Abstract
Data scientists rely on visualizations to interpret the data returned by queries, butnding the right visualization remains amanual task that is oen laborious. We propose aDBMS that partially automates the task of finding the right visualizations for a query. In a nutshell, given an input query Q, the new DBMS optimizer will explore not only the space of physical plans for Q, but also the space of possible visualizations for the results of Q. The output will comprise a recommendation of potentially "interesting" or "useful" visualizations, where each visualization is coupled with a suitable query execution plan. We discuss the technical challenges in building this system and outline an agenda for future research.
Original language | English (US) |
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Pages (from-to) | 325-328 |
Number of pages | 4 |
Journal | Proceedings of the VLDB Endowment |
Volume | 7 |
Issue number | 4 |
DOIs | |
State | Published - Dec 2013 |
Externally published | Yes |
Event | Proceedings of the 40th International Conference on Very Large Data Bases, VLDB 2014 - Hangzhou, China Duration: Sep 1 2014 → Sep 5 2014 |
ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Computer Science(all)