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Understanding Big Data for Industrial Innovation and Design: The Missing Information Systems Perspective

widespread use and adoption of big data applications is unlikely ever to go beyond the pages of policies, academic papers, and speculative industrial articles. The real world of government, industry, and business is a pragmatic one, driven by business value, efficiency, and competition. If the added value of big data applications and services cannot be clearly established beyond the realm of speculation and theory, then its survival is doomed. The Need for New Agendas in Information Systems Some attempt to address the set of basic questions posed above is crucial if

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A Framework for the Assessment of Research and Its Impacts

understanding the reality. The potentiality of models can be expressed for description, interpretation, forecasting, and intervention. These different roles may be correlated or not, depending on the objective of the analysis and the way the model is built. To be successful the modeling has to take into account the specificities of the processes and systems under investigation, and in particular consider that the behavior is free and finalized to given aims; history and evolution matter as the behavior of systems and processes changes over time (see e.g. Georgescu

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Enhancing Navigability: An Algorithm for Constructing Tag Trees

of navigation. On the other hand, other studies aimed to develop more loosely structured hierarchies for the purpose of navigating through a large number of resources (e.g. Candan, Di Caro, & Sapino, 2008 ; Helic et al., 2010 ; Heymann, & Garcia-Molina, 2006 ; Huang et al., 2013 ; Sinclair & Cardew-Hall, 2008 ). These hierarchies usually involved various tags and were more practical when users were not familiar with the resource domain. This study belongs to this stream and goes further on semantic coherence and structural balance of the hierarchy for the

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Factors Influencing Cities’ Publishing Efficiency

team of researchers is), which, due to their nature, vary city to city. However, based on the general factors, typical geographical patterns can be revealed. In this paper, I aim to measure cities’ publishing efficiency worldwide and present the most significant general factors that might influence their publishing efficiency. The structure of the paper is as follows. In Section 2 , I present the data collection process and the methodology. Section 3 is divided into two subsections. In the first subsection, I rank cities based on their publishing efficiency, and

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Science Mapping: A Systematic Review of the Literature

reveal the underlying mechanisms of how science advances. The complexity of science mapping is shared by many research fields. In this article, our aim is to demonstrate the process of a systematic review based on a series of visual analytic functions implemented in the continously evolving software CiteSpace ( Chen, 2004 ; Chen, 2006 ; Chen, Ibekwe-SanJuan, & Hou, 2010 ). We demonstrate the steps of preparing a representative dataset, how to generate visualizations that can guide our review, and how to identify salient patterns at various levels of granularity. We

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