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The literature provides a wide range of techniques to assess and improve the quality of data. Due to the diversity and complexity of these techniques, research has recently focused on defining methodologies that help the selection, customization, and application of data quality assessment and improvement techniques. The goal of this article is to provide a(More)
The quality of data is often defined as "fitness for use", i.e., the ability of a data collection to meet user requirements. The assessment of data quality dimensions should consider the degree to which data satisfy users' needs. User expectations are clearly related to the selected services and at the same time a service can have different characteristics(More)
In service oriented architectures, Quality of Service (QoS) is a key issue. Service requestors evaluate QoS at run time to address their service invocation to the most suitable provider. Thus, QoS has a direct impact on the providers' revenues. However, QoS requirements are difficult to satisfy because of the high variability of Internet workloads. This(More)
In service oriented systems, Quality of Service (QoS) is a service selection driver. Users evaluate QoS at run time to address their service invocation to the most suitable provider. Thus, QoS has a direct impact on providers' revenues. However, QoS requirements are difficult to satisfy because of the high variability of Internet workloads. Workload(More)
Current e-service technology paradigms require the analysis and conceptual modeling of cooperative inter-organizational workflows. Cooperation among different organizations is based on contractual agreements that coordinate production activities among cooperating companies and establish mechanisms to control the fulfillment of production goals. Existing(More)