1,081 research outputs found
Reconciliation of RDF* and Property Graphs
Both the notion of Property Graphs (PG) and the Resource Description
Framework (RDF) are commonly used models for representing graph-shaped data.
While there exist some system-specific solutions to convert data from one model
to the other, these solutions are not entirely compatible with one another and
none of them appears to be based on a formal foundation. In fact, for the PG
model, there does not even exist a commonly agreed-upon formal definition.
The aim of this document is to reconcile both models formally. To this end,
the document proposes a formalization of the PG model and introduces
well-defined transformations between PGs and RDF. As a result, the document
provides a basis for the following two innovations: On one hand, by
implementing the RDF-to-PG transformations defined in this document, PG-based
systems can enable their users to load RDF data and make it accessible in a
compatible, system-independent manner using, e.g., the graph traversal language
Gremlin or the declarative graph query language Cypher. On the other hand, the
PG-to-RDF transformation in this document enables RDF data management systems
to support compatible, system-independent queries over the content of Property
Graphs by using the standard RDF query language SPARQL. Additionally, this
document represents a foundation for systematic research on relationships
between the two models and between their query languages.Comment: slightly changed the definition of PGs and added the notion of
property uniquenes
An introduction to Graph Data Management
A graph database is a database where the data structures for the schema
and/or instances are modeled as a (labeled)(directed) graph or generalizations
of it, and where querying is expressed by graph-oriented operations and type
constructors. In this article we present the basic notions of graph databases,
give an historical overview of its main development, and study the main current
systems that implement them
Cypher: An Evolving Query Language for Property Graphs
International audienceThe Cypher property graph query language is an evolving language, originally designed and implemented as part of the Neo4j graph database, and it is currently used by several commercial database products and researchers. We describe Cypher 9, which is the first version of the language governed by the openCypher Implementers Group. We first introduce the language by example, and describe its uses in industry. We then provide a formal semantic definition of the core read-query features of Cypher, including its variant of the property graph data model, and its " ASCII Art " graph pattern matching mechanism for expressing subgraphs of interest to an application. We compare the features of Cypher to other property graph query languages, and describe extensions, at an advanced stage of development, which will form part of Cypher 10, turning the language into a compositional language which supports graph projections and multiple named graphs
G-CORE a core for future graph query languages
We report on a community effort between industry and academia to
shape the future of graph query languages. We argue that existing
graph database management systems should consider supporting
a query language with two key characteristics. First, it should be
composable, meaning, that graphs are the input and the output of
queries. Second, the graph query language should treat paths as
first-class citizens. Our result is G-CORE, a powerful graph query
language design that fulfills these goals, and strikes a careful balance
between path query expressivity and evaluation complexity
G-CORE a core for future graph query languages
We report on a community effort between industry and academia to shape the future of graph query languages. We argue that existing graph database management systems should consider supporting a query language with two key characteristics. First, it should be composable, meaning, that graphs are the input and the output of queries. Second, the graph query language should treat paths as first-class citizens. Our result is G-CORE, a powerful graph query language design that fulfills these goals, and strikes a careful balance between path query expressivity and evaluation complexity
G-CORE a core for future graph query languages
We report on a community effort between industry and academia to shape the future of graph query languages. We argue that existing graph database management systems should consider supporting a query language with two key characteristics. First, it should be composable, meaning, that graphs are the input and the output of queries. Second, the graph query language should treat paths as first-class citizens. Our result is G-CORE, a powerful graph query language design that fulfills these goals, and strikes a careful balance between path query expressivity and evaluation complexity
A Researcher’s Digest of GQL
International audienceGQL (Graph Query Language) is being developed as a new ISO standard for graph query languages to play the same role for graph databases as SQL plays for relational. In parallel, an extension of SQL for querying property graphs, SQL/PGQ, is added to the SQL standard; it shares the graph pattern matching functionality with GQL. Both standards (not yet published) are hard-to-understand specifications of hundreds of pages. The goal of this paper is to present a digest of the language that is easy for the research community to understand, and thus to initiate research on these future standards for querying graphs. The paper concentrates on pattern matching features shared by GQL and SQL/PGQ, as well as querying facilities of GQL
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