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Knowledge graphs for Locations in the Humanitarian and Development Sector

Session Track: App Dev

Session Time:

Session description

In the humanitarian sector, timely and accurate data is essential, yet master and reference data are often fragmented and siloed across systems as well as difficult to access or govern consistently. At the Norwegian Refugee Council (NRC), we are addressing this challenge by applying semantic web technologies and knowledge graph principles to master data management, with the aim of transforming how critical data is structured, related, and shared across the organization. This session will be about our use case of modeling NRC’s organizational locations using a graph database. Locations—spanning country offices, field sites, and headquarters—were previously stored in disconnected systems with limited visibility into their hierarchical or operational relationships. By restructuring this data into a knowledge graph, we now capture the real-world relationships between locations, including physical containment, administrative hierarchies, attributes and programmatic linkages. This graph-based model has significantly improved data accuracy, consistency, and accessibility across NRC. It has eliminated duplication, enabled dynamic queries across systems, and serves as a trusted single source of truth for both internal teams and integrated applications. Just as important, this model also supports GDPR compliance by providing clear data lineage and contextual traceability. This successful implementation demonstrates how moving from static taxonomies to dynamic ontologies and knowledge graphs can unlock the true value of master data, empowering humanitarian decision-making with more intelligent, connected, and governable data ecosystems.

Speaker

photo of Himanshu Ardawatia

Himanshu Ardawatia

Masterdata Management Lead, Norwegian Refugee Council

As masterdata management lead (data governance) at the Norwegian Refugee Council, Himanshu focuses on building meaningful, human-centered data ecosystems that drive sustainable outcomes. His work explores how knowledge graphs and semantic data models can break down silos, enhance interoperability, and make complex relationships across systems both visible and actionable. Himanshu combines technical depth in IT and data with insights from biology, systems thinking, network theory, and philosophy. This interdisciplinary lens enables him to design data architectures that not only support organizational goals but also empower people. Himanshu is also the creator of the physical simulation game for collaboration and gaining systemic insights called Glaring Reality.