Knowledge Graphs

Definition

Knowledge Graphs examines knowledge graphs within the broader domain of how knowledge is captured, connected, verified, reused and translated into action.

Why this matters

Knowledge Graphs can materially affect human agency, capability, belonging, livelihoods, culture, trust, resilience and long-term societal outcomes.

Research questions

Under which conditions does knowledge graphs improve human and system outcomes, how do effects vary across populations and contexts, and what safeguards prevent dependency, exclusion, distortion or loss of agency?

Hypotheses

A transparent, participatory and human-directed approach to knowledge graphs, with explicit safeguards and longitudinal evaluation, will improve retrieval accuracy; provenance completeness; reuse; context retention; decay; decision quality; time-to-action compared with opaque, automation-first or short-term approaches.

Proposed methods

knowledge graph analysis; provenance audit; retrieval testing; organisational ethnography; decay measurement; decision-use studies; literature and policy review; expert and affected-user interviews; reproducibility testing; methods adapted specifically to Knowledge Graphs

Stakeholders and beneficiaries

creators; cultural custodians; communities; educators; researchers; publishers; platforms; collecting societies; libraries; archives; museums; regulators; funders