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Bofan Sun

dblp:166/8388 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Data models and query languages · 56% Database system architecture and tuning · 44%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Data models and query languages
tabular data management
0.212015
DATASPREAD: Unifying Databases and Spreadsheets · Proc. VLDB Endow. 2015
Data models and query languages › SQL
SQL query
0.112015
DATASPREAD: Unifying Databases and Spreadsheets · Proc. VLDB Endow. 2015

Methods — techniques the papers use, named apart from their topics

spreadsheet front-end · 0.2PostgreSQL back-end · 0.2
YearPublicationVenuePosition
2015 DATASPREAD: Unifying Databases and Spreadsheets
abstract
Spreadsheet software is often the tool of choice for ad-hoc tabular data management, processing, and visualization, especially on tiny data sets. On the other hand, relational database systems offer significant power, expressivity, and efficiency over spreadsheet software for data management, while lacking in the ease of use and ad-hoc analysis capabilities. We demonstrate D ata S pread , a data exploration tool that holistically unifies databases and spreadsheets. It continues to offer a Microsoft Excel-based spreadsheet front-end, while in parallel managing all the data in a back-end database, specifically, PostgreSQL. D ata S pread retains all the advantages of spreadsheets, including ease of use, ad-hoc analysis and visualization capabilities, and a schema-free nature, while also adding the advantages of traditional relational databases, such as scalability and the ability to use arbitrary SQL to import, filter, or join external or internal tables and have the results appear in the spreadsheet. D ata S pread needs to reason about and reconcile differences in the notions of schema, addressing of cells and tuples, and the current "pane" (which exists in spreadsheets but not in traditional databases), and support data modifications at both the front-end and the back-end. Our demonstration will center on our first and early prototype of the D ata S pread , and will give the attendees a sense for the enormous data exploration capabilities offered by unifying spreadsheets and databases.
Mangesh Bendre, Bofan Sun, Kevin Chen-Chuan Chang, Aditya G. Parameswaran
Proc. VLDB Endow.2