CODBDMMar 24

Knowledge management in House of Graphs

arXiv:2603.2307043.01 citationsh-index: 18
AI Analysis

This work addresses data management challenges for researchers and users relying on the House of Graphs as a scientific repository, but it is incremental as it describes improvements to an existing system.

The authors tackled the problem of ensuring data reliability and consistency in the House of Graphs, an online database of graphs, by focusing on knowledge management to maintain coherent, qualitative, and stable data.

The House of Graphs is an online database of graphs which can be accessed at https://houseofgraphs.org/. It serves as a central repository for complete lists of graphs for various graph classes. However, its main feature is a searchable database of so-called "interesting" graphs. The development of the original House of Graphs started in 2010 and it was completely rebuilt in 2021-2022. Each graph in the database is accompanied by a significant amount of meta-data such as a name, drawings, precomputed graph invariants, and comments. Given this volume of information and the importance of reliability in the scientific world, robust data management is essential to ensure accuracy and consistency across the database. In this article, we therefore focus on knowledge management in the House of Graphs and describe the inner workings of the House of Graphs and how we ensure that its data is coherent, qualitative and stable.

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