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README.md

@@ -210,10 +210,44 @@ Cross-ontology links discovered via shared external IDs (UMLS, Wikidata, MESH, e
 
 ## Usage with DuckDB
 
+### Option 1: Pre-built database file (recommended)
+
+This repository includes a ready-to-use DuckDB database file (`datalake.duckdb`, 274 KB) with 145 SQL views pre-configured to read directly from HuggingFace. Download just this one file and query all 7 datasets immediately — no pipeline setup required.
+
+```python
+import duckdb
+
+con = duckdb.connect()
+con.execute("INSTALL httpfs; LOAD httpfs;")
+con.execute("ATTACH 'hf://datasets/J0nasW/science-datalake/datalake.duckdb' AS lake")
+
+# Query using familiar schema.table syntax
+df = con.execute("""
+    SELECT doi, title, year, sciscinet_disruption, oa_cited_by_count
+    FROM lake.xref.unified_papers
+    WHERE sciscinet_disruption IS NOT NULL
+    ORDER BY sciscinet_disruption DESC
+    LIMIT 100
+""").df()
+
+# Cross-source joins work out of the box
+con.execute("""
+    SELECT t.display_name AS topic, o.ontology, o.term_name, o.similarity
+    FROM lake.xref.topic_ontology_map o
+    JOIN lake.openalex.topics t ON t.id = o.topic_id
+    WHERE o.similarity >= 0.85
+    ORDER BY o.similarity DESC
+    LIMIT 20
+""").df()
+```
+
+### Option 2: Direct Parquet queries
+
+You can also query individual Parquet files directly without the database file:
+
 ```python
 import duckdb
 
-# Query directly from HuggingFace
 con = duckdb.connect()
 con.execute("INSTALL httpfs; LOAD httpfs;")