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Istituto di Scienza e Tecnologie dell'Informazione     
Mannocci A., Manghi P. DataQ: a data flow quality monitoring system for aggregative data infrastructures. Accepted for publication in TPDL 2016 - Theory and Practice of Digital Libraries. 20th International Conference (September 5-9 2016, Hannover, Germany). Springer, 2016. Preprint, 2016.
 
 
Abstract
(English)
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.
Subject Monitoring
Data flow
Data quality
Aggregative data infrastructures
D.2.8 SOFTWARE ENGINEERING. Metrics
K.6.4 MANAGEMENT OF COMPUTING AND INFORMATION SYSTEMS. System Management


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