Synonyms
Semi-structured data
Definition
The semi-structured data model is designed as an evolution of the relational data model that allows the representation of data with a flexible structure. Some items may have missing attributes, others may have extra attributes, some items may have two or more occurrences of the same attribute. The type of an attribute is also flexible: it may be an atomic value, or it may be another record or collection. Moreover, collections may be heterogeneous, i.e., they may contain items with different structures. The semi-structured data model is self-describing data model, in which the data values and the schema components co-exist. Formally:
Definition 1
A semi-structured data instance is a rooted, directed graph in which the edges carry labels representing schema components, and leaf nodes (i.e., nodes without any outgoing edges) are labeled with data values (integers, reals, strings, etc.).
There are two variations of semi-structured data, depending on...
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsRecommended Reading
Buneman P, Davidson S, Suciu D. Programming constructs for unstructured data. In: Proceedings of the 5th International Workshop on Database Programming Languages; 1995.
Buneman P, Davidson S, Hillebrand G, Suciu D. A query language and optimization techniques for unstructured data. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 1996. p. 505–16.
Buneman P, Fernandez M, Suciu D. UNQL: a query language and algebra for semistructured data based on structural recursion. VLDB J. 2000;9(1):76–110.
Deutsch A, Fernandez M, Florescu D, Levy A, Suciu D. A query language for XML. In: Proceedings of the 8th International World Wide Web Conference; 1999. p. 77–91.
Garcia-Molina H, Papakonstantinou Y, Quass D, Rajaraman A, Sagiv Y, Ullman J, Widom J. The TSIMMIS project: integration of heterogeneous information sources. J Intell Inf Syst. 1997;8(2):117–32.
Luniewski A, Schwarz P, Shoens K, Stamos J, Thomas J. Information organization using Rufus. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 1993. p. 560–1.
Paige R, Tarjan R. Three partition refinement algorithms. SIAM J. Comput. 1987;16(6):973–88.
Papakonstantinou Y, Garcia-Molina H, Widom J. Object exchange across heterogeneous information sources. In: Proceedings of the 11th International Conference on Data Engineering; 1995. p. 251–60.
Shoens K, Luniewski A, Schwarz P, Stamos J, Thomas II J. The Rufus system: information organization for semi-structured data. In: Proceedings of the 19th International Conference on Very Large Data Bases; 1993. p. 97–107.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this entry
Cite this entry
Suciu, D. (2018). Semi-structured Data Model. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_337
Download citation
DOI: https://doi.org/10.1007/978-1-4614-8265-9_337
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-8266-6
Online ISBN: 978-1-4614-8265-9
eBook Packages: Computer ScienceReference Module Computer Science and Engineering