Encyclopedia of Big Data Technologies

Living Edition
| Editors: Sherif Sakr, Albert Zomaya

Graph Path Navigation

Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-63962-8_214-1

Synonyms

Definitions

Navigational query languages for graph databases allow to recursively traverse the edges of a graph while checking for the existence of a path that satisfies certain regular conditions. The basic building block of such languages is the class of regular path queries (RPQs), which are expressions that compute the pairs of nodes that are linked by a path whose label satisfies a regular expression. RPQs are often extended with features that turn them more flexible for practical applications, e.g., with the ability to traverse edges in the backward direction (RPQs with inverses) or to express arbitrary patterns over the data (conjunctive RPQs).

Overview

Graph Databases

Graph databases provide a natural encoding of many types of data where one needs to deal with objects and relationships between them. An object is represented as a node, and a relationship between two objects is represented as an edge, where labels...

This is a preview of subscription content, log in to check access.

References

  1. Alkhateeb F, Baget J, Euzenat J (2009) Extending SPARQL with regular expression patterns (for querying RDF). J Web Sem 7(2):57–73Google Scholar
  2. Angles R, Arenas M, Barceló P, Hogan A, Reutter JL, Vrgoc D (2017) Foundations of Modern Graph Query Languages. ACM Computing Surveys 50(5)Google Scholar
  3. Barceló P (2013) Querying graph databases. In: Proceedings of the 32nd ACM Symposium on Principles of Database Systems, PODS 2013, pp 175–188Google Scholar
  4. Barceló P, Libkin L, Lin AW, Wood PT (2012) Expressive languages for path queries over graph-structured data. ACM Trans Database Syst 37(4):31Google Scholar
  5. Barrett CL, Jacob R, Marathe MV (2000) Formal-language-constrained path problems. SIAM Journal on Computing 30(3):809–837Google Scholar
  6. Calvanese D, De Giacomo G, Lenzerini M, Vardi MY (2000) Containment of conjunctive regular path queries with inverse. In: Proceedings of the 7th International Conference on Principles of Knowledge Representation and Reasoning, KR 2000, pp 176–185Google Scholar
  7. Holland DA, Braun UJ, Maclean D, Muniswamy-Reddy KK, Seltzer MI (2008) Choosing a data model and query language for provenance. In: 2nd International Provenance and Annotation Workshop (IPAW)Google Scholar
  8. Libkin L, Martens W, Vrgoč D (2016) Querying graphs with data. J ACM 63(2):14Google Scholar
  9. Mendelzon AO, Wood PT (1995) Finding regular simple paths in graph databases. SIAM J Comput 24(6):1235–1258Google Scholar
  10. Paths TFP (2009) Use cases in property paths task force. http://www.w3.org/2009/sparql/wiki/TaskForce:PropertyPaths#Use_Cases
  11. Pérez J, Arenas M, Gutierrez C (2010) nSPARQL: A navigational language for RDF. J Web Sem 8(4): 255–270Google Scholar
  12. Robinson I, Webber J, Eifrem E (2013) Graph Databases, 1st edn. O’Reilly MediaGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Pontificia Universidad Católica de ChileSantiagoChile
  2. 2.Universidad de ChileSantiagoChile
  3. 3.School of InformaticsUniversity of EdinburghEdinburghUK

Section editors and affiliations

  • Hannes Voigt
    • 1
  • George Fletcher
    • 2
  1. 1.Dresden Database Systems GroupTechnische Universität DresdenDresdenGermany
  2. 2.Department of Mathematics and Computer ScienceEindhoven University of Technology