Exploratory movement analysis and report building with R package stmove

Abstract Background As GPS tags and data loggers have become lighter, cheaper, and longer-lasting, there has been a growing influx of data on animal movement. Simultaneously, methods of analyses and software to apply such methods to movement data have expanded dramatically. Even so, for many interdisciplinary researchers and managers without familiarity with the field of movement ecology and the open-source tools that have been developed, the analysis of movement data has remained an overwhelming challenge. Description Here we present stmove , an R package designed to take individual relocation data and generate a visually rich report containing a set of preliminary results that ecologists and managers can use to guide further exploration of their data. Not only does this package make report building and exploratory data analysis (EDA) simple for users who may not be familiar with the extent of available analytical tools, but it sets forth a framework of best practice analyses, which offers a common starting point for the interpretation of terrestrial movement data. Results Using data from African elephants ( Loxodonta africana ) collected in southern Africa, we demonstrate stmove ’s report building function through the main analyses included: path visualization, primary statistic calculation, summary in space and time, and space-use construction. Conclusions The stmove package provides consistency and increased accessibility to managers and researchers who are interested in movement analysis but who may be unfamiliar with the full scope of movement packages and analytical tools. If widely adopted, the package will promote comparability of results across movement ecology studies

Designing Improved Sediment Transport Visualizations

Monitoring, or more commonly, modeling of sediment transport in the coastal environment is a critical task with relevance to coastline stability, beach erosion, tracking environmental contaminants, and safety of navigation. Increased intensity and regularity of storms such as Superstorm Sandy heighten the importance of our understanding of sediment transport processes. A weakness of current modeling capabilities is the ability to easily visualize the result in an intuitive manner. Many of the available visualization software packages display only a single variable at once, usually as a two-dimensional, plan-view cross-section. With such limited display capabilities, sophisticated 3D models are undermined in both the interpretation of results and dissemination of information to the public. Here we explore a subset of existing modeling capabilities (specifically, modeling scour around man-made structures) and visualization solutions, examine their shortcomings and present a design for a 4D visualization for sediment transport studies that is based on perceptually-focused data visualization research and recent and ongoing developments in multivariate displays. Vector and scalar fields are co-displayed, yet kept independently identifiable utilizing human perception\u27s separation of color, texture, and motion. Bathymetry, sediment grain-size distribution, and forcing hydrodynamics are a subset of the variables investigated for simultaneous representation. Direct interaction with field data is tested to support rapid validation of sediment transport model results. Our goal is a tight integration of both simulated data and real world observations to support analysis and simulation of the impact of major sediment transport events such as hurricanes. We unite modeled results and field observations within a geodatabase designed as an application schema of the Arc Marine Data Model. Our real-world focus is on the Redbird Artificial Reef Site, roughly 18 nautical miles offshor- Delaware Bay, Delaware, where repeated surveys have identified active scour and bedform migration in 27 m water depth amongst the more than 900 deliberately sunken subway cars and vessels. Coincidently collected high-resolution multibeam bathymetry, backscatter, and side-scan sonar data from surface and autonomous underwater vehicle (AUV) systems along with complementary sub-bottom, grab sample, bottom imagery, and wave and current (via ADCP) datasets provide the basis for analysis. This site is particularly attractive due to overlap with the Delaware Bay Operational Forecast System (DBOFS), a model that provides historical and forecast oceanographic data that can be tested in hindcast against significant changes observed at the site during Superstorm Sandy and in predicting future changes through small-scale modeling around the individual reef objects

Taking time to understand: articulating relationships between technologies and organizations

Dynamic relationships between technologies and organizations are investigated through research on digital visualization technologies and their use in the construction sector. Theoretical work highlights mutual adaptation between technologies and organizations but does not explain instances of sustained, sudden, or increasing maladaptation. By focusing on the technological field, I draw attention to hierarchical structuring around inter-dependent levels of technology; technological priorities of diverse groups; power asymmetries and disjunctures between contexts of development and use. For complex technologies, such as digital technologies, I argue these field-level features explain why organizations peripheral to the field may experience difficulty using emerging technology

Linking students' timing of engagement to learning design and academic performance

In recent years, the connection between Learning Design (LD) and Learning Analytics (LA) has been emphasized by many scholars as it could enhance our interpretation of LA findings and translate them to meaningful interventions. Together with numerous conceptual studies, a gradual accumulation of empirical evidence has indicated a strong connection between how instructors design for learning and student behaviour. Nonetheless, students' timing of engagement and its relation to LD and academic performance have received limited attention. Therefore, this study investigates to what extent students' timing of engagement aligned with instructor learning design, and how engagement varied across different levels of performance. The analysis was conducted over 28 weeks using trace data, on 387 students, and replicated over two semesters in 2015 and 2016. Our findings revealed a mismatch between how instructors designed for learning and how students studied in reality. In most weeks, students spent less time studying the assigned materials on the VLE compared to the number of hours recommended by instructors. The timing of engagement also varied, from in advance to catching up patterns. High-performing students spent more time studying in advance, while low-performing students spent a higher proportion of their time on catching-up activities. This study reinforced the importance of pedagogical context to transform analytics into actionable insights

Fine-grained traffic state estimation and visualisation

Tools for visualising the current traffic state are used by local authorities for strategic monitoring of the traffic network and by everyday users for planning their journey. Popular visualisations include those provided by Google Maps and by Inrix. Both employ a traffic lights colour-coding system, where roads on a map are coloured green if traffic is flowing normally and red or black if there is congestion. New sensor technology, especially from wireless sources, is allowing resolution down to lane level. A case study is reported in which a traffic micro-simulation test bed is used to generate high-resolution estimates. An interactive visualisation of the fine-grained traffic state is presented. The visualisation is demonstrated using Google Earth and affords the user a detailed three-dimensional view of the traffic state down to lane level in real time

Visualizing the dynamics of London's bicycle hire scheme

Visualizing flows between origins and destinations can be straightforward when dealing with small numbers of journeys or simple geographies. Representing flows as lines embedded in geographic space has commonly been used to map transport flows, especially when geographic patterns are important as they are when characterising cities or managing transportation. However, for larger numbers of flows, this approach requires careful design to avoid problems of occlusion, salience bias and information overload. Driven by the requirements identified by users and managers of the London Bicycle Hire scheme we present three methods of representation of bicycle hire use and travel patterns. Flow maps with curved flow symbols are used to show overviews in flow structures. Gridded views of docking station location that preserve geographic relationships are used to explore docking station status over space and time in a graphically efficient manner. Origin-Destination maps that visualise the OD matrix directly while maintaining geographic context are used to provide visual details on demand. We use these approaches to identify changes in travel behaviour over space and time, to aid station rebalancing and to provide a framework for incorporating travel modelling and simulation