OLAP on Information Networks: A New Framework for Dealing with Bibliographic Data

Abstract

Abstract. In the context of decision making, data warehouses support OLAP technology and they have been very useful for efficient analysis onto structured data. For several years, OLAP is also used to analyze and visualize more complex data. Now, many data sets of interest can be described as a linked collection of interrelated objects. They could be represented as heterogeneous information networks, in which there are multiple object and link types. In this paper, we are focusing on bibliographic data. This type of data constitutes a rich source that is the starting point of research on bibliometrics, scientometrics domains. In this context, we discuss the interest of combining information networks, OLAP and data mining technologies. We propose a framework to materialize this combination and discuss the main challenges to build this framework. The basic idea is to be able to analyze various networks built from the bibliographic data representing different points of view (authors networks, citations networks...) and their dynamic.

A Systematic Review of Recommendations of Long-Term Strategies for Researchers Using Data Science Techniques

“…They also presented an analysis of the relationship between data mining and scientometrics. Meanwhile, Jakawat et al [87] described the current research trend but specifically for the topic of online analytical processing information networks. They presented a framework that builds several networks on the same topic, where each network constitutes a different perspective on how the topic was perceived or approached.…”