From 23–26 March 2026, iCARE4CVD participated in SWAT4HCLS in Amsterdam, the Netherlands, a conference focused on improving how health data is structured and used.
During the event, iCARE4CVD lead researchers Komal Gilani (Maastricht University) and Cornelis Bouter (TNO) presented their team’s latest work, developed through close collaboration between data scientists at Maastricht University, including Associate Professor Visara Urovi and Professor Michel Dumontier, and TNO’s Digital Biomarker Scientific Lead, Willem van den Brink.
Their poster introduced a Digital Biomarker Ontology (DBO) – a framework to organise and connect data from remote monitoring devices such as blood pressure monitors, smartwatches, and scales. The goal is to structure data from various devices so it can be meaningfully interpreted, combined, and merged across data sources to answer key questions.
As Komal explains, one of the main challenges lies in making sense of the growing volume of fragmented data:
“Remote monitoring generates vast amounts of data, but without a structured way to connect it, its value as digital biomarkers remains largely untapped. We’re exploring whether semantic modelling can turn this fragmented data into a queryable knowledge graph—enabling questions around adherence, cross-setting comparisons, device usage patterns, and even insights we haven’t anticipated yet.”
This work addresses a key challenge in digital health: patient data is often fragmented across devices and systems, making it difficult to use in practice. By creating a shared structure, the DBO helps transform raw measurements into meaningful insights for clinicians and researchers.
Importantly, this contribution is part of iCARE4CVD’s broader effort to collect, harmonise, and integrate diverse cardiovascular data, to enable secondary data analysis for a more personalised and data-driven care of CVD conditions.
This work also builds on earlier work within the project, such as the Clinical Metadata Exploration Ontology (CMEO), which focuses on organising and making study-level data easier to find and reuse. Together, these approaches are helping to create a more connected and usable data ecosystem—bringing iCARE4CVD a step closer to its goals.
A big thank you and congratulations to the iCARE4CVD team—Komal Gilani, Cornelis Bouter, Willem van den Brink, Visara Urovi, and Michel Dumontier—for this contribution!
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