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Animal behavior research is becoming an increasingly data-driven field, enabled by advancements in GPS tracking. Rather than directly observe movement and behavior in small numbers of animals, over short time-spans and in small areas, researchers can use GPS collars to track many animals, over large areas and long time spans. These large datasets have the potential to provide rich information about animal behavior. However, this tracking data needs to be integrated with geospatial data about the environment in order to put the movements and estimated behaviors into context. We present an immersive visualization which integrates high resolution topological data from Barro Colorado Island, a 4000 acre island located in the Panama Canal, with GPS tracking data from close to two dozen primates captured over several months. Our application leverages parallelization for rapid filtering of the movement data, allowing researchers to explore the data in a large-scale, immersive environment (CAVE2). We present this work in order to explore the possibility of creating virtual field environments from data, to bring the field into the lab and enable big data animal behavior research.

In this paper, we present SAGE2, a software framework that enables local and remote collaboration on Scalable Resolution Display Environments (SRDE). An SRDE can be any configuration of displays, ranging from a single monitor to a wall of tiled flat-panel displays. SAGE2 creates a seamless ultra-high resolution desktop across the SRDE. Users can wirelessly connect to the SRDE with their own devices in order to interact with the system. Many users can simultaneously utilize a drag-and-drop interface to transfer local documents and show them on the SRDE, use a mouse pointer and keyboard to interact with existing content that is on the SRDE and share their screen so that it is viewable to all. SAGE2 can be used in many configurations and is able to support many communities working with various types of media and high-resolution content, from research meetings to creative session to education. SAGE2 is browser-based, utilizing a web server to host content, WebSockets for message passing and HTML with JavaScript for rendering and interaction. Recent web developments, with the emergence of HTML5, have allowed browsers to use advanced rendering techniques without requiring plug-ins (canvas drawing, WebGL 3D rendering, native video player, etc.). One major benefit of browser-based software is that there are no installation requirements for users and it is inherently cross-platform. A user simply needs a web browser on the device he/she wishes to use as an interaction tool for the SRDE. This lowers considerably the barrier of entry to engage in meaningful collaboration sessions.

In East Africa, up to four symbiotic ant species associate with the obligate myrmecophyte Acacia drepanolobium. These ant species differ in the extent to which they defend their host trees from both vertebrate and invertebrate herbivores, but other potential roles of ants in tree defense have not been studied. We investigate the distribution of a new species of parasitic midge targeting A. drepanolobium in a region where A. drepanolobium is inhabited almost exclusively by two ant species—Crematogaster nigriceps and C. mimosae. We find that the frequency of infestation correlates strongly with the identity of the ant occupant: trees inhabited by C. nigriceps are significantly less likely to be infested with parasitic midges. Although the two ant species responded similarly to simulated large herbivore disturbances, trees inhabited by C. nigriceps also had a lower invertebrate load than trees inhabited by C. mimosae. We suggest that differences in defensive behavior towards invertebrates could be one explanation of the observed differences in infestation of A. drepanolobium by parasitic midges.

Constructing integrative visualizations that simultaneously cater to a variety of data types is challenging. Hybrid-reality environments blur the line between virtual environments and tiled display walls. They incorporate high-resolution, stereoscopic displays, which can be used to juxtapose large, heterogeneous datasets while providing a range of naturalistic interaction schemes. They thus empower designers to construct integrative visualizations that more effectively mash up 2D, 3D, temporal, and multivariate datasets.

Current web-based collaboration systems, such as Google Hangouts, WebEx, and Skype, primarily enable single users to work with remote collaborators through video conferencing and desktop mirroring. The original SAGE software, developed in 2004 and adopted at over one hundred international sites, was designed to enable groups to work in front of large shared displays in order to solve problems that required juxtaposing large volumes of information in ultra high-resolution. We have developed SAGE2, as a complete redesign and implementation of SAGE, using cloud-based and web browser technologies in order to enhance data intensive co-located and remote collaboration. This paper provides an overview of SAGE2's infrastructure, the technical design challenges, and the afforded benefits to data intensive collaboration. Lastly, we provide insight on how future collaborative applications can be developed to support large displays and demonstrate the power and flexibility that SAGE2 offers in collaborative scenarios through a series of use cases.

Molecular and systems biologists are tasked with the comprehension and analysis of incredibly complex networks of biochemical interactions, called pathways, that occur within a cell. Through interviews with domain experts, we identified four common tasks that require an understanding of the causality within pathways, that is, the downstream and upstream relationships between proteins and biochemical reactions, including: visualizing downstream consequences of perturbing a protein; finding the shortest path between two proteins; detecting feedback loops within the pathway; and identifying common downstream elements from two or more proteins. We introduce ReactionFlow, a visual analytics application for pathway analysis that emphasizes the structural and causal relationships amongst proteins, complexes, and biochemical reactions within a given pathway. To support the identified causality analysis tasks, user interactions allow an analyst to filter, cluster, and select pathway components across linked views. Animation is used to highlight the flow of activity through a pathway. We evaluated ReactionFlow by providing our application to two domain experts who have significant experience with biomolecular pathways, after which we conducted a series of in-depth interviews focused on each of the four causality analysis tasks. Their feedback leads us to believe that our techniques could be useful to researchers who must be able to understand and analyze the complex nature of biological pathways. ReactionFlow is available at https://github.com/CreativeCodingLab/ReactionFlow .

Background The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. Results In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE through a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. Conclusions BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics.