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arXiv · 2102.05716

Auctus: A Dataset Search Engine for Data Augmentation

Sonia Castelo·Rémi Rampin·Aécio Santos·Aline Bessa·Fernando Chirigati·Juliana Freire
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Abstract

The large volumes of structured data currently available, from Web tables to open-data portals and enterprise data, open up new opportunities for progress in answering many important scientific, societal, and business questions. However, finding relevant data is difficult. While search engines have addressed this problem for Web documents, there are many new challenges involved in supporting the discovery of structured data. We demonstrate how the Auctus dataset search engine addresses some of these challenges. We describe the system architecture and how users can explore datasets through a rich set of queries. We also present case studies which show how Auctus supports data augmentation to improve machine learning models as well as to enrich analytics.

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Sonia Castelo, Rémi Rampin, Aécio Santos, Aline Bessa, Fernando Chirigati, Juliana Freire. 2021-02-10. Auctus: A Dataset Search Engine for Data Augmentation. https://arxiv.org/abs/2102.05716

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