Mapping trajectories and flows: facilitating a human-centered approach to movement data analytics

Abstract

This paper argues for a "human-centered" approach to knowledge discovery from movement data through the use of visualization and mapping. As movement data becomes more available and diverse in dimension and resolution, mapping becomes particularly important in the exploratory analysis of movement trajectories and for capturing patterns and structures in large origindestination flow data sets. Movement phenomena (e.g. ranging from micro-movements of humans and animals to macro-level mobility, to migration flows, to spread of viruses) are complex dynamic processes which are realized in a multidimensional location-time-context space. This paper provides a comprehensive overview of various visualization techniques for mapping movement through the lens of cartography and with a special focus on the "human user" (e.g. data scientist, analyst, domain expert, etc.). We systematically characterize and categorize available techniques based on their visual specifications and functional capacities for human control, map-interaction, and design flexibility. These elements are beneficial to enhance the user's capacities for map reasoning and knowledge discovery. Trends and gaps in the literature on movement visualization over the past 10 years are discussed. Our review suggests that future research should focus more on the role of the "human" in the development of human-centered visual analytic and exploratory tools, while providing functionalities for mapping uncertainty and protecting individual privacy in knowledge discovery of movement. These tools should be guided by a cartographic framework and visual principles specifically pertinent to movement.

DynamoVis 1.0: an exploratory data visualization software for mapping movement in relation to internal and external factors

“…However, the proper selection and combination of these variables require a systematic user study evaluation to assess their efficacy in enhancing cognition of movement patterns for different applications. For more information on the cartographic design and symbology choices, the readers are referred to Dodge and Noi [ 1 ] which provides a systematic classification of available movement visualization techniques and a detailed discussion on various elements of the cartographic framework used in DynamoVis. In addition, our ongoing work focuses on the systematic evaluation of this cartographic framework for various applications.…”

“…DynamoVis is based on a cartographic framework introduced in Dodge and Noi [ 1 ]. Figure 1 provides a modified version of the framework tailored to the visualization of animal movement.…”

“…Visualization tools have never been as widely available as they are today, creating a foundation for enormous strides in fields such as geography, information visualization, ecology, and biology. New multimodal sensors and data collection methods paired with powerful developments in spatial analytics and mapping tools have given scientists the power to study animals’ movement behavior and understand how they adapt given environmental variability [ 1 ]. These opportunities include combining new and increasingly abundant multifaceted data sets of animal movement tracking at high spatial and temporal granularity that are enriched with contextual information on the physiological state, motion and navigation capacities of the individuals, as well as the geography and the surrounding environment impacting their movement [ 2 ].…”

“…It can enable researchers and decision-makers to explore complex spatial and temporal relationships between movement and its context, uncover hidden patterns, and convey information captured in the data. It can be used as a powerful tool to support hypothesis generation and confirmation through human visual reasoning and to facilitate communication and discussion in interdisciplinary research [ 1 ]. It can also be used as a decision-support tool to inform fieldwork and facilitate collaborations between experts and professionals from diverse backgrounds [ 13 , 14 ].…”

Mapping Research Trajectories

“…Mapping trajectories has a long tradition in geographic visualization and it has, more recently, also been used in the fields computational movement analysis and trajectory mining. An overview on some applications in these fields is given by Dodge and Noi [16], Laube [17], Zheng [18]. For visualization of geographic trajectories flow maps are often used, in particular, to depict aggre-gated movement of entities [16].…”