Towards Intelligent Data Analysis: The Metadata Challenge

Besim Bilalli, Alberto Abelló, Tomàs Aluja-Banet, Robert Wrembel


Once analyzed correctly, data can yield substantial benefits. The process of analyzing the data and transforming it into knowledge is known as Knowledge Discovery in Databases (KDD). The plethora and subtleties of algorithms in the different steps of KDD, render it challenging. An effective user support is of crucial importance, even more now, when the analysis is performed on Big Data. Metadata is the necessary component to drive the user support. In this paper we study the metadata required to provide user support on every stage of the KDD process. We show that intelligent systems addressing the problem of user assistance in KDD are incomplete in this regard. They do not use the whole potential of metadata to enable assistance during the whole process. We present a comprehensive classification of all the metadata required to provide user support. Furthermore, we present our implementation of a metadata repository for storing and managing this metadata and explain its benefits in a real Big Data analytics project.


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Paper Citation

in Harvard Style

Bilalli B., Abelló A., Aluja-Banet T. and Wrembel R. (2016). Towards Intelligent Data Analysis: The Metadata Challenge . In Proceedings of the International Conference on Internet of Things and Big Data - Volume 1: IoTBD, ISBN 978-989-758-183-0, pages 331-338. DOI: 10.5220/0005876203310338

in Bibtex Style

author={Besim Bilalli and Alberto Abelló and Tomàs Aluja-Banet and Robert Wrembel},
title={Towards Intelligent Data Analysis: The Metadata Challenge},
booktitle={Proceedings of the International Conference on Internet of Things and Big Data - Volume 1: IoTBD,},

in EndNote Style

JO - Proceedings of the International Conference on Internet of Things and Big Data - Volume 1: IoTBD,
TI - Towards Intelligent Data Analysis: The Metadata Challenge
SN - 978-989-758-183-0
AU - Bilalli B.
AU - Abelló A.
AU - Aluja-Banet T.
AU - Wrembel R.
PY - 2016
SP - 331
EP - 338
DO - 10.5220/0005876203310338