CaGIS vol. 32, no. 2

April 2005

Geovisualization and GIScience

Menno-Jan Kraak and Alan M. MacEachren

Today it is recognized that we can no longer rely upon uni-disciplinary solutions for our most pressing geo-problems. The hard problems require multiple perspectives and different types of expertise. This is reflected in the names and activities of organizations and journals. This journal has evolved, in both name and perspectives, from The American Cartographer via Cartography and Geographic Information Systems into its current shape as Cartography and Geographic Information Science (CaGIS). Similarly, the International Cartographic Association (for which this journal is one of three official outlets) has recently decided to add “The International Society for Cartography and Geographic Information Science” as a subtitle to its name. Over the years, the ICA Commission on Visualization and Virtual Environments has worked together with other disciplines such as those related to scientific visualization and computer graphics (through the SIGGRAPH CartoProject led by Theresa-Marie Rhyne http://www.siggraph.org/~rhyne/carto/ ) and information visualization (through a workshop at City University in London that resulted in the recently published edited collection, Exploring Geovisualization).

These ICA Commission activities and related developments have culminated in the term “Geovisualization” and have resulted in the Commission-led international and multidisciplinary research agenda which was published as a special issue of this journal in 2001 (MacEachren and Kraak 2001) . Geovisualization can be described as a loosely bounded domain that addresses the visual exploration, analysis, synthesis, and presentation of geospatial data by integrating approaches from cartography with those from other information representation and analysis disciplines, including scientific visualization, image analysis, information visualization, exploratory data analysis, and GIScience (Dykes et al. 2005).

This special issue is a representation of the Commission’s recent activities toward GIScience. It is derived from Commission-sponsored activities included in the GIScience 2004 Conference.

Three of the four papers were given as oral presentations in the main conference and one at the Commission’s pre-conference workshop. The former derive from extended abstracts included in the GIScience proceedings. All reflect work in progress related to goals outlined in the Commission’s 2001 research agenda.

Geovisualization is becoming a diverse, multidisciplinary field of research and practice. The breadth of research issues was articulated in a 2001 international, multidisciplinary research agenda report published in CaGIS (MacEachren and Kraak 2001). In that report, four cross-cutting themes were articulated:

• To develop the understanding and integrated technologies that make it possible to take advantage of the potential offered by increasingly experiential representation technologies.

• To develop extensible methods and tools that enable understanding of, and insight to be derived from, the increasingly large and complex geospatial data sets becoming available.

• To develop a new generation of geovisualization methods and tools that support group work.

• To develop a human centered approach to geovisualization.

The papers making up this issue reflect each of these themes, and they represent the multidisciplinary perspective on geovisualization fostered by the ICA Commission.

The paper by Döllner, a computer scientist, addresses aspects of theme one. He focuses on strategies for controlling usage of 3D virtual spaces by means of constraints on navigation through the space. The application domain is 3D city models. Much of the focus is on spatial and structural constraints on what can be viewed and how the 3D space can be navigated. Beyond these issues, however, Döllner addresses an additional category of constraints that goes beyond the themes in the 2001 research agenda and which directly relate to other activities in GIScience —constraints associated with digital rights management (ways to govern and authorize the distribution and use of content and services).

Shafer and colleagues (a team of information scientists) consider web-based, visual methods and tools to enable community collaboration. Their work emphasizes synchronous geocollaboration and draws upon and extends recent developments in computer-supported cooperative work. Specifically, they review recent geocollaboration software projects. The emphasis is on the first author’s dissertation research and on a commercial system with which another author is affiliated. Using these examples as a base, they outline a set of core design issues for map-based, synchronous, web-based, geocollaboration tools.

The paper by Ahonen-Rainio and Kraak (both cartographers) relates to the themes two and four, that is, extraction from complex data sets and human-centered approaches to geovisualization, respectively. The authors focus on the application of interactive visualization methods to understanding the multiple components of metadata needed to determine suitability of data sets for particular categories of use. Their visualization approach integrates traditional cartographic representations with multivariate visualization methods derived from exploratory data analysis and information visualization.

