Title: The Geometry and Topology of Data and Information for Analytics of Processes and Behaviours: Building on Bourdieu and Addressing New Societal Challenges,
Abstract: We begin by summarizing the relevance and importance of inductive analytics
based on the geometry and topology of data and information. Contemporary issues
are then discussed. These include how sampling data for representativity is
increasingly to be questioned. While we can always avail of analytics from a
"bag of tools and techniques", in the application of machine learning and
predictive analytics, nonetheless we present the case for Bourdieu and
Benzécri-based science of data, as follows. This is to construct bridges
between data sources and position-taking, and decision-making. There is summary
presentation of a few case studies, illustrating and exemplifying application
domains.