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DataTweener: A Demonstration of a Tweening Engine for Incremental Visualization of Data Transforms

Summary: DataTweener introduces “data tweening”: animated intermediate visual states that expose structural changes between successive query results. An automated diff-based framework decomposes query-session transitions into basic transforms and visual cues, validated by user study. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11683
Venue
VLDB
Year
2017
Pagerank
5.093636e-05
Overall Rank
12,015 | 17.57%
DOI
10.14778/3137765.3137801

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Authors

BibTeX Citation

@article{khan_vldb17,
        title = {{DataTweener: A Demonstration of a Tweening Engine for Incremental Visualization of Data Transforms}},
        author = {Khan, Meraj and Xu, Larry and Nandi, Arnab and Hellerstein, Joseph M.},
        journal = {PVLDB},
        series = {{VLDB} '17},
        volume = {10},
        number = {12},
        pages = {1953--1956},
        doi = {10.14778/3137765.3137801},
        url = {https://doi.org/10.14778/3137765.3137801},
        year = {2017}
}

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
2,559 dbTouch: Analytics at your Fingertips 2013 CIDR 8.4156672e-05
2,946 Gestural Query Specification 2014 VLDB 7.93259e-05
6,511 Data Tweening: Incremental Visualization of Data Transforms 2017 VLDB 5.8567275e-05
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