What Google Maps can do for Biomedical Data Dissemination: Examples and a Design Study

Background: Biologists often need to assess whether unfamiliar datasets warrant the time investment required for more detailed exploration. Basing such assessments on brief descriptions provided by data publishers is unwieldy for large datasets that contain insights dependent on specific scientific questions. Alternatively, using complex software systems for a preliminary analysis may be deemed as too time consuming in itself, especially for unfamiliar data types and formats. This may lead to wasted analysis time and discarding of potentially useful data. Results: We present an exploration of design opportunities that the Google Maps interface offers to biomedical data visualization. In particular, we focus on synergies between visualization techniques and Google Maps that facilitate the development of biological visualizations which have both low-overhead and sufficient expressivity to support the exploration of data at multiple scales. The methods we explore rely on displaying pre-rendered visualizations of biological data in browsers, with sparse yet powerful interactions, by using the Google Maps API. We structure our discussion around five visualizations: a gene co-regulation visualization, a heatmap viewer, a genome browser, a protein interaction network, and a planar visualization of white matter in the brain. Feedback from collaborative work with domain experts suggests that our Google Maps visualizations offer multiple, scale-dependent perspectives and can be particularly helpful for unfamiliar datasets due to their accessibility. We also find that users, particularly those less experienced with computer use, are attracted by the familiarity of the Google Maps API. Our five implementations introduce design elements that can benefit visualization developers. Conclusions: We describe a low-overhead approach that lets biologists access readily analyzed views of unfamiliar scientific datasets. We rely on pre-computed visualizations prepared by data experts, accompanied by sparse and intuitive interactions, and distributed via the familiar Google Maps framework. Our contributions are an evaluation demonstrating the validity and opportunities of this approach, a set of design guidelines benefiting those wanting to create such visualizations, and five concrete example visualizations.

The rodent fauna of Long Pine Key, Everglades National Park: a comparison of habitat types

Rodents are often involved at several stages of trophic dynamics. Consequently they often play crucial roles in the structure and function of many complex ecological systems. This study sought to address the lack of baseline data concerning rodents in tropical areas, and south Florida in particular. Live trapping took place in the four major habitat types of the Long Pine Key area of Everglades National Park over the course of one year. I compared population structures and abundance of murid rodents in the four habitat types, and tested multiple weather variables for their effectiveness as predictors of rodent abundance. I found the Long Pine Key area to be depauperate in terms of species diversity. Each of the four species of rodent encountered favored a particular habitat type. The density of the understory vegetation and the avoidance of avian predators in particular appear to be the most important factors in the distribution and abundance of rodents in the Long Pine Key area of Everglades National Park.