Loading...
Loading...
Social network graphs, knowledge graphs, citation networks, molecular graphs for GNN, web link graphs
322 datasets
A directory of the Department of Utility Resources in Ukraine, last updated on 2023-02-23. The dataset includes identification codes, official websites, email addresses, phone numbers, and physical addresses. It is provided by the States site of Ukraine and is available in an EXCEL XLSX format.
Open Graph Benchmark (OGB) is a collection of diverse benchmark datasets for graph machine learning developed by the SNAP group at Stanford University. Updated through May 2025, it provides standardized data loaders and evaluators for node, link, and graph-level prediction tasks across multiple domains.
1996-present vessel trip reports submitted by commercial and charter boat operators to the Greater Atlantic Regional Fisheries Office. The data is reported by vessel operators and covers fisheries in areas like Georges Bank. The National Oceanic and Atmospheric Administration provides this fishery-dependent information.
This repository provides a curated collection of graph datasets and research papers focusing on heterophily in Graph Neural Networks, maintained by alexfanjn and updated through December 2024. It serves as a central directory for benchmarking GNN models on graphs where connected nodes frequently belong to different classes.
EQTPartners released Companykg in June 2024 as a large-scale heterogeneous knowledge graph for the investment and private equity sector. It maps company relations to facilitate graph-based machine learning and industry benchmarking.
3,312 scientific publications categorized into six classes, interconnected by a citation network of 4,732 links. Each publication is represented by a 3,703-dimensional binary word vector indicating the presence or absence of specific dictionary terms.
2,708 scientific publications categorized into seven distinct classes, connected by a citation network of 5,429 links. Each entry includes a binary word vector representing the presence or absence of 1,433 unique dictionary terms.
A knowledge graph dataset focused on mathematics, published on the Hugging Face platform. The dataset was created by author mlo0ollm and was last updated on 2025-02-26. Its specific content, scale, and structure require verification after download.
Over 1,000 entities and relations representing the One Piece universe, categorized into characters, devil fruits, and locations. The data maps complex narrative connections through a graph structure to support semantic queries and lore analysis.
Illinois Graph Benchmark (IGB) is a collection of large-scale real-world graph datasets developed by the IBM-Illinois Discovery Accelerator Institute in collaboration with Amazon and NVIDIA. Updated in June 2025, it provides graph structures and node features specifically designed for benchmarking Graph Neural Network (GNN) performance. It is positioned as the largest open-source dataset of its kind for graph learning research.
Multiple datasets for knowledge graph completion featuring structured triples and corresponding textual descriptions for entities. The data facilitates the training of embedding models that leverage both graph topology and natural language semantics to predict missing links.
1 code repository containing implementation scripts for the ICLR 2021 paper 'Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective'. It provides the computational framework for evaluating the expressive power of graph neural networks through spectral filter analysis.
This collection organizes resources across 6 categories including graph processing systems, databases, data structures, datasets, and academic or industrial research. It maps the technical landscape of temporal and evolving graph technologies for streaming data applications.
bxshi released this repository in 2019 to support the ConMask model for open-world knowledge graph completion. It provides data and TensorFlow code for representation learning and network embedding, specifically targeting entities not seen during training.
1,835 gait sequences categorized into four emotion classes including Happy, Sad, Angry, and Neutral for affective computing research. The data consists of spatial-temporal graphs representing 16 skeletal joints across multiple frames of human walking to capture movement dynamics.
Trial Full Gnn is a dataset for testing Graph Neural Network models, uploaded by user KalElofKrypton to the Hugging Face platform. The dataset was last updated on July 15, 2022. Its specific contents and structure are not described.
Created by simonschoelly in 2021, Graphdatasets.Jl provides a programmatic interface for retrieving graph-structured data for classification and kernel analysis. The package facilitates the download of multiple graph datasets specifically formatted for use within the JuliaGraphs and LightGraphs.jl software ecosystems.
A dataset for testing Graph Neural Network models, uploaded by user KalElofKrypton to the Hugging Face platform. The dataset was last updated in July 2022. Specific details on the graph structure, node features, and edge types are not provided.
8 subgraph classification datasets including HPO-NEURO, HPO-METAB, and PPI-BP, designed to evaluate how neural networks capture subgraph topology. The collection includes subgraphs of varying sizes and connectivity patterns embedded within large base graphs representing biological and synthetic networks.
Maintained by wey-gu and updated in February 2025, this GitHub repository provides a curated collection of graph datasets specifically formatted for the NebulaGraph database. It serves as a community hub for graph-structured data, though specific record counts and schemas vary by individual dataset within the collection.