Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema

By Jeen Broekstra, Arjohn Kampman, Frank van Harmelen. International Workshop on the Semantic Web, 2002

1,602 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/ef82501ce2722202cff3d62830d9923118aedcff

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Citations in the corpus

LUBM: A benchmark for OWL knowledge base systems (2005, methodology): “0.16) as the underlying DBMS since, according to a test by Broekstra and Kampman [5], Sesame performs significantly better than using the other DBMS PostgreSQL [43].”
Semantic Annotation, Indexing, and Retrieval (2003, background): “For an overview of those, please see [13], [12], [16], and [21].”
gStore: Answering SPARQL Queries via Subgraph Matching (2011, background): “Existing RDF storage systems, such as Jena [23], Yars2 [11] and Sesame 2.0 [5], cannot work well in large RDF datasets (such as Yago dataset).”
Optimized index structures for querying RDF from the Web (2005, background): “Systems such as Jena2 [17], Sesame [5], rdfDB [7], Redland [2], Kowari 1 , FORTH RDF Suite [1] and others provide a storage infrastructure for RDF data.”
3store: Efficient Bulk RDF Storage (2003, background): “Sesame [ 9 ] is an architecture for inferencing and querying of RDF and RDF Schema which supports RDQL queries among others (though not OKBC) and produces all the RDF and RDFS entailments.”
Diversified Stress Testing of RDF Data Management Systems (2014, background): “While earlier triplestores followed this approach [8,9], it has been demonstrated that maintaining redundant copies with different sort orders and indexes can be much more effective [19].”
Hexastore: sextuple indexing for semantic web data management (2008, methodology): “Thus, significant efforts have been dedicated to the development of architectures for storing and querying RDF data, called triple stores [8] [9] [11] [17] [25] [26] [46] [19] [45] [39] [44].”
Flink: Semantic Web technology for the extraction and analysis of social networks (2005, neutral): “(For more information about the Sesame RDF storage and query facility, we refer to [ 4 ].) Note that since the model is a compatible extension of FOAF, the knowledge can be further processed from this point by any FOAF-compatible”
GraphX: Graph Processing in a Distributed Dataflow Framework (2014, methodology): “Numerous systems [1, 6, 28] have been proposed for storing and executing SPARQL [31] subgraph queries against RDF triplets.”
Ontop: Answering SPARQL queries over relational databases (2016, background): “– Sesame [9] is a de-facto standard framework for processing RDF data.”