Year-end Sale % OFF 
Abstract
BackgroundBiologists 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.ResultsWe 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.ConclusionsWe 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.
Highlights
Biologists often need to assess whether unfamiliar datasets warrant the time investment required for more detailed exploration
Design Here we describe how to leverage the features of the Google Maps API in the context of data visualization
While traditionally end users are responsible for constructing visualizations, our evaluation suggests that in some cases placing the construction of visualizations in the hands of bioinformatics staff in larger labs, such that they are computed only once and become readily available for users to analyze, can be useful in several scenarios
Summary
Biologists often need to assess whether unfamiliar datasets warrant the time investment required for more detailed exploration. Raw datasets are commonly analyzed in one of the many stand-alone systems for biological data visualization developed over the past decade These include software packages targeting microarray expression such as Clusterview [1], Hierarchical Clustering Explorer (HCE) [2], and Spotfire [3], systems for pathway and network analysis like Cytoscape [4], VisANT [5], Ingenuity [6] and Patika [7], or genome viewers such as Cinteny [8] and Mizbee [9]. Some developers overcame browser constraints by making their systems available as applets or to be run as client applications directly from websites [4,11] In such approaches, users must still cope with overheads inherent to stand-alone applications such as adjusting visualization parameters, specifying data queries and learning features. Such websites are often difficult to setup and maintain, becoming prohibitively expensive for small data producers
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
