Nexus: Correlation Discovery over Collections of Spatio-Temporal Tabular Data
Summary: Nexus aligns heterogeneous spatio-temporal tabular datasets in a large repository to support exploratory correlation discovery as a precursor to causal analysis. Key novelty: robust cross-dataset space/time alignment with missing-data handling plus ranking of “interesting” correlations, validated on Chicago open data and UN datasets. (summarized by gpt-5.4-mini on May 24 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,644 | Fair and Actionable Causal Prescription Ruleset | 2025 | SIGMOD | 4.3067693e-05 |
| 9,928 | Fainder: A Fast and Accurate Index for Distribution-Aware Dataset Search | 2024 | VLDB | 4.2470891e-05 |
| 10,197 | Qualitative Join Discovery in Data Lakes using Examples | 2026 | SIGMOD | 4.1905499e-05 |
| 10,353 | A Theoretical Framework for Distribution-Aware Dataset Search | 2025 | PODS | 4.1905499e-05 |
| 10,732 | Suna: Scalable Causal Confounder Discovery over Relational Data | 2025 | VLDB | 4.1905499e-05 |
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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.
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,147 | Causal Explanations for Disparate Trends: Where and Why? | 2026 | SIGMOD | 4.1905499e-05 |
| 814 | Finding Related Tables | 2012 | SIGMOD | 0.00016298739 |
| 5,538 | Data-Driven Domain Discovery for Structured Datasets | 2020 | VLDB | 5.4520759e-05 |
| 3,827 | Correlation Sketches for Approximate Join-Correlation Queries | 2021 | SIGMOD | 6.7195959e-05 |
| 2,111 | Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets | 2016 | SIGMOD | 9.5276068e-05 |
| 1,454 | Causal Relational Learning | 2020 | SIGMOD | 0.00011921443 |
| 6,445 | Causal Data Integration | 2023 | VLDB | 5.0539192e-05 |
| 6,565 | Toward Interpretable and Actionable Data Analysis with Explanations and Causality | 2022 | VLDB | 5.0033542e-05 |
| 8,751 | Multivariate Correlations Discovery in Static and Streaming Data | 2022 | VLDB | 4.4520434e-05 |
| 906 | Fusing Data with Correlations | 2014 | SIGMOD | 0.00015420344 |