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Charlie Fang

dblp:116/5201 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2012
—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 integration and cleaning · 100%

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

TopicWeightPapersLastEvidence papers
Data integration and cleaning
data-driven workflows		 0.112012
Provenance-Based Debugging and Drill-Down in Data-Oriented Workflows · ICDE 2012
Data integration and cleaning
data provenance		 0.112012
Provenance-Based Debugging and Drill-Down in Data-Oriented Workflows · ICDE 2012

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

provenance tracing · 0.1
YearPublicationVenuePosition
2012 Provenance-Based Debugging and Drill-Down in Data-Oriented Workflows
abstract
Panda (for Provenance and Data), a system for data-oriented workflows that supports debugging and drill-down using logical provenance-provenance information stored at the processing-node level is demonstrated. In this demonstration, Panda is used to integrate, process, and analyze actual education data from multiple sources.
Robert Ikeda, Junsang Cho, Charlie Fang, Semih Salihoglu, Satoshi Torikai, Jennifer Widom
 ICDE3