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FAIR² is a publishing platform for research data — combining curation, certification, and peer-reviewed publication into one operational workflow.

Reusable Data.
Credited Research.

Built for publishers. Powered by AI. Designed for trustworthy science.

Senscience turns open data requirements into credited research outputs. The FAIR² Data Platform handles the full lifecycle of research data—from curation and validation to peer-reviewed publication with DOI, interactive exploration, and responsible reuse guidance. Researchers get credit and career impact. Publishers reduce burden. Data becomes trustworthy, reusable, and AI-ready.

The Credit Gap: Why Open Data Alone Isn't Enough

~70% of researchers believe data sharing is under-credited. Open data requirements exist, but without clear attribution, career recognition, and reuse guidance, researchers have little incentive to invest in making data truly reusable.

Senscience closes this gap. By turning open data into credited, citable research outputs with clear reuse guidance, we make openness the path of least resistance—and give researchers the credit they deserve.

Senscience is already in production at Frontiers, demonstrating how data publishing can be operationalized at scale while closing the credit gap and enabling responsible reuse.

How It Works: From Raw Data to Reusable Research Outputs

The FAIR² Data Platform orchestrates the entire data publishing lifecycle. Scientists submit raw research data, and our AI-assisted processes—powered by Clara, our intelligent data steward working with human experts—handle curation, validation, and standardization in minutes instead of weeks. The platform applies rigorous quality checks, generates comprehensive metadata, ensures FAIR² compliance, and produces publication-ready outputs. The result: discoverable, trustworthy, reusable data that researchers can cite, publishers can confidently host, and machines can responsibly use. Senscience orchestrates across publishers, repositories, and institutions without replacing them.

Senscience FAIR2 Data Platform Workflow

Built on the FAIR2 Open Specification

The FAIR2 Data Platform is designed around the FAIR2 Open Specification for responsible, machine-actionable scientific data. Not proprietary, not locked-in—built on open standards that empower the scientific community and advance science.

What is FAIR2?

FAIR2 (Findable, Accessible, Interoperable, Reusable, AI-Ready, and Responsible) is a fully semantic framework built on open standards that goes beyond traditional FAIR principles. The FAIR2 Open Specification is not proprietary, not vendor-locked—it belongs to the scientific community. The FAIR2 Data Platform builds a per-dataset knowledge graph for each publication, enabling intelligent discovery and AI-ready data integration to advance science.

  • ✓ Per-dataset knowledge graphs for semantic understanding
  • ✓ Rich contextual metadata documenting full methods & protocols
  • ✓ Machine-actionable metadata on open standards
  • ✓ MLCommons Croissant compatibility
  • ✓ Intrinsic bias documentation
  • ✓ Ethical reuse guidance

Why FAIR2?

FAIR2 ensures that your scientific data is not just discoverable and accessible, but also semantically understood by machines and humans alike. Knowledge graphs enable intelligent data discovery, cross-dataset connections, and trustworthy AI applications that accelerate scientific progress.

Every scientific dataset published through the FAIR2 Data Platform meets FAIR2 Open Specification standards with built-in knowledge graphs, ensuring maximum scientific impact, responsible stewardship, and seamless integration with modern AI workflows.

FAIR² Pillars: FAIR (Findable, Accessible, Interoperable, Reusable), AI-Ready (Machine-actionable, TensorFlow/PyTorch integration), Responsible & Verifiable (Governance, provenance, ethics), Context-Rich (Methodology, contributors, bias documentation)

Learn more about the FAIR² Open Specification:

Visit fair2.ai

Featured Examples

FAIR2 Data Articles were pioneered with Frontiers. Explore real-world examples of this groundbreaking approach to data publishing, advancing science across multiple disciplines.

Ocean Sustainability

Environmental Quality Trends in Marine Ecosystems

Long-term monitoring dataset (1995-2023) of marine environmental quality across 51 sampling stations in the Bay of Biscay, including water quality parameters, biotic indices, and ecosystem health assessments.

  • ✓ FAIR2 Certified
  • ✓ 28 years of monitoring data
  • ✓ Multi-parameter water quality
View ArticleExplore Portal
Bioinformatics

SARS-CoV-2 Variant Structure Predictions

Structure-enriched dataset of 3,705 single-point and 100 higher-order SARS-CoV-2 variants with AlphaFold2 predictions, biophysical measurements, and ACE2 binding data for pandemic preparedness research.

  • ✓ FAIR2 Certified
  • ✓ 3,705+ variant predictions
  • ✓ Machine learning ready
View ArticleExplore Portal
Neurology

Multi-site MRI Dataset of Traumatic Brain Injury

343 diffusion-weighted MRI scans from 186 rats across 4 research sites with harmonized protocols, both raw and processed versions, supporting reproducible TBI research and machine learning model development.

  • ✓ FAIR2 Certified
  • ✓ 343 MRI scans
  • ✓ Multi-site harmonization
View ArticleExplore Portal

AI-Powered Data Curation & Validation

The FAIR² Data Platform leverages advanced artificial intelligence to automate data curation, validation, and metadata standardization. Our AI data steward transforms raw research data into publication-ready, FAIR² Open Specification compliant, machine-actionable assets in minutes instead of weeks.

