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DataQ: a data flow quality monitoring system for aggregative data infrastructures

Contributo in Atti di convegno
Data di Pubblicazione:
2016
Abstract:
Aggregative Data Infrastructures (ADIs) are information systems offering services to integrate content collected from data sources so as to form uniform and richer information spaces and support communities of users with enhanced access services to such content. The resulting information spaces are an important asset for the target communities, whose services demand for guarantees on their "correctness" and "quality" over time, in terms of the expected content (structure and semantics) and of the processes generating such content. Application-level continuous monitoring of ADIs becomes therefore crucial to ensure validation of quality. However, ADIs are in most of the cases the result of patchworks of software components and services, in some cases developed independently, built over time to address evolving requirements. As such they are not generally equipped with embedded monitoring components and ADI admins must rely on third-party monitoring systems. In this paper we describe DataQ, a general-purpose system for exible and cost-effective data fow quality monitoring in ADIs. DataQ supports ADI admins with a framework where they can (i) represent ADIs data fows and the relative monitoring specification, and (ii) be instructed on how to meet such specification on the ADI side to implement their monitoring functionality.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Monitoring; Data flow; Data quality; Aggregative data infrastructures
Elenco autori:
Mannocci, Andrea; Manghi, Paolo
Autori di Ateneo:
MANGHI PAOLO
MANNOCCI ANDREA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/318036
Link al Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/318036/163914/prod_357402-doc_116644.pdf
Titolo del libro:
TPDL 2016 - Research and Advanced Technology for Digital Libraries. 20th International Conference on Theory and Practice of Digital Libraries
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URL

https://link.springer.com/chapter/10.1007/978-3-319-43997-6_28
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