In this series, we’ve explored the four principles of FAIR — ensuring that your data is Findable, Accessible, Interoperable, and Reusable. We’ve also looked at how a LIMS can help labs achieve data that meets these principles, and where a traditional LIMS might fall short. It should also be obvious from these posts that FAIR isn’t something a lab can achieve alone. FAIR data requires shared standards, common tools, and community adoption, not just the good intentions of a single lab or a well-configured LIMS.
To make FAIR practical at scale, global organizations have stepped in to develop frameworks, vocabularies, protocols, and best practices that help labs adopt FAIR in real-world settings. Two of the most influential forces driving this movement are the Pistoia Alliance and GO FAIR.
What is the Pistoia Alliance?
The Pistoia Alliance is a global, not-for-profit organization that brings together life science companies, technology vendors, publishers, and research institutions to make R&D more collaborative, innovative, and data-driven.
The Alliance is known for turning industry FAIR challenges into shared solutions. Some of these initiatives include:
- FAIR toolkits and data models: Standardized approaches to metadata capture, identifiers, and semantic interoperability in pharma and biotech. For example, the Unified Data Model (UDM) project created an open, extendable, and freely available data format for the exchange of experimental information about compound synthesis and testing. Originally co-developed by Elsevier and Roche, with input from other pharmaceutical companies, UDM was donated to the Pistoia Alliance so the model could be extended and adopted even more widely.
- Ontology and vocabulary working groups: Collaboratively developing controlled vocabularies that support FAIR interpretation of R&D data. The Pharma General Ontology project, for example, has a charter to identify “preferred vocabularies for community-wide standardization of core concepts” in the pharmaceutical industry.
- Pre-competitive technology projects: Members co-fund projects that no single organization could build alone. For example, the Informed Consent Blockchain project built BlockSent to secure informed consent in clinical trials. This solution “implemented key components of decentralized digital identities,” including decentralised identifiers (DIDs), verifiable credentials (VCs), and a blockchain registry (a digital ledger that uses blockchain technology to record transactions in a secure, transparent, and tamper-proof way).
- Training and change management programs: Workshops and adoption guides that help organizations not just understand FAIR, but implement it. The Change Management Community has a number of goals, including increasing change management leadership skills, developing strategies to prepare for enterprise and project level transformation, creating training and certification for members of the Pistoia Alliance, and sharing best practices for change management in the context of digital transformation.
Many FAIR efforts fail not for technical reasons, but because organizations lack shared standards and alignment. Pistoia helps solve this challenge by supporting and encouraging collaboration across academia, pharma, and vendors; reducing duplication; and helping FAIR principles become real, scalable practice.
What is GO FAIR?
GO FAIR is an international effort focused on implementing FAIR principles and promoting FAIR-by-design approaches across all data domains. The organization supports FAIR through:
- FAIR principles and FAIRification process: GO FAIR provides straightforward, evolving guidance on the FAIR principles, how to “GO FAIR”, and the FAIRification process, helping organizations progress the maturity of their FAIR data over time.
- Implementation networks: GO FAIR implementation networks (INs) are composed of groups of researchers, institutions, and technologists who come together to solve FAIR challenges in a specific domain, such as rare disease data, chemistry data, and lab automation metadata. The Virus Outbreak Data Network (VODAN), for example, developed FAIR-compliant infrastructures for pandemic data sharing across hospitals and governments during COVID-19, enabling controlled access to patient data under strict privacy rules.
- Standards and protocol advocacy: GO FAIR promotes shared frameworks such as persistent identifiers (like ORCID for researchers, DOI for datasets, and RRIDs for reagents), open communication protocols (like HTTPS/REST APIs with OAuth2 authentication), and FAIR-compliant vocabularies.
- Policy and funding influence: The GO FAIR International Support and Coordination Office works with organizations and public policy actors on changes in culture, training, and technology to support the shift to FAIR data. GO FAIR also contributes to developments in the federated European Open Science Cloud (EOSC), which has a goal of providing a multi-disciplinary environment for publishing, finding, and reusing data, tools, and services for research, innovation, and educational purposes.
GO FAIR helps create the rules, expectations, and proof points that labs need to justify investment in FAIR data practices, including the implementation of modern, interoperable LIMS solutions.
How these initiatives can benefit your lab
You don’t need to join either consortium to benefit from their work. However, your lab could gain tremendous value by aligning with the standards and frameworks they have created. For example, your lab could benefit from:
- Using community taxonomies and ontologies
- Selecting tools that support FAIR-compliant APIs
- Employing persistent identifiers across systems
- Exporting data in repository-friendly formats
- Choosing vendors who adopt FAIR-by-design
In practice, these global initiatives make it easier for your lab to adopt data standards without building them from scratch. They also help you validate software purchases with FAIR-aligned benchmarks, collaborate securely across institutions or research domains, and know that today’s data will still be usable decades from now.
Where LIMS fit in
Although these initiatives don’t build LIMS, they do shape the requirements your LIMS should meet. If your lab wants to be FAIR-ready, you’ll need lab informatics solutions that support:
- Semantic interoperability (ontologies, identifiers)
- Open, standards-based APIs
- Structured metadata capture
- Repository-friendly exports
- FAIR licensing, provenance, and tracking
Most traditional LIMS systems were built before FAIR existed, making true alignment difficult or impossible without major customization. However, next-generation lab informatics systems, like Labbit, have been built with FAIR in mind. This gives labs a more efficient way to implement FAIR data, solve challenges through new innovations, and future-proof the business.
What’s your next move?
The FAIR movement is more than a set of ideals. It’s quickly becoming the foundation of modern, data-driven science. For labs, the message is clear: investing in FAIR today could help you shape the breakthroughs of tomorrow.
Whether you’re running a single research lab or a large commercial lab organization, now is the time to move beyond data capture and start building data that can collaborate. The next step starts with your infrastructure. Choose tools, systems, and standards that make FAIR practical, and turn your data into an asset that grows more valuable every year.
Contact us to begin or advance your FAIR data journey.
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