graphsacross

GraphsAcross is a conceptual framework for cross-graph analysis that studies relationships across multiple graphs sharing common entities. It provides methods and visualizations designed to compare structure, detect consistent patterns, and track changes across contexts or time.

At its core, GraphsAcross emphasizes aligning nodes across graphs (entity resolution) and establishing correspondences between edges. It supports calculating cross-graph metrics that summarize behavior over the set of graphs, such as cross-graph density, cross-graph centrality, and cross-graph community stability.

The data model represents each graph as a set of nodes and edges with optional attributes. After alignment, a cross-graph store keeps per-graph attributes and per-graph edge presence, enabling analyses at the per-graph, cross-graph, and per-entity level. Visualization approaches include synchronized views, small multiples, and interactive tracing of edges across graphs.

Applications span social network analysis, where networks from different platforms are compared; biology, by contrasting signaling or metabolic networks across species; transportation and infrastructure, by comparing networks across regions or time periods; and knowledge-graph integration, where entities appear in multiple sources.

Limitations include potential alignment errors, incomplete overlap of node identities, scalability issues for large graphs, and privacy or data integration concerns when combining multiple sources. As a methodological concept, GraphsAcross emphasizes careful data preparation and transparent interpretation of cross-graph results.