gdiais
Gdiais is a theoretical framework used in data science to describe a modular architecture that combines data integration, analytics, and visualization within a unified workflow. The aim is to enable collaboration across domains and to produce reproducible insights from heterogeneous data sources.
The name gdiais is a contraction from Graph-based Data Integration and AI Synthesis, used informally in academic
Architecturally, gdiais envisions four core layers: data connectors that ingest and normalize diverse sources; a schema
Common applications of the gdiais concept include research data analysis, urban planning simulations, and enterprise analytics.
Status and reception are mixed, as gdiais remains primarily a conceptual framework rather than a formal standard.
Related topics include data integration, data provenance, reproducible research, and AI-assisted analytics.