IQ-METER - An evaluation tool for data-transformation systems

Giansalvatore Mecca, Paolo Papotti, Donatello Santoro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

We call a data-transformation system any system that maps, translates and exchanges data across different representations. Nowadays, data architects are faced with a large variety of transformation tasks, and there is huge number of different approaches and systems that were conceived to solve them. As a consequence, it is very important to be able to evaluate such alternative solutions, in order to pick up the right ones for the problem at hand. To do this, we introduce IQ-Meter, the first comprehensive tool for the evaluation of data-transformation systems. IQ-Meter can be used to benchmark, test, and even learn the best usage of data-transformation tools. It builds on a number of novel algorithms to measure the quality of outputs and the human effort required by a given system, and ultimately measures 'how much intelligence' the system brings to the solution of a data-translation task.

Original languageEnglish
Title of host publication2014 IEEE 30th International Conference on Data Engineering, ICDE 2014
PublisherIEEE Computer Society
Pages1218-1221
Number of pages4
ISBN (Print)9781479925544
DOIs
Publication statusPublished - 1 Jan 2014
Event30th IEEE International Conference on Data Engineering, ICDE 2014 - Chicago, IL, United States
Duration: 31 Mar 20144 Apr 2014

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627

Other

Other30th IEEE International Conference on Data Engineering, ICDE 2014
CountryUnited States
CityChicago, IL
Period31/3/144/4/14

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ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems

Cite this

Mecca, G., Papotti, P., & Santoro, D. (2014). IQ-METER - An evaluation tool for data-transformation systems. In 2014 IEEE 30th International Conference on Data Engineering, ICDE 2014 (pp. 1218-1221). [6816745] (Proceedings - International Conference on Data Engineering). IEEE Computer Society. https://doi.org/10.1109/ICDE.2014.6816745