oc-graphenricher 1.0.1

A tool to enrich any OCDM compliant Knowledge Graph, finding new identifiers and deduplicating entities

OC GraphEnricher

OC GraphEnricher enriches OpenCitations Data Model (OCDM) compliant knowledge graphs by finding missing identifiers and deduplicating entities.

Documentation: https://opencitations.github.io/oc_graphenricher/

Quick start

pip install oc-graphenricher

from oc_ocdm.graph.graph_set import GraphSet
from oc_ocdm.reader import Reader
from rdflib import Graph

from oc_graphenricher.enricher import GraphEnricher
from oc_graphenricher.instancematching import InstanceMatching
from oc_graphenricher.storage import single_file_storage

graph = Graph().parse("data/input.nt", format="nt11")

reader = Reader()
graph_set = GraphSet(base_iri="https://w3id.org/oc/meta/")
reader.import_entities_from_graph(
    graph_set,
    graph,
    enable_validation=False,
    resp_agent="https://w3id.org/oc/meta/prov/pa/2",
)

GraphEnricher(
    g_set=graph_set,
    storage=single_file_storage(
        graph_path="enriched.json",
        provenance_path="provenance.json",
    ),
).enrich()
InstanceMatching(
    g_set=graph_set,
    storage=single_file_storage(
        graph_path="matched.json",
        provenance_path="provenance.json",
    ),
).match()

By default, InstanceMatching does not merge contributor roles only because author names are similar. To enable that opt-in behavior, pass merge_similar_named_contributors=True.

For configuration options and usage details, see the documentation.

License

Distributed under the ISC License. See LICENSE.