Data Curation

Automated data preparation and organization in hours instead of weeks, while maintaining rigorous quality standards for careful review.

Quality Validation

Automated checks ensure data integrity, completeness, and compliance with standards.

Metadata Standardization

AI generates comprehensive, standardized metadata aligned with FAIR² principles.

AI-Ready Format

Datasets are transformed into machine-actionable formats optimized for AI systems.

From One Submission, Three Integrated Outputs

Each output serves a distinct purpose: establishing credit, enabling exploration, and ensuring preservation. Together, they close the credit gap and make data truly reusable.

Scholarly Record

Data Article

Peer-reviewed publication with permanent DOI. Researchers get career credit, publishers establish scholarly record, and the dataset becomes citable and discoverable.

  • ✓ Permanent DOI & citation
  • ✓ Peer-reviewed publication
  • ✓ Career recognition for researchers
Interactive

Interactive Portal

No-code exploration and AI-assisted analysis. Researchers explore without coding. Machines access responsibly. Reuse guidance ensures ethical, informed integration.

  • ✓ No-code exploration
  • ✓ AI-assisted analysis
  • ✓ Reuse guidance & ethics
  • ✓ Lifetime hosting
Preservation

FAIR² Package

Immutable archive with provenance, governance, and reuse assessment. Ensures long-term preservation, auditable lineage, and responsible reuse at scale.

  • ✓ Version of Record
  • ✓ Provenance & governance
  • ✓ Auditable & long-term

Why All Three Products Are Essential

The three products work together to address the complete incentive structure—breaking them apart breaks the solution.

Data Article

The peer-reviewed scholarly record with DOI creates academic legitimacy and career credit for researchers. It serves as the authoritative citable publication for your entire dataset—including the Interactive Portal and FAIR² Package. Without it, data remains invisible to the scholarly community and lacks proper attribution.

Solves: Academic incentives, discoverability, career advancement, proper citation and attribution

Interactive Portal

The live portal with lifetime hosting enables exploration, collaboration, and AI-assisted analysis. An AI data steward, governed by human experts, provides instant answers to common questions about the dataset, its methodology, and collection process—reducing the support burden on researchers while creating opportunities for new collaborations. Integrated responsible reuse framework guides ethical data application and documents intrinsic biases. Without it, data is static and inaccessible to researchers who need to explore and reuse it responsibly.

Solves: Data reusability, collaboration, research velocity, accessibility, ethical reuse

FAIR² Package

Senscience guarantees preservation with deposition to long-term archives for additional peace of mind. The immutable archive ensures institutional trust and research permanence, with integrity verification, data sovereignty support, and documentation of intrinsic biases and ethical stewardship guidance. Without it, data is at risk of loss, and funders cannot guarantee research impact or responsible reuse.

Solves: Long-term preservation, funder accountability, institutional trust, research permanence, ethical stewardship, data sovereignty

The Integrated Advantage

Together, these three products create a complete ecosystem that addresses every stakeholder's incentives: researchers get career credit and powerful tools, publishers maintain their editorial standards, funders see impact, and institutions ensure preservation. Separating them breaks this alignment.

Value for Every Stakeholder

Senscience creates measurable value across the entire research ecosystem.

Publishers

  • Editorial autonomy and standards control
  • Data integrity verification and sovereignty
  • Seamless integration

Researchers & Data Scientists

  • Interactive exploration
  • Machine-actionable datasets
  • Proper citation via peer-reviewed Data Article with DOI
  • Ethical reuse guidance & bias documentation

Funders

  • Maximize funding impact
  • Ensure accessibility
  • FAIR2 Certification compliance

Editors & Journals

  • Streamlined workflow
  • Automated validation
  • Responsible reuse framework

Reviewers

  • Pre-validated data
  • Interactive tools
  • Faster review

Repositories & Librarians

  • Pre-curated, FAIR2 Certified data
  • FAIR2 specification compliance
  • Ethical stewardship & bias documentation

The Data Lifecycle

From raw data to publication-ready assets, Senscience orchestrates a seamless workflow that produces three complementary products.

1. Raw Data Submission

Researchers submit raw datasets with minimal metadata. Senscience ingests and catalogs all incoming data.

2. AI-Powered Curation

Advanced AI systems analyze, validate, and standardize the data:

  • Quality validation and integrity verification
  • Comprehensive metadata generation with bias documentation
  • FAIR² compliance, standardization, and data sovereignty support

3. Publication-Ready Products

Data Article

Publisher-issued peer-reviewed article with DOI

Citable • Discoverable • Indexed

Interactive Portal

Live explorer with AI-powered analysis tools

Explorable • Interactive • Jupyter-Ready

FAIR² Package

Machine-actionable dataset with comprehensive metadata, standardized for AI systems and repositories

AI-Ready • Standardized • Reusable • Future-Proof

4. Lifetime Availability

All three products persist across complementary layers:

Data Lifecycle

Data Article

Permanent DOI, peer-reviewed citation, scholarly record

Interactive Portal

Interactive portal, AI access, Jupyter notebooks, DOI for portal

FAIR² Package

Version of Record, long-term preservation, immutable archive

Trusted by Leading Researchers & Data Experts

Hear from researchers, data stewards, and community leaders who are using the FAIR2 Data Platform to transform research data publishing.

