The Challenge of using Map-reduce to Query Open Data

Mauro Pelucchi; Giuseppe Psaila; Maurizio Toccu

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Paper

The Challenge of using Map-reduce to Query Open Data

In Proceedings of the 6th International Conference on Data Science, Technology and Applications - Volume 1: KomIS, 331-342, 2017 , Madrid, Spain

Authors: Mauro Pelucchi ¹ ; Giuseppe Psaila ² and Maurizio Toccu ³

Affiliations: ¹ University of Bergamo and Tabulaex srl, Italy ; ² University of Bergamo, Italy ; ³ University of Milano Bicocca, Italy

Keyword(s): Retrieval of Open Data, Single Item Extraction, Map-reduce.

Abstract: For transparency and democracy reasons, a few years ago Public Administrations started publishing data sets concerning public services and territories. These data sets are called open, because they are publicly available through many web sites. Due to the rapid growth of open data corpora, both in terms of number of corpora and in terms of open data sets available in each single corpus, the need for a centralized query engine arises, able to select single data items from within a mess of heterogeneous open data sets. We gave a first answer to this need in (Pelucchi et al., 2017), where we defined a technique for blindly querying a corpus of open data. In this paper, we face the challenge of implementing this technique on top of the Map-Reduce approach, the most famous solution to parallelize computational tasks in the Big Data world.

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Paper citation in several formats:

Pelucchi, M.; Psaila, G. and Toccu, M. (2017). The Challenge of using Map-reduce to Query Open Data. In Proceedings of the 6th International Conference on Data Science, Technology and Applications - KomIS; ISBN 978-989-758-255-4; ISSN 2184-285X, SciTePress, pages 331-342. DOI: 10.5220/0006487803310342

@conference{komis17,
author={Mauro Pelucchi. and Giuseppe Psaila. and Maurizio Toccu.},
title={The Challenge of using Map-reduce to Query Open Data},
booktitle={Proceedings of the 6th International Conference on Data Science, Technology and Applications - KomIS},
year={2017},
pages={331-342},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006487803310342},
isbn={978-989-758-255-4},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Data Science, Technology and Applications - KomIS
TI - The Challenge of using Map-reduce to Query Open Data
SN - 978-989-758-255-4
IS - 2184-285X
AU - Pelucchi, M.
AU - Psaila, G.
AU - Toccu, M.
PY - 2017
SP - 331
EP - 342
DO - 10.5220/0006487803310342
PB - SciTePress