Visual Analytics for Characterizing Mobility Aspects of Urban Context

AbstractVisual analytics science develops principles and methods for efficient human–computer collaboration in solving complex problems. Visual and interactive techniques are used to create conditions in which human analysts can effectively utilize their unique capabilities: the power of seeing, interpreting, linking, and reasoning. Visual analytics research deals with various types of data and analysis tasks from numerous application domains. A prominent research topic is analysis of spatiotemporal data, which may describe events occurring at different spatial locations, changes of attribute values associated with places or spatial objects, or movements of people, vehicles, or other objects. Such kinds of data are abundant in urban applications. Movement data are a quintessential type of spatiotemporal data because they can be considered from multiple perspectives as trajectories, as spatial events, and as changes of space-related attribute values. By example of movement data, we demonstrate the utilization of visual analytics techniques and approaches in data exploration and analysis.

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Visual analytics of movement: An overview of methods, tools and procedures

Information Visualization ◽

10.1177/1473871612457601 ◽

2012 ◽

Vol 12 (1) ◽

pp. 3-24 ◽

Cited By ~ 149

Author(s):

Natalia Andrienko ◽

Gennady Andrienko

Keyword(s):

Machine Learning ◽

Visual Analytics ◽

Data Analytics ◽

Information Science ◽

State Of The Art ◽

Geographic Information Science ◽

Geographic Information ◽

Research Topic ◽

Visual Methods ◽

Movement Data

Analysis of movement is currently a hot research topic in visual analytics. A wide variety of methods and tools for analysis of movement data has been developed in recent years. They allow analysts to look at the data from different perspectives and fulfil diverse analytical tasks. Visual displays and interactive techniques are often combined with computational processing, which, in particular, enables analysis of a larger number of data than would be possible with purely visual methods. Visual analytics leverages methods and tools developed in other areas related to data analytics, particularly statistics, machine learning and geographic information science. We present an illustrated structured survey of the state of the art in visual analytics concerning the analysis of movement data. Besides reviewing the existing works, we demonstrate, using examples, how different visual analytics techniques can support our understanding of various aspects of movement.

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Measuring the brain-gut axis in Psychological Sciences: a necessary challenge

10.31234/osf.io/fpmrn ◽

2019 ◽

Author(s):

Ismael Palacios-Garcia ◽

Francisco J. Parada

Keyword(s):

Mental Health ◽

Public Policy ◽

Cognitive Process ◽

Research Topic ◽

The Body ◽

Symbiotic Relationship ◽

Multiple Perspectives ◽

Medical Sciences ◽

4E Cognition ◽

The Brain

Cognitive process and associated states such as wellbeing are embodied, in a process of phylogenetic and ontogenic interdependencies, encompassing an organism’s both internal and external environments. Diurnal mammals’ physiology has been enslaved by the day/night cycle, imposed to planet Earth from the cosmos. Mammals’ physiology is furthermore entangled to the micro-dynamics of small organisms, imposed onto the body through the development of a symbiotic relationship unfolding throughout ontogeny and phylogeny. Therefore, adequate scientific study of human behavior will include as many levels as possible: socio-cultural, psychological, microbiological, etc. The brain-gut-microbiota topic represents a fascinating opportunity to expand our knowledge about cognition, mental health, and life in general. It is important to frame this research topic from multiple perspectives including biological/medical sciences, public policy, architecture, urbanism, and psychology. Furthermore, recent philosophical and epistemological advances, under the 4E-cognition framework, will help the integration of evidence, providing new insights and novel hypotheses.

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