Nowadays, IoT is being used in more and more application areas and the importance of IoT
data quality is widely recognized by practitioners and researchers. The requirements for …

Over the last two decades, much attention hasbeen paid to the area of Goal-Oriented
Requirements Engineering (GORE), where goals are used as a useful conceptualizationto …

In the complex decision-environments that characterize e-business settings, it is important to
permit decision-makers to proactively manage data quality. In this paper we propose a …

A data evolution life cycle typically consists of four stages of data activities: collection,
organization, presentation, and application. During the cycle, data evolve as per the needs …

As the volume of data exponentially increases, organizations are looking for smarter ways to
create the most value from their data. One approach to achieve this is through developing …

In order to enhance their global business performance, organizations must be careful with
the quality of their information since it is one of their main assets. Analogies to quality …

Purpose–The purpose of the paper is to propose a reference model describing a holistic
view of the master data lifecycle, including strategic, tactical and operational aspects. The …

It is aware that big data has gathered tremendous attentions from academic research
institutes, governments, and enterprises in all aspects of information sciences. With the …

BPMN is a notation for business process modeling through which it is possible to represent
multiple characteristics of the analyzed business processes. However, although in a …

Purpose–The purpose of this paper is to conceptualize data quality (DQ) in the context of
business process management and to propose a DQ oriented approach for business …