★★★★★

"[Senscience] is one of the easiest and most effective ways to make data FAIR. Every PI wants their data to be findable, accessible, comparable, and reusable — in the lab, with collaborators, and across the scientific community. The real bottleneck has always been the time and effort required. [Senscience] dramatically lowers that barrier, putting truly FAIR data within reach for most labs."

Maryann Martone

Chief Editor, Open Data Commons

★★★★★

"[Senscience] provides objective checks on data quality and missingness that are invaluable for both domain experts and non-specialists. These unbiased assessments and data summaries will become crucial as we scale big data across disparate sub-disciplines."

Neil Harris

Professor, UCLA

★★★★★

"AI-assisted curation is a game changer—making research more accessible and delivering faster, more accurate insights to all."

Angel Borja

Marine Biodiversity Researcher, AZTI

Why Choose the FAIR2 Data Platform?

See how the FAIR2 Data Platform's AI-powered capabilities compare to traditional research data publishing workflows. While peer review timelines vary, the FAIR2 Data Platform accelerates data preparation, curation, validation, and metadata standardization from weeks to minutes—enabling careful review while dramatically reducing operational burden and enabling FAIR² compliance.

FeatureTraditional PublishingFAIR2 Data Platform
Data Preparation & CurationWeeksMinutes
Data ValidationManualAI-Assisted
Metadata StandardizationLimitedFAIR² Compliant
Interactive ExplorationNot IncludedBuilt-In
Lifetime HostingVariesGuaranteed
AI-Ready FormatNoYes

Frequently Asked Questions

Questions from publishers, researchers, and the broader research community.

For Publishers

Who owns the data?

Publishers and authors retain full ownership of their data. Senscience does not monetize access to data, portals, or reuse. We provide the infrastructure and curation; you maintain control over your editorial requirements and data strategy.

How long does integration take?

Integration typically takes 2-4 weeks depending on your submission system complexity. We handle journal configuration, system integration, and staff training. Most publishers are publishing their first datasets within a month of signing.

What support do you provide?

We provide dedicated support including technical integration, staff training, curation assistance, and ongoing platform maintenance. Our team is available to help with troubleshooting and optimization.

Is my data secure and compliant?

Yes. Senscience implements industry-standard security practices, data encryption, access controls, and compliance with GDPR, HIPAA, and other regulatory requirements. All data is backed up and preserved with integrity verification.

What is FAIR2 Certification?

FAIR2 Certification means your data meets the highest standards for Findability, Accessibility, Interoperability, Reusability, and Reproducibility. Every dataset published through the FAIR2 Data Platform is automatically FAIR2 Certified with machine-actionable metadata, semantic knowledge graphs, and compliance with the FAIR2 Open Specification. This certification ensures your data is discoverable by both humans and AI systems, maximizing research impact and reuse.

For Researchers & Community

How do I access published data?

All data published through the FAIR2 Data Platform is freely accessible through the Interactive Portal. You can explore datasets, download data, run analyses in Jupyter notebooks, and access the data through APIs. No login required for most datasets.

Can I use this data in my research?

Yes. All datasets published through the FAIR2 Data Platform are published under the ODC-BY (Open Data Commons Attribution) license by default, with additional data use agreements available for sensitive data. Each dataset includes clear licensing terms and responsible reuse guidance. Always cite the original data article and respect any specific usage restrictions.

What is the AI data steward?

The AI data steward is an intelligent assistant that answers common questions about datasets—what's included, how it was collected, methodology, limitations, and appropriate use cases. This reduces friction for researchers exploring new datasets and provides instant support.

How does responsible reuse work?

Each dataset includes documentation of intrinsic biases, limitations, and ethical considerations. Our responsible reuse framework guides researchers on appropriate applications, potential pitfalls, and best practices. This ensures data is used ethically and effectively.

Will this data be available long-term?

Yes. The FAIR2 Data Platform guarantees preservation with deposition to long-term archives. The Interactive Portal is maintained indefinitely, and the FAIR² Package is preserved in institutional repositories for permanent access. Your data is protected for decades to come.

How do I cite data from the FAIR2 Data Platform?

Each dataset is published as a peer-reviewed Data Article with a permanent DOI. The Data Article is the authoritative citable publication for the entire dataset, including the Interactive Portal and FAIR² Package. Use the DOI and Data Article citation in your research. Full citation information is provided on each dataset's landing page. Proper citation ensures researchers get credit for their data contributions.

Request a Demo

See the FAIR2 Data Platform in action. Our team will walk you through how we can transform your data publishing workflow.

Latest Updates & Insights

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