Open Data (OD) is one of the most discussed issue of Big Data which raised the joint interest of public institutions, citizens and private companies since 2009. However, the massive amount of freely available data has not yet brought the expected effects: as of today, there is no application that has fully exploited the potential provided by large and distributed information sources in a non-trivial way, nor any service has substantially changed for the better the lives of people. The era of a new generation applications based on OD is far to come. In this context, we observe that OD quality is one of the major threats to achieving the goals of the OD movement. The starting point of this case study is the quality of the OD released by the five Constitutional offices of Italy. Our exploratory case study aims to assess the quality of such releases and the real implementations of OD. The outcome suggests the need of a drastic improvement in OD quality. Finally we highlight some key quality principles for OD, and propose a roadmap for further research.

Big Data Quality: a Roadmap for Open Data

Poggi Francesco;
2016

Abstract

Open Data (OD) is one of the most discussed issue of Big Data which raised the joint interest of public institutions, citizens and private companies since 2009. However, the massive amount of freely available data has not yet brought the expected effects: as of today, there is no application that has fully exploited the potential provided by large and distributed information sources in a non-trivial way, nor any service has substantially changed for the better the lives of people. The era of a new generation applications based on OD is far to come. In this context, we observe that OD quality is one of the major threats to achieving the goals of the OD movement. The starting point of this case study is the quality of the OD released by the five Constitutional offices of Italy. Our exploratory case study aims to assess the quality of such releases and the real implementations of OD. The outcome suggests the need of a drastic improvement in OD quality. Finally we highlight some key quality principles for OD, and propose a roadmap for further research.
2016
Inglese
2016 IEEE 2nd International Conference on Big Data Computing Service and Applications, BigDataService
210
215
6
29/03/2016,01/04/2016
Oxford, UK
Open Data Quality
Information Modeling
E-Government
Big Data Knowledge Extraction
3
none
Ciancarini, Paolo; Poggi, Francesco; Russo, Daniel
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/448605
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 17
  • ???jsp.display-item.citation.isi??? 8
social impact