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.

Organizational culture, organizational climate, and collaborative capacity for planning

The objective of this study was to investigate the relationship of organizational culture and organizational climate on participant perceptions of collaborative capacity for planning, within the context of the Florida School Readiness Coalitions (FSRCs). Three hypotheses were proposed for study: First, that organizational culture would be correlated to organizational climate; second, that organizational culture would be correlated to collaborative capacity for planning; and the third that organizational climate would be correlated to collaborative capacity for planning. ^ A cross-sectional survey research design was used to obtain data from participants in 25 Florida School Readiness Coalitions. Pearson product-moment correlations were used to examine the association between the dependent variable, collaborative capacity for planning, and the independent variables, organizational culture and climate. Bivariate analyses revealed a significant level of association for five culture indicators to collaborative capacity for planning: motivation, interpersonal, service, supportive and individualistic indicators, and four climate indicators: cooperation, job satisfaction, organizational commitment, and role clarity. Findings suggest (a) a constructive culture and positive climate were present within the FSRCs during the period of study and (b) participants perceived that the collaborative capacity for planning existed. Hierarchical multiple regression, controlling for effects of participant demographics, were used to examine the degree to which organizational culture and climate predict collaborative capacity. The culture indicators, supportive and individualistic, and the climate indicator job satisfaction accounted for 46% of the variance in collaborative capacity for planning. No other indicators of the independent variables demonstrated significance. The findings suggests that (a) culture and climate should be studied together, (b) culture and climate are two constructs that may provide knowledge about the way community groups work together, and (c) the collaborative capacity of groups planning services such as the FSRCs may benefit through consideration of how culture and climate affect service planners' relationships, communication, and ability to achieve a mission or goal. Culture and climate may offer social workers new information about internal factors affecting the collaborative process. Further investigation of these constructs with other types of groups is warranted. ^