Abstract:
The Semantic Web allows data to be shared and reused through
a mechanism of URIs and resource description. RDF, as a standard for
describing resources and data, models information in the form of subject-
predicate-object triples. This model can be viewed as a graph; subjects and
objects are vertices or nodes and are connected through predicates as edges
of the graph. Relational database systems are not e cient in processing Se-
mantic Web data. With the massive increase in graph data, attributed to the
growth of social networks, many native graph database systems have surfaced
to replace Relational databases. Neo4j is the leading and very scalable graph
database system that can store up to millions of nodes and relationships.
Storage of Semantic Web data in Neo4J requires mapping of RDF constructs
to Neo4j. Henceforth, retrieval requires mapping of the SPARQL query lan-
guage for Semantic Web, with the Cypher query language for Neo4j. Logical
inference or reasoning is a fundamental building block of the Semantic Web.
A complementary standard in the SemanticWeb architecture, known as RDF
Schema or RDF/S for short, provides a set of inference rules that de ne the
mechanism for discovering and generating new relationships based on exist-
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ing data. An e cient and scalable implementation of RDF/S inference rules
is also missing in most of the graph database systems. This paper contributes
three pieces of the jigsaw to achieve a scalable RDF storage system. First a
mechanism for mapping RDF constructs with Neo4J is outlined. Secondly,
SPARQL query language is mapped with Cypher for e cient retrieval. And
nally, RDF/S inference rules are implemented to realize logical inference
capability.
