Title: Visualizing spatial relationships among health, environment, and demographic statistics: Interface design issues.

Authors: MacEachren, Alan M., C. Polsky, D. Haug, D. Brown, F. Boscoe, J. Beeddasy, L. Pickle, and M. Marrara.

Date: 1997

Abstract: Mapping of georeferenced health statistics has, in the past, led to insights concerning various health-environment-behavior interactions. Insights have derived from the identification of clusters of deaths on static maps (Mason et al., 1975; Pickle et al., 1987; Pickle et al., 1990) followed by comparison of the cluster locations to the mapped distribution of potential etiologic agents (Croner et al., 1992). Spatial associations identified have prompted hypotheses about the causal relations, some of which have been verified. Examples include identification of "hot spots" of esophagal cancer in China and oral cancer in the U.S. state of North Carolina (Winn et al., 1981). Static paper maps, while somewhat successful in prompting epidemiological hypotheses, impose constraints on exploration of spatial characteristics of health-environment-behavior interactions. Dynamic visualization methods offer the potential to dramatically extend the role of maps in health analysis. This paper reports on the design and implementation of a prototype dynamic interface to georeferenced health, environmental, and demographic data, with the prototype sponsored by and developed for the U.S. National Center for health Statistics, Centers for Disease Control and Prevention (NCHS). Two specific objectives have been delineated for the initial prototype: (1) to design alternative methods for displaying dynamic maps of death rate and risk factor data in a user-friendly computer system, and (2) to test these designs in an experiment where users attempt to draw inferences about changing death rate patterns and their relationship to risk factor patterns.

Publication: Proceedings of the 18th International Cartographic Conference, June 21-27, 1997, Stockholm, Sweden, pp 880-887.

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Title: Evaluation of map color schemes for the NCHS mortality atlas

Authors: Brewer, Cynthia and Alan M. MacEachren

Date: 1995

Publication: Proceedings, International Symposium on Computer Mapping in Epidemiology and Environmental Health, February 12-15.

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Title: Mapping mortality: Selecting hues and evaluating color schemes

Authors: Brewer, Cynthia, A. M. MacEachren, L. Pickle, and D. Herrmann

Date: 1997

Publication: Annals of the Association of American Geographers, 87(3): pp 411-438.

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Title: Visualizing georeferenced data: representing reliability in health statistics.

Authors: MacEachren, Alan, Cynthia Brewer, Linda Pickle

Date: 1997

Abstract: The power of human vision to synthesize information and recognize pattern is fundamental to the success of visualization as a scientific method. This same power can mislead investigators who use visualization to explore geo-referenced data - if data reliability is not addressed directly in the visualization process. Here, we apply an integrated cognitive-semiotic approach to devise and test three methods for depicting reliability of georeferenced health data. The first method makes use of adjacent maps, one for data and one for reliability. This form of paired representation is compared to two methods in which data and reliability are spatially coincident (on a single map). A novel method for coincident visually separable depiction of data and data reliability on mortality maps (using a color fill to represent data and a texture overlay to represent reliability) is found to be effective in allowing map users to recognize unreliable data without interfering with their ability to notice clusters and characterize patterns in mortality rates. A coincident visually integral depiction (using color characteristics to represent both data and reliability) is found to inhibit perception of clusters that contain some enumeration units with unreliable data, but to make it difficult for users to consider data and reliability independently.

Publication: (In Press) Environment and Planning: A

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Title: Mapping Health Statistics: Representing Data Reliability

Authors: MacEachren, Alan M., Cynthia Brewer, Linda Pickle

Date: 1995

Abstract: Data reliability is a major concern for both science and policy analysis. Methods of specifying the reliability of sample data, the variance around measures of central tendency, the confidence we should put in statistical summaries, etc. are well developed. When data are geo referenced, however, reliability estimates have not traditionally been mapped. For the same reasons that we map spatial data rather than limiting ourselves to tables or to numerical results of statistical analysis, we should portray data reliability in map form. This paper reports on the first stage of an effort to develop and assess reliability representation methods in the context of the U. S. National Center for Health Statistics Mortality Atlas.

Publication: Proceedings of the 17th International Cartographic Conference, September 3-9, 1995, Barcelona, Spain, pp 311-319.

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Title: Visualizing the health of the Chesapeake Bay: An uncertain endeavor.

Authors: MacEachren, Alan M., D. Howard, M. von Wyss, D. Askov, T. Taormino.

Date: 1993

Abstract: This paper reports on a prototype interactive exploratory spatial data analysis (ESDA) environment designed to facilitate incorporation of uncertainty estimates. The prototype is directed particularly to analysis of dissolved inorganic nitrogen in the Chesapeake Bay. Emphasis is placed on spatial, temporal, and attribute uncertainty issues inherent in collection and processing of space-time data (e.g., sampling, categorization, interpolation, spatial filtering, etc.). Two important questions related to uncertainty representation have been identified in previous research:

(a) which graphic variables are appropriate for showing different kinds of uncertainty

(b) what kind of user interface is most effective. The development platform for the ESDA project is IMSL/IDL, running under UNIX on Sun Sparcstations.

IDL provides a dynamic environment for addressing the above questions and for extending the first to dynamic as well as static variables.

Publication: GIS/LIS '93 Proceedings, Minneapolis, MN, pp 449 - 458.

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Title: Constructing and Evaluating an Interactive Interface for Visualizing Reliability

Authors: Howard, David and Alan M. MacEachren

Date: 1995

Publication: Proceedings of the 17th International Cartographic Conference, September 3-9, 1995, Barcelona, Spain, pp 320-329.

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Title: Visualizing Uncertain Information

Authors: MacEachren, Alan M.

Date: 1992

Abstract: When maps are used as visualization tools, exploration of potential relationships takes precedence over presentation of facts. In these early stages of scientific analysis or policy formulation, providing a way for analysts to assess uncertainty in the data they are exploring is critical to the perspectives they form and the approaches they decide to pursue. As a basis from which to develop methods for visualizing uncertain information, this paper addresses the difference between data quality and uncertainty, the application of Bertin's graphic variables to the representation of uncertainty, conceptual models of spatial uncertainty as they relate to kinds of cartographic symbolization, and categories of user interfaces suited to presenting data and uncertainty about that data. Also touched on is the issue of how we might evaluate our attempts to depict uncertain information on maps.

Publication: Cartographic Perspectives, vol. 13: pp 10-19.

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Title: Visualization quality and the representation of uncertainty

Authors: MacEachren, Alan M.

Date: 1991

Publication: NCGIA Specialist Meeting: Initiative 7, Visualization of Data Quality: Working Papers

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Title: Geographic Visualization: Designing Manipulable Maps for Exploring Temporally Varying Georeferenced Statistics.

Authors: MacEachren, Alan M., Boscoe, Frank, Haug, Daniel, and :ickle, Linda (in press)

Date: 1998

Publication: Proceedings, IEEE Symposium on Information Visualization, Oct. 19-20, 1998, Research Triangle Park, NC

Keywords: geographic visualization, information interfaces, animation, user centered design, prototyping, interaction styles, spatiotemporal data, exploratory data analysis, cartography, maps, computer aplications, health statistics

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