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license: apache-2.0
task_categories:
- graph-machine-learning
- relational-databases
- knowledge-graphs
tags:
- database-integrity
- automated-reasoning
- first-order-logic
- craig-interpolation
- formal-verification
- sigmod-reproducibility
size_categories:
- 10GB<n<100GB
---
# UpdateGuard Benchmark Suite (Anonymized Submission)
This repository contains the complete cross-paradigm benchmark suites, schemas, constraints, and data instances for **UpdateGuard**, an automated first-order theorem proving and Craig interpolation framework for database integrity verification.
## Repository Contents
The repository is modularly structured into tier-based packages:
### 1. Constraints Suite (`constraints.zip` ~0.5 MB)
Contains all integrity constraints evaluated across the three paradigms:
- **Property Graphs:** Mined and hand-crafted Graph Generating Dependencies (GGDs) for **CORDIS**, **DBLP**, **GDELT**, and **LDBC SNB**, alongside property-level constraints: Graph Object Functional Dependencies (GO-FDs) for **Northwind**, graph functional/uniqueness dependencies (gFDs/gUCs) for **Offshore Leaks**, and graph functional dependencies and keys for **London Public Transport (LPT)** and **Train Services (TS)**.
- **RDF Knowledge Graphs:** W3C SHACL shape schemas and OWL ontologies for **LUBM** and **WatDiv**.
- **Relational Schemas:** Relational dependencies (foreign keys, uniqueness EGDs, check constraints) for **TPC-H** and all **ChaseBench** scenarios (`doctors`, `doctors-fd`, `LUBM`, `Ontology-256`, `STB-128`, `deep`, and `correctness` suites).
### 2. Standard Evaluation Benchmarks (`graph_benchmarks.zip`, `rdf_benchmarks.zip`, `relational_benchmarks.zip`)
- **Property Graphs (`graph_benchmarks.zip`):** Ready-to-evaluate node and edge CSV files for Neo4j and localized r-hop neighborhood extraction (`cordis_small`, `dblp_small`, `gdelt_small`, `ldbc_small_*`, `northwind`, `offshore_small`, `lpt`, `trains`).
- **RDF Knowledge Graphs (`rdf_benchmarks.zip`):** LUBM multi-university instances (1 to 15 universities in OWL/RDF), WatDiv 100k triple sample (`watdiv_100k.nt`), and UBA synthetic data generator.
- **Relational Databases (`relational_benchmarks.zip`):** ChaseBench relational scenarios with tables, schemas, queries, and repair tools, alongside TPC-H decision-support tables at scale factors 0.01 to 0.1.
### 3. Full-Scale Datasets (Optional, for heavy data scaling)
- `ldbc_scales.zip`: LDBC SNB SF 1 and SF 3 instances.
- `watdiv_10m.zip`: WatDiv full 10M triples dataset (`watdiv.10M.nt`).
- `dblp_raw.zip`: Complete DBLP publication XML database (`dblp.xml`, `dblp.dtd`).
- `tpch_scales.zip`: TPC-H tables at SF 0.3, SF 1, SF 3, and SF 10.
---
## Quick Download & Setup
You can download and extract these datasets directly into the codebase using the automated downloader script:
```bash
# Download standard evaluation bundle (constraints + benchmark datasets):
python scripts/download_benchmarks.py
# Download only constraints (ultra-lightweight, ~300 KB):
python scripts/download_benchmarks.py --constraints-only
# Download specific datasets:
python scripts/download_benchmarks.py --dataset ldbc cordis
```
All archives extract into the `datasets/` root directory, maintaining the exact folder paths expected by the evaluation pipelines (`run_all_benchmarks.py`, `run_eval.sh`, `run_chasebench_eval.sh`, and `run_lubm_scaling.sh`).
---
## Double-Blind Anonymity Compliance
This repository and its contents are fully anonymized for double-blind peer review. All local paths, personal metadata, and author identifications have been scrubbed in accordance with SIGMOD review guidelines.
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