Encyclopedia of Database Systems

Living Edition
| Editors: Ling Liu, M. Tamer Özsu


  • Amarnath GuptaEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4899-7993-3_1306-2


An annotation is any form of additional information “superposed” on any existing data or document.

Example: If a scientist records her experimental data in a relational database and then marks some “cells” of a table with the comment “consistent with previous findings,” this additionally “marked” information is an annotation.

Key Points

Often annotations are not originally intended to be part of the collected data, and hence no data or schema structure was designed to hold it. Annotating data is a very common practice in science, where scientists would literally “mark” experimental observation with comments and often use annotations to share their opinions in a collaborative study. One can annotate data at the level of whole data sets, groups of data elements (like columns), or values. As larger-scale experiments are conducted and larger collaborations are formed, management of the annotated data becomes a serious challenge. In recent times, the emerging importance of...

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

Recommended Reading

  1. 1.
    Bhagwat D, Chiticariu L, Tan WC, Vijayvargiya G. An annotation management system for relational databases. In: Proceedings 30th International Conference on Very Large Data Bases; 2004. p. 900–11.Google Scholar
  2. 2.
    Buneman P, Khanna S, Tan W-C. On propagation of deletions and annotations through views. In: Proceedings 21st ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems; 2002. p. 150–8.Google Scholar
  3. 3.
    Geerts F, Kementsiesidis A, Milano D. MONDRIAN: annotating and querying databases through colors and blocks. In: Proceedings 22nd International Conference on Data Engineering; 2006. p. 82.Google Scholar
  4. 4.
    Gertz M, Sattler K-U. Integrating scientific data through external, concept-based annotations. In: Proceedings Workshop on Efficiency and Effectiveness of XML Tools and Techniques and Data Integration over the Web. LNCS, vol. 2590. Springer; 2002. p. 220–40.Google Scholar
  5. 5.
    Murthy S, Maier D, Delcambre LML. Querying bi-level information. In: Proceedings 7th International Workshop on the World Wide Web and Databases; 2004. p. 7–12.Google Scholar
  6. 6.
    Srivastava D, Velegrakis Y. Intensional associations between data and metadata. In: Proceedings ACM SIGMOD International Conference on Management of Data; 2007. p. 401–12.Google Scholar

Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  1. 1.San Diego Supercomputer CenterUniversity of California San DiegoLa JollaUSA

Section editors and affiliations

  • Amarnath Gupta
    • 1
  1. 1.San Diego Supercomputer CenterUniversity of California San DiegoLa JollaUSA