TY - JOUR
T1 - Auctus
T2 - 47th International Conference on Very Large Data Bases, VLDB 2021
AU - Castelo, Sonia
AU - Rampin, Rémi
AU - Santos, Aécio
AU - Bessa, Aline
AU - Chirigati, Fernando
AU - Freire, Juliana
N1 - Funding Information:
This work was partially supported by the DARPA D3M program and NSF award OAC-1640864. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of NSF and DARPA.
Publisher Copyright:
© The authors.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85113860489&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85113860489&partnerID=8YFLogxK
U2 - 10.14778/3476311.3476346
DO - 10.14778/3476311.3476346
M3 - Conference article
AN - SCOPUS:85113860489
SN - 2150-8097
VL - 14
SP - 2791
EP - 2794
JO - Proceedings of the VLDB Endowment
JF - Proceedings of the VLDB Endowment
IS - 12
Y2 - 16 August 2021 through 20 August 2021
ER -