Relationships are Complicated! An Analysis of Relationships Between Datasets on the Web

• URL: http://arxiv.org/abs/2408.14636v1
• Date: Mon, 26 Aug 2024 21:00:25 GMT
• Title: Relationships are Complicated! An Analysis of Relationships Between Datasets on the Web
• Authors: Kate Lin, Tarfah Alrashed, Natasha Noy,
• Abstract summary: We study dataset relationships from the perspective of users who discover, use, and share datasets on the Web. We first present a comprehensive taxonomy of relationships between datasets on the Web and map these relationships to user tasks performed during dataset discovery. We demonstrate that machine-learning based methods that use dataset metadata achieve multi-class classification accuracy of 90%.
• Score: 1.02801486034657
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The Web today has millions of datasets, and the number of datasets continues to grow at a rapid pace. These datasets are not standalone entities; rather, they are intricately connected through complex relationships. Semantic relationships between datasets provide critical insights for research and decision-making processes. In this paper, we study dataset relationships from the perspective of users who discover, use, and share datasets on the Web: what relationships are important for different tasks? What contextual information might users want to know? We first present a comprehensive taxonomy of relationships between datasets on the Web and map these relationships to user tasks performed during dataset discovery. We develop a series of methods to identify these relationships and compare their performance on a large corpus of datasets generated from Web pages with schema.org markup. We demonstrate that machine-learning based methods that use dataset metadata achieve multi-class classification accuracy of 90%. Finally, we highlight gaps in available semantic markup for datasets and discuss how incorporating comprehensive semantics can facilitate the identification of dataset relationships. By providing a comprehensive overview of dataset relationships at scale, this paper sets a benchmark for future research.

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