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TsQuality: Measuring Time Series Data Quality in Apache IoTDB

Summary: TsQuality measures time-series data quality in Apache IoTDB at scale, implementing four metrics—completeness, consistency, timeliness, validity—as in-DB functions or Spark operators. Provides multi-granularity dirty-point navigation and integrates with Zeppelin/Superset for SQL-driven inspection and dashboards over millions of series. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13245
Venue
VLDB
Year
2023
Pagerank
4.427232e-05
Overall Rank
8,912 | 38.01%
DOI
10.14778/3611540.3611601

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
10,867 T-Assess: An Efficient Data Quality Assessment System Tailored for Trajectory Data 2025 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

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

Rank Cited Paper Year Venue Pagerank
3,825 Cleanits: A Data Cleaning System for Industrial Time Series 2019 VLDB 6.7255837e-05
3,967 Apache IoTDB: A Time Series Database for IoT Applications 2023 SIGMOD 6.5796647e-05
7,391 Time Series Data Validity 2023 SIGMOD 4.7429293e-05
9,048 On Repairing Timestamps for Regular Interval Time Series 2022 VLDB 4.4039656e-05
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