Add anonymized benchmark datasets and constraint suites for paper evaluation

README.md

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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
+---
+
+# GraphGuard Benchmark Suite (Anonymized Submission)
+
+This repository contains the complete cross-paradigm benchmark suites, schemas, constraints, and data instances for **GraphGuard**, 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**.
+- **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_*`).
+- **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.

constraints.zip

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dblp_raw.zip

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graph_benchmarks.zip

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ldbc_scales.zip

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manifest.json

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+  "repository": "graphguard-benchmarks",
+  "description": "Anonymized GraphGuard benchmark and constraint artifacts",
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