Guo and colleagues (all geographers) address the second theme. Their focus is on the development and application of methods and tools for knowledge construction from large, multivariate geospatial data sets. Specifically, they detail their work on the development and application of an integrated visual-computational environment for multivariate data analysis. The environment they describe applies cartographic insights on bivariate color schemes to a dynamically linked set of tools that include a map, SOM, and parallel coordinate plots that depict results of computational clustering. Their application focus is cancer data analysis.

REFERENCES

Dykes, J., A. M. MacEachren, and M.-J. Kraak. (eds). 2005. Exploring geovisualization. Amsterdam: Elsevier.

MacEachren, A. M. and M.-J. Kraak. 2001. Research challenges in geovisualization. Cartography and Geographic Information Science 28(1): 3-12.

Constraints as Means of Controlling Usage of Geovirtual Environments

Jürgen Döllner

In this paper a concept for controlling the usage of geovirtual environments by means of constraints is developed. Constraints serve to improve the usability of geovirtual environments by guarding the navigation and interaction processes of users. In addition, they facilitate the implementation of Digital Rights Management for geovirtual environments. The presented approach distinguishes spatial constraints, structural constraints, and redistribution constraints. Several types of spatial constraints have been identified for navigation in geovirtual environments. To demonstrate their applications, this paper reports on using constraints in virtual 3D city models.

Keywords: Geovirtual environments, geovisualization, 3D maps, 3D city models, navigation, user guidance, usability, constraints

Designing the Next Generation of Distributed, Geocollaborative Tools

Wendy A. Schafer, Craig H. Ganoe, Lu Xiao, Gabriel Coch, and John M. Carroll

Geocollaboration is a new field of research that investigates how technology can support human–human collaboration with geospatial information. This paper considers the design issues inherent in distributed geospatial software. It looks at providing a non-spatial communication channel, supporting real-time synchronous awareness, designing interaction techniques, establishing common ground, and using floor control and attention techniques. Using examples from existing geocollaboration tools and realistic geocollaboration scenarios, it demonstrates some of the design alternatives for geocollaboration. The paper concludes with a future research agenda describing the complexities in supporting longer-term geocollaboration activities.

Deciding on Fitness for Use: Evaluating the Utility of Sample Maps as an Element of Geospatial Metadata

Paula Ahonen-Rainio and Menno-Jan Kraak

Metadata that describe characteristics of geographic datasets are used to discover potential datasets and evaluate their suitability for intended purposes. Here sample maps are suggested as tools for evaluating datasets. Their usefulness in this process was studied as part of a wider research on visualization of geospatial metadata. First, design concepts were tested with twelve subjects who commented different static presentations of sample maps and multivariate visualizations. Then a prototype of an interactive metadata environment composed of sample maps, textual metadata documents, and a parallel coordinate plot was tested with eighteen subjects whose task it was to select the most suitable dataset from among six alternatives each of which represented the same theme. The subjects determined suitability within a use scenario. The prototype proved to be a valuable tool in the evaluation process, especially because multiple maps could be compared.

Multivariate Analysis and Geovisualization with an Integrated Geographic Knowledge Discovery Approach

Diansheng Guo, Mark Gahegan, Alan M. MacEachren, and Biliang Zhou

The discovery, interpretation, and presentation of multivariate spatial patterns are important for scientific understanding of complex geographic problems. This research integrates computational, visual, and cartographic methods together to detect and visualize multivariate spatial patterns. The integrated approach is able to: (1) perform multivariate analysis, dimensional reduction, and data reduction (summarizing a large number of input data items in a moderate number of clusters) with the Self-Organizing Map (SOM); (2) encode the SOM result with a systematically designed color scheme; (3) visualize the multivariate patterns with a modified Parallel Coordinate Plot (PCP) display and a geographic map (GeoMap); and (4) support human interactions to explore and examine patterns. The research shows that such “mixed initiative” methods (computational and visual) can mitigate each other’s weakness and collaboratively discover complex patterns in large geographic datasets, in an effective and efficient way.

KEYWORDS: Spatial data mining, geovisualization, self-organizing map (SOM), multidimensional visualization, multivariate mapping, bivariate color scheme