{"url":"/dataset/color-connectivity","name":"Color-connectivity","full_name":null,"description_markdown":"Synthetic graph classification datasets with the task of recognizing the connectivity of same-colored nodes in 4 graphs of varying topology.\n\n* The four Color-connectivity datasets were created by taking a graph and randomly coloring half of its nodes one color, e.g., red, and the other nodes blue, such that the red nodes either form a single connected island or two disjoint islands.\n  The binary classification task is then distinguishing between these two cases.\n  The node colorings were sampled by running two red-coloring random walks starting from two random nodes.\n* For the underlying graph topology we used: 1) 16x16 2D grid, 2) 32x32 2D grid, 3) Euroroad road network (Šubelj et al. 2011), and 4) Minnesota road network.\n* We sampled a balanced set of 15,000 coloring examples for each graph, except for Minnesota network for which we generated 6,000 examples due to memory constraints.\n* The Color-connectivity task requires combination of local and long-range graph information processing to which most existing message-passing Graph Neural Networks (GNNs) do not scale.\n  These datasets can serve as a common-sense validation for new and more powerful GNN methods.\n  These testbed datasets can still be improved, as the node features are minimal (only a binary color) and recognition of particular topological patterns (e.g., rings or other subgraphs) is not needed to solve the task.","description_withheld":null,"homepage":"https://github.com/rampasek/HGNet","introduced_date":"2021-07-15","introduced_date_note":null,"introduced_by":{"paper":"/paper/hierarchical-graph-neural-nets-can-capture","title":"Hierarchical graph neural nets can capture long-range interactions","first_author":"Ladislav Rampášek","url":null},"license":{"name":"MIT","url":"https://github.com/rampasek/HGNet/blob/master/LICENSE"},"modalities":[{"name":"Graphs","url":"/datasets/modality/graphs"}],"tasks":[{"name":"Graph Classification","url":"/task/graph-classification","datasets_with_task":"/datasets/task/graph-classification"}],"languages":[],"variants":["Color-connectivity"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}