Data Linkage & Entity Resolution
Connect data.
Reveal insights.
Linking data from multiple sources is fundamental to modern research. SeRP Linkage combines advanced technology with specialist expertise to accurately match records across datasets, helping organisations create richer, research-ready data while maintaining robust governance and quality assurance.
Accurately identify when records belong to the same individual—even when information is incomplete, inconsistent, or recorded differently across datasets
Whether data remains within its host environment or is brought together under shared governance, SeRP provides flexible federation approaches to support collaborative research at scale.
Why SeRP Linkage?
Flexible Linkage Methods
Every dataset is different.
SeRP Linkage supports deterministic, probabilistic, fuzzy, and hybrid linkage techniques, allowing the most appropriate approach to be applied based on the characteristics of your data.
More Than Record Matching
Data linkage is only one part of the process.
SeRP provides tools and expertise for:
Helping organisations build confidence in their linked datasets.
Built for Scale
Whether linking new datasets to an existing research resource or matching records within a single dataset, SeRP Linkage supports both one-off linkage projects and repeatable, automated workflows.
Choose between:
Measure Linkage Quality
Understand the confidence behind every linkage.
SeRP provides comprehensive reporting and quality metrics that help practitioners evaluate linkage performance, identify potential issues, and continuously improve matching accuracy.
Backed by Research Expertise
Our specialist linkage team doesn't just use existing methods—they actively contribute to the development of new linkage techniques and technologies.
Working alongside your organisation, we help design linkage approaches that meet your data, governance, and research requirements.
Key Capabilities
Need to link data from multiple sources?
Talk to our linkage specialists about your project requirements.