Auctus: A dataset search engine for data discovery and augmentation

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

Research output: Contribution to journalConference articlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)2791-2794
Number of pages4
JournalProceedings of the VLDB Endowment
Issue number12
StatePublished - 2021
Event47th International Conference on Very Large Data Bases, VLDB 2021 - Virtual, Online
Duration: Aug 16 2021Aug 20 2021

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • General Computer Science


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