T-Assess: An Efficient Data Quality Assessment System Tailored for Trajectory Data

Summary: T-Assess: an automated, trajectory-specific data-quality assessment system defining comprehensive criteria (validity, completeness, consistency, fairness) and supporting both offline and real-time stream evaluations. Introduces evaluation optimizations for efficiency and demonstrates superior coverage and practical effectiveness versus general-purpose DQ tools on four real-world trajectory benchmarks. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 14415
Venue: VLDB
Year: 2025
Pagerank: 5.093636e-05
Overall Rank: 11,090 | 23.92%
DOI: 10.14778/3712221.3712233

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Junhao Zhu (Zhejiang University)
2. Tao Wang (Zhejiang University)
3. Danlei Hu (Zhejiang University)
4. Ziquan Fang (Zhejiang Key Laboratory of Big Data Intelligent Computing; Zhejiang University)
5. Lu Chen (Zhejiang Key Laboratory of Big Data Intelligent Computing; Zhejiang University)
6. Yunjun Gao (Zhejiang Key Laboratory of Big Data Intelligent Computing; Zhejiang University)
7. Tianyi Li (Aalborg University)
8. Christian S. Jensen (Aalborg University)

BibTeX Citation

@article{zhu_vldb25,
        title = {{T-Assess: An Efficient Data Quality Assessment System Tailored for Trajectory Data}},
        author = {Zhu, Junhao and Wang, Tao and Hu, Danlei and Fang, Ziquan and Chen, Lu and Gao, Yunjun and Li, Tianyi and Jensen, Christian S.},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {3},
        pages = {666--674},
        doi = {10.14778/3712221.3712233},
        url = {https://doi.org/10.14778/3712221.3712233},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
533	Improving Data Quality: Consistency and Accuracy	2007	VLDB	0.0001705859
1,350	Automating Large-Scale Data Quality Verification	2018	VLDB	0.00011065626
3,345	Effective Travel Time Estimation: When Historical Trajectories over Road Networks Matter	2020	SIGMOD	7.4975085e-05
3,630	TensorFlow Data Validation: Data Analysis and Validation in Continuous ML Pipelines	2020	SIGMOD	7.2387749e-05
3,849	Calibrating Trajectory Data for Similarity-based Analysis	2013	SIGMOD	7.0745507e-05
3,899	MDTP: A Multi-source Deep Traffic Prediction Framework over Spatio-Temporal Trajectory Data	2021	VLDB	7.0361711e-05
4,475	UlTraMan: A Unified Platform for Big Trajectory Data Management and Analytics	2018	VLDB	6.6803264e-05
7,314	Time Series Data Validity	2023	SIGMOD	5.6471526e-05
8,435	Spatial Data Quality in the IoT Era: Management and Exploitation	2022	SIGMOD	5.4253644e-05
8,734	Ghost: A General Framework for High-Performance Online Similarity Queries over Distributed Trajectory Streams	2023	SIGMOD	5.3766157e-05
9,065	R2D2: Reducing Redundancy and Duplication in Data Lakes	2023	SIGMOD	5.3251649e-05
9,066	TsQuality: Measuring Time Series Data Quality in Apache IoTDB	2023	VLDB	5.3251649e-05
9,069	DQDF: Data-Quality-Aware Dataframes	2022	VLDB	5.3251649e-05

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