FIREFly: Formal Interactive Rich Explanations on the Fly

Sudeepa Roy

Funding       Overview       Publications     Students

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Funding

NSF CAREER Award #1552538: "CAREER: FIREFLY - Rich Explanations for Database Queries"

Overview

The recent popularity of Big Data has inspired a range of users to seek high level explanations for trends and anomalies
in different applications. Such a user will typically run some queries on the datasets, compute some aggregates,
plot the answers as a graph, and look for explanations for what she observes: "Why are two graphs similar/different?"
"Why is a sequence of points increasing/decreasing?" "Why is there a sudden spike or dip in a graph" etc. The FireFly project
aims to introduce a fresh perspective to data analysis and help users understand query results with fast, rich, insightful explanations.

Publications

1. Putting Things into Context: Rich Explanations for Query Answers using Join Graphs. [arxiv].
       (with Chenjie Li, Zhengjie Miao, Qitian Zeng, and Boris Glavic)
       Accepted in ACM SIGMOD International Conference on Management of Data (SIGMOD), 2021.
   
   
2. Properties of Inconsistency Measures for Databases.
       (with Ester Livshits, Rina Kochirgan, Segev Tsur, Ihab Ilyas, and Benny Kimelfeld)
       Accepted in ACM SIGMOD International Conference on Management of Data (SIGMOD), 2021.
   
   
3. I-Rex: An Interactive Relational Query Explainer for SQL.
       (with Zhengjie Miao, Tiangang Chen, Alexander Bendeck, Kevin Day, and Jun Yang)
       To appear in Proceedings of the VLDB Endowment (PVLDB), Vol 13, demonstration track, 2020.
   
   
4. MuSe: Multiple Deletion Semantics for Data Repair.
       (with Amir Gilad, Yihao Hu, and Daniel Deutch)
       To appear in Proceedings of the VLDB Endowment (PVLDB), Vol 13, demonstration track, 2020.
   
   
5. On Multiple Semantics for Declarative Database Repairs [pdf] [arxiv].
       (with Amir Gilad and Daniel Deutch)
       To appear in ACM SIGMOD International Conference on Management of Data (SIGMOD), 2020.
   
   
6. Computing Local Sensitivities of Counting Queries with Joins [pdf] [arxiv].
       (with Yuchao Tao, Xi He, and Ashwin Machanavajjhala)
       To appear in ACM SIGMOD International Conference on Management of Data (SIGMOD), 2020.
   
   
7. Learning to Sample: Counting with Complex Queries [arxiv].
       (with Brett Walenz, Stavros Sintos, and Jun Yang)
       Proceedings of the VLDB Endowment (PVLDB), Vol 13, 2019.
   
   
8. Going Beyond Provenance: Explaining Query Answers with Pattern-based Counterbalances [pdf].
       (with Zhengjie Miao, Qitian Zeng, and Boris Glavic)
       ACM SIGMOD International Conference on Management of Data (SIGMOD), 2019.
   
   
9. Explaining Wrong Queries Using Small Examples [pdf].
       (with Zhengjie Miao and Jun Yang)
       ACM SIGMOD International Conference on Management of Data (SIGMOD), 2019.
   
   
10. iQCAR: inter-Query Contention Analyzer for Data Analytics Frameworks [pdf].
        (with Prajakta Kalmegh and Shivnath Babu)
        ACM SIGMOD International Conference on Management of Data (SIGMOD), 2019.
    
    
11. RATest: Explaining Wrong Queries Using Small Examples [pdf].
        (with Zhengjie Miao and Jun Yang)
        ACM SIGMOD International Conference on Management of Data (SIGMOD), 2019, demonstration track.
    
    
12. CAPE: Explaining Outliers by Counterbalancing [pdf].
        (with Zhengjie Miao, Qitian Zeng, ChenjieLi, Boris Glavic, and Oliver Kennedy)
        Proceedings of the VLDB Endowment (PVLDB) Vol 11 2019/VLDB 2019.
    
    
13. LensXPlain: Visualizing and Explaining Contributing Subsets for Aggregate Query Answers [pdf].
        (with Zhengjie Miao and Andrew Lee)
        Proceedings of the VLDB Endowment (PVLDB) Vol 11 2019/VLDB 2019.
    
    
14. Interactive Summarization and Exploration of Top Aggregate Query Answers [pdf].
        (with Yuhao Wen, Xiaodan Zhu, and Jun Yang)
        Proceedings of the VLDB Endowment (PVLDB) Vol 11 2018/VLDB 2019.
    
    
15. iQCAR: Inter-Query Contention Analyzer [pdf].
        (with Prajakta Kalmegh and Shivnath Babu)
        Symposium on Cloud Computing (SOCC) 2018, Poster.
    
    
16. Computing Optimal Repairs for Functional Dependencies [arxiv].
        (with Ester Livshits and Benny Kimelfeld)
        Principles of Database Systems (PODS) 2018.
    
    
17. iQCAR: A Demonstration of an Inter-query Contention Analyzer for Cluster Computing Frameworks [pdf].
        (with Prajakta Kalmegh, Harrison Lundberg, Frederick Xu, and Shivnath Babu)
        ACM SIGMOD International Conference on Management of Data (SIGMOD), demonstration track, 2018.
    
    
18. QAGView: Interactively Summarizing High-Valued Aggregate Query Answers [pdf].
        (with Yuhao Wen, Xiaodan Zhu, and Jun Yang)
        ACM SIGMOD International Conference on Management of Data (SIGMOD), demonstration track, 2018.
    
    
19. Explaining Query Answers with Explanation-Ready Databases [pdf].
        (with Laurel Orr and Dan Suciu)
        Proceedings of the VLDB Endowment (PVLDB) Vol 9 2015/VLDB 2016
    
    
20. Tutorial: Causality and Explanations in Databases [pdf] [slides].
        (with Alexandra Meliou and Dan Suciu)
        International Conference on Very Large Data Bases (VLDB) 2014.
    
    
21. A Formal Approach to Finding Explanations for Database Queries [pdf] [slides].
        (with Dan Suciu)
        ACM SIGMOD International Conference on Management of Data (SIGMOD) 2014.
    
    

Students

Current Members

• Zhengjie Miao (PhD)

Past Members

• Prajakta Kalmegh (PhD, 2019)
• Shweta Patwa (PhD)
• Kehan Lyu (MS, 2020)
• Yuhao Wen (MS, 2019)
• Andrew Lee (MS, 2018)
• Xiaodan Zhu (MS, 2016)

Last updated on May 27, 2020.