Overview
The Hypergraphx-data repository provides real-world hypergraph datasets designed for higher-order network analysis. This repository supports diverse configurations, encompassing weighted, directed, temporal, and multiplex hypergraphs, and spans a range of domains from social networks to biology and finance. Each dataset includes relational information and associated metadata, offered in both an open JSON format and a binarized format specifically for Hypergraphx.
Research Context
The availability of network datasets is essential for advancing research in network science, machine learning, and related fields. Such datasets enable empirical analyses and their reproducibility, facilitate algorithm development, and support model validation and benchmarking processes. Existing repositories, including SNAP and Netzschleuder, have made traditional network datasets accessible, often alongside metadata, metrics, and basic visualizations. However, these repositories primarily focus on pairwise interactions. This focus limits data access for systems that involve many-body interactions.
Approach
To address the identified gap in data accessibility for systems with many-body interactions, the Hypergraphx-data repository was developed. The repository was constructed to specifically host real-world hypergraph datasets, supporting higher-order network analysis. Datasets within Hypergraphx-data are characterized by relational information and comprehensive metadata. These data elements are provided in two formats: an open JSON format and a binarized format compatible with Hypergraphx.
The repository incorporates features to enhance user interaction and data integrity. It offers a user-friendly interface designed for browsing, filtering, and accessing the stored datasets. Furthermore, Hypergraphx-data ensures data integrity and reproducibility through the implementation of hash-based verification and data versioning.
Findings
- Hypergraphx-data provides a collection of real-world hypergraph datasets.
- The datasets facilitate higher-order network analysis.
- The repository includes datasets from social networks, biology, and finance domains.
- Supported hypergraph configurations include weighted, directed, temporal, and multiplex hypergraphs.
- Each dataset contains relational information and metadata.
- Data is provided in an open JSON format.
- Data is also provided in a binarized format for Hypergraphx.
- A user-friendly interface supports browsing, filtering, and accessing datasets.
- Hash-based verification and data versioning are implemented for integrity and reproducibility.
Why This Matters
The provision of hypergraph datasets through Hypergraphx-data directly supports empirical analyses and their reproducibility in fields relying on network data. This resource aids in the development of algorithms specifically designed for higher-order network structures and contributes to the validation and benchmarking of related models. By addressing the previous limitation of data access for systems with many-body interactions, the repository helps advance research beyond pairwise interaction models across multiple scientific and engineering domains.