therefore often required, and tracing data provenance across those systems is challenging.
An unsuitable, non-interoperable database format
Most, if not all, LIMS available today are built on relational databases, which don’t support several functions critical for findable, sharable, accessible, and reusable data. For example, relational databases don’t allow storage of data together with its critical context (metadata). Instead, they store data and metadata in separate tables connected by non-intuitive data constraints.
As a result, data remains locked up in a lab’s informatics systems and can’t be easily viewed by interested parties such as regulators and investigators. Data also cannot be shared in a user-friendly format.
With legacy solutions, exchanging data across sites and customized systems is a laborious and potentially error-prone process. It involves time-consuming and complex extract, transform, and load (ETL) procedures to get data into non-real time storage systems such as data lakes.
Critically, such a burdensome and slow process hinders innovation in your lab.
Labbit: save time with FAIR data from day one
Discover the benefits of a FAIR-ready LIMS in your lab
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