Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/1421
Title: MONDRIAN: Annotating And Querying Databases Through Colors And Blocks
Authors: GEERTS, Floris 
Kementsietsidis, A
Milano, D.
Issue Date: 2006
Source: Liu, Ling & Reuter, Andreas & Whang, Kyu-Young & Zhang, Jianjun (Ed.) Proceedings of the 22nd International Conference on Data Engineering (ICDE '06). p. 82-....
Series/Report: IEEE Computer Society
Abstract: Annotations play a central role in the curation of scientific databases. Despite their importance, data formats and schemas are not designed to manage the increasing variety of annotations. Moreover, DBMS’s often lack support for storing and querying annotations. Furthermore, annotations and data are only loosely coupled. This paper introduces an annotation-oriented data model for the manipulation and querying of both data and annotations. In particular, the model allows for the specification of annotations on sets of values and for effectively querying the information on their association. We use the concept of block to represent an annotated set of values. Different colors applied to the blocks represent different annotations. We introduce a color query language for our model and prove it to be both complete (it can express all possible queries over the class of annotated databases), and minimal (all the algebra operators are primitive). We present MONDRIAN, a prototype implementation of our annotation mechanism, and we conduct experiments that investigate the set of parameters which influence the evaluation cost for color queries.
Keywords: Annotations, Query languages, Data models
Document URI: http://hdl.handle.net/1942/1421
ISBN: 0-7695-2570-9
DOI: 10.1109/ICDE.2006.102
Category: C1
Type: Proceedings Paper
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
paperICDE.pdfPostprint398.65 kBAdobe PDFView/Open
Show full item record

SCOPUSTM   
Citations

77
checked on Sep 2, 2020

Page view(s)

40
checked on May 15, 2022

Download(s)

176
checked on May 15, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.