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Collaborative Data Science using Scalable Homoiconicity

Published: 25 January 2023 Publication History

Abstract

Motivation: Data science is increasingly collaborative. On the one hand, results need to be distributed, e.g., as interactive visualizations. On the other, collaboration in the data development process improves quality and timeliness. This can take many forms: partitioning a problem and working on aspects in parallel, exploring different solutions or reviewing someone else's work.

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Published In

cover image ACM SIGMOD Record
ACM SIGMOD Record  Volume 51, Issue 4
December 2022
73 pages
ISSN:0163-5808
DOI:10.1145/3582302
Issue’s Table of Contents
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 January 2023
Published in SIGMOD Volume 51, Issue 4

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