Update READM for version v1.0.1

README.md

@@ -24,9 +24,9 @@ Each file in the dataset has a SHA-256 checksum to verify its integrity:
 
 | File Name                  | SHA-256 Checksum                                                          |
 |----------------------------|---------------------------------------------------------------------------|
-| `graph.cypher`             | `9159a04d385ccbd53858eaf21f4f80c9ce17b52ff997c410400ecc085bfbe010`        |
-| `graph.graphml`            | `2ca75302371f6be9fee1a051948144ba26147c1eebaea1e7a00dd1eb86ba2031`        |
-| `graph.json`               | `1dbeef75206edc3f893819589461b2a2ed9c1a14311dcc8aca304fb58c005ca1`        |
+| `graph.cypher`             | `d78f7b166a86be3ceec16db75a1575dac95249af188b1d2e2adab7388a8e654a`        |
+| `graph.graphml`            | `a781e358b338a181db5081a50127325febab67dcb283cb4124c877bf06de439e`        |
+| `graph.json`               | `4794fd070953b3544ba3c841f13155f1cf8a1ca9abd1b240bbfaf482ce2cde32`        |
 
 ### Verification
 
@@ -181,23 +181,38 @@ The knowledge graph includes several relationship types that define how nodes ar
 
 ## Statistics
 
-- **Total Nodes**: **135,764**
-  - **Publication**: 125,939
-  - **Dataset**: 6,390
-  - **ScienceKeyword**: 1,609
-  - **Instrument**: 867
-  - **Platform**: 442
-  - **Project**: 333
-  - **DataCenter**: 184
-- **Total Relationships**: **344,525**
-  - **CITES**: 208,670
-  - **HAS_APPLIED_RESEARCH_AREA**: 89,039
-  - **HAS_SCIENCEKEYWORD**: 20,436
-  - **HAS_PLATFORM**: 9,884
-  - **HAS_DATASET**: 9,017
-  - **OF_PROJECT**: 6,049
-  - **HAS_INSTRUMENT**: 2,469
-  - **HAS_SUBCATEGORY**: *(Count not provided)*
+# Data Statistics
+
+## Total Counts
+| Type                 | Count   |
+|----------------------|---------|
+| **Total Nodes**      | 135,764 |
+| **Total Relationships** | 365,857 |
+
+## Node Label Counts
+| Node Label        | Count    |
+|-------------------|----------|
+| Dataset           | 6,390    |
+| DataCenter        | 184      |
+| Project           | 333      |
+| Platform          | 442      |
+| Instrument        | 867      |
+| ScienceKeyword    | 1,609    |
+| Publication       | 125,939  |
+
+## Relationship Label Counts
+| Relationship Label        | Count     |
+|---------------------------|-----------|
+| HAS_DATASET              | 9,017     |
+| OF_PROJECT               | 6,049     |
+| HAS_PLATFORM             | 9,884     |
+| HAS_INSTRUMENT           | 2,469     |
+| HAS_SUBCATEGORY          | 1,823     |
+| HAS_SCIENCEKEYWORD       | 20,436    |
+| CITES                    | 208,670   |
+| HAS_APPLIED_RESEARCH_AREA| 89,039    |
+| USES_DATASET             | 18,470    |
+
 
 ## Data Formats
 
@@ -211,12 +226,140 @@ The Knowledge Graph Dataset is available in three formats:
 
