Semantic Layer Strategy for Linked Data Investigations

The Challenge A government organization sought to more effectively exploit their breadth of data generated by investigation activity of criminal networks for comprehensive case building and threat trend analysis. The agency struggled to meaningfully connect structured and unstructured data from multiple siloed data sources, each with misaligned naming conventions and inconsistent data structures and formats. Users had to have an existing understanding of underlying data models and jump between multiple system views to answer core investigation analysis questions, such as “What other drivers have been associated with this vehicle involved in an inspection at the border?” or “How often has this person in the network traveled to a known suspect storage location in the past 6 months?” These challenges manifest in data ambiguity across the organization, complex and resource-intensive integration workflows, and underutilized data assets lacking meaningful context, all resulting in significant cognitive load and burdensome manual efforts for users conducting intelligence analyses. The organization recognized the need to define a robust semantic layer solution grounded in data modeling, architecture frameworks, and governance controls to unify, contextualize, and operationalize data assets via a “single pane of intelligence” analysis platform. The Solution To address these challenges, EK engaged with the client to develop a strategy and product vision for their semantic solution, paired with foundational semantic data models for meaningful data categorization and linking, architecture designs and tool recommendations for integrating and leveraging graph data, and entitlements designs for adhering to complex security standards.