 #### Loading the JSON Format
 
-To load the JSON file into a graph database that supports Cypher and the APOC library, use the following command:
+To load the JSON file into a graph database using Python and multiprocessing you can using the following script:
+
+```python
+import json
+from tqdm import tqdm
+from collections import defaultdict
+from multiprocessing import Pool, cpu_count
+from neo4j import GraphDatabase
+
+# Batch size for processing
+BATCH_SIZE = 100
+
+# Neo4j credentials (replace with environment variables or placeholders)
+NEO4J_URI = "bolt://<your-neo4j-host>:<port>"  # e.g., "bolt://localhost:7687"
+NEO4J_USER = "<your-username>"
+NEO4J_PASSWORD = "<your-password>"
+
+
+def ingest_data(file_path):
+    # Initialize counters and label trackers
+    node_label_counts = defaultdict(int)
+    relationship_label_counts = defaultdict(int)
+    node_count = 0
+    relationship_count = 0
+
+    with open(file_path, "r") as f:
+        nodes = []
+        relationships = []
+
+        # Read and categorize nodes and relationships, and count labels
+        for line in tqdm(f, desc="Reading JSON Lines"):
+            obj = json.loads(line.strip())
+            if obj["type"] == "node":
+                nodes.append(obj)
+                node_count += 1
+                for label in obj["labels"]:
+                    node_label_counts[label] += 1
+            elif obj["type"] == "relationship":
+                relationships.append(obj)
+                relationship_count += 1
+                relationship_label_counts[obj["label"]] += 1
+
+    # Print statistics
+    print("\n=== Data Statistics ===")
+    print(f"Total Nodes: {node_count}")
+    print(f"Total Relationships: {relationship_count}")
+    print("\nNode Label Counts:")
+    for label, count in node_label_counts.items():
+        print(f"  {label}: {count}")
+    print("\nRelationship Label Counts:")
+    for label, count in relationship_label_counts.items():
+        print(f"  {label}: {count}")
+    print("=======================")
+
+    # Multiprocess node ingestion
+    print("Starting Node Ingestion...")
+    node_batches = [nodes[i : i + BATCH_SIZE] for i in range(0, len(nodes), BATCH_SIZE)]
+    with Pool(processes=cpu_count()) as pool:
+        list(
+            tqdm(
+                pool.imap(ingest_nodes_batch, node_batches),
+                total=len(node_batches),
+                desc="Ingesting Nodes",
+            )
+        )
+
+    # Multiprocess relationship ingestion
+    print("Starting Relationship Ingestion...")
+    relationship_batches = [
+        relationships[i : i + BATCH_SIZE]
+        for i in range(0, len(relationships), BATCH_SIZE)
+    ]
+    with Pool(processes=cpu_count()) as pool:
+        list(
+            tqdm(
+                pool.imap(ingest_relationships_batch, relationship_batches),
+                total=len(relationship_batches),
+                desc="Ingesting Relationships",
+            )
+        )
+
+
+def ingest_nodes_batch(batch):
+    with GraphDatabase.driver(NEO4J_URI, auth=(NEO4J_USER, NEO4J_PASSWORD)) as driver:
+        with driver.session() as session:
+            for node in batch:
+                try:
+                    label = node["labels"][0]  # Assumes a single label per node
+                    query = f"""
+                    MERGE (n:{label} {{globalId: $globalId}})
+                    SET n += $properties
+                    """
+                    session.run(
+                        query,
+                        globalId=node["properties"]["globalId"],
+                        properties=node["properties"],
+                    )
+                except Exception as e:
+                    print(
+                        f"Error ingesting node with globalId {node['properties']['globalId']}: {e}"
+                    )
+
+
+def ingest_relationships_batch(batch):
+    with GraphDatabase.driver(NEO4J_URI, auth=(NEO4J_USER, NEO4J_PASSWORD)) as driver:
+        with driver.session() as session:
+            for relationship in batch:
+                try:
+                    rel_type = relationship[
+                        "label"
+                    ]  # Use the label for the relationship
+                    query = f"""
+                    MATCH (start {{globalId: $start_globalId}})
+                    MATCH (end {{globalId: $end_globalId}})
+                    MERGE (start)-[r:{rel_type}]->(end)
+                    """
+                    session.run(
+                        query,
+                        start_globalId=relationship["start"]["properties"]["globalId"],
+                        end_globalId=relationship["end"]["properties"]["globalId"],
+                    )
+                except Exception as e:
+                    print(
+                        f"Error ingesting relationship with label {relationship['label']}: {e}"
+                    )
+
+
+if __name__ == "__main__":
+    # Path to the JSON file
+    JSON_FILE_PATH = "<path-to-your-graph.json>"
+
+    # Run the ingestion process
+    ingest_data(JSON_FILE_PATH)
 
-```cypher
-CALL apoc.load.json("path/to/graph.json") YIELD value
-MERGE (n {id: value.id, label: value.label})
-SET n += value.properties
 ```
 
 ### 2. GraphML
@@ -360,7 +503,7 @@ Please cite the dataset as follows:
 ```bibtex
 @misc {nasa_goddard_earth_sciences_data_and_information_services_center__(ges-disc)_2024,
     author       = { {NASA Goddard Earth Sciences Data and Information Services Center (GES-DISC)} },
-    title        = { nasa-eo-knowledge-graph (Revision b8f650e) },
+    title        = { nasa-eo-knowledge-graph },
     year         = 2024,
     url          = { https://huggingface.co/datasets/nasa-gesdisc/nasa-eo-knowledge-graph },
     doi          = { 10.57967/hf/3463 },