I-17 Specialist Meeting Report, Appendix D

NCGIA Technical Report 95-14

NCGIA Research Initiative 17: Collaborative Spatial Decision-Making
Scientific Report for the Specialist Meeting

continued
   Go to Table of Contents

   Go back to previous section


APPENDIX C.
INITIATIVE PROPOSAL TO NCGIA BOARD

Collaborative Spatial Decision-Making
Request for Approval in Detail

PROJECT SUMMARY

Many spatial problems are intrinsically complex and require an interdiciplinary approach to their solution. Consequently, individuals often collaborate on developing solutions to these problems, working as members of a committee or task force. It is in supporting this collaboration that existing spatial decision support systems are weakest: they are not designed explicitly to provide tools that enable groups to develop and evaluate alternative solutions to complex spatial problems. The purpose of this initiative, therefore, is to extend current conceptual frameworks for spatial decision support systems (SDSS) to help groups of decision-makers generate tractable solutions to ill-defined spatial problems. A specific point of emphasis will be placed on integrating SDSS with new computer supported cooperative work environments. Such environments enable groups of people to work together by providing a set of generic tools that handle many of the tasks that are required of group enterprises: exchange of textual, numerical and graphical information; and group evaluation, consensus building and voting. To be credible in supporting group problem-solving and decision-making, collaborative spatial decision-making (CSDM) systems must exhibit certain characteristics. Three focal areas for research are: first, how to encapsulate knowledge in SDSS to assist decision-makers in formulating alternative solutions to their problem; second, how to improve decision-makers' interaction with spatial analysis tools; and, finally, how to provide decision-makers with mechanisms for evaluating alternative solutions to a problem.

Ties to the NCGIA's Research Agenda

This proposed Research Initiative will contribute to the following areas identified in the NCGIA's Renewal Proposal to NSF:

1.2 Data Models for Geographic Information
1.5 Knowledge Representation
2.2 Exploratory Spatial Analysis
2.4 Spatial Models
3.1.1 Human-Computer Interaction
3.1.3 Spatial Decision Support Systems
3.3.2 Visualization Tools

Initiative Leaders

Paul Densham (Geography, SUNY-Buffalo)
Marc Armstrong (Geography, Iowa)
Frank Davis (Geography, UC-Santa Barbara)

Proposed Core Planning Group

Mike Batty *
Britton Harris *
Joe Ferreira *
Peter Nijkamp
Jay Nunamaker
Tim Nyerges
Jack Dangermond
(* indicates that we have approached this person and that they have given their consent.)

Disciplines to be Involved

Geography, Computer Science, Operations Research, Management Science, Planning, Psychology

Potential Center Participants

Batty (Geography, SUNY-Buffalo)
Buttenfield (Geography, SUNY-Buffalo),
Calkins (Geography, SUNY-Buffalo),
Mark (Geography, SUNY-Buffalo),
Church (Geography, UC-Santa Barbara),
Couclelis (Geography, UC-Santa Barbara),
Golledge (Geography, UC-Santa Barbara),
Lanter (Geography, UC-Santa Barbara)
Onsrud (Survey Engineering, Maine)
Pinto (Survey Engineering, Maine)

Timetable

Specialist Meeting: To be held immediately before GIS/LIS '94 (Phoenix, November, 1994).

Closing Session: To be held at GIS/LIS '96.

PROJECT DESCRIPTION
1. INTRODUCTION

The broad adoption of GIS technology has been fueled, in part, by its ability to support interdisciplinary approaches to spatial problem-solving. The traditional layered view of spatial data supported by GIS provides a means through which thematic data coverages can be integrated in a common spatial framework to support analyses conducted from different disciplinary perspectives. With such a repository of layered information in place, a host of powerful analytical operations can be brought to bear on spatially referenced data (e.g., Tomlin, 1990). GIS technology has been especially successful when these operations are applied to problems that are well understood -- problems with clearly defined questions and measurable outcomes. Many spatial problems, however, are not so straightforward. Consequently, spatial decision support systems (SDSS) have been developed to address ill-structured problems with spatial query, modelling and analysis, and display capabilities (Densham, 1991; Guariso and Werthner, 1989).

A mismatch exists, however, between the widespread single-user model of GIS and SDSS use and the group-based approach to decision-making that is often adopted when ill-structured public policy issues are addressed. SDSS-based spatial analysis and display methods must be expanded to encompass group decision-making processes, and new tools must be developed that will enable group members to generate, evaluate, and illustrate the strong and weak points of alternative scenarios and come to a consensus about how to proceed toward a decision.

2. OBJECTIVES

The five major objectives of the proposed Research Initiative on Collaborative Spatial Decision-Making are to:
  1. examine the body of theory on the design, implementation and use of computer supported cooperative work (CSCW) environments and evaluate its utility for GIS/GIA;
  2. identify impediments to the development of highly interactive, group-based spatial modelling and decision-making environments;
  3. develop methods for eliciting, capturing and manipulating knowledge bases that support individual and collective development of alternative solutions to spatial problems;
  4. develop methods for supporting collaborative spatial decision-making (CSDM), including methods for managing spatial models; and
  5. extend capabilities for supporting multicriteria decision-making in interactive, CSDM environments.

2.1 Computer supported cooperative work environments

Researchers in computer supported cooperative work (CSCW) have been concerned with the development of ways in which group members can interact to achieve goals using computer hardware and software (groupware) in much the same way that group business communication now takes place. Such interaction can be structured along both locational and temporal dimensions. In the temporal dimension, groupware may be applied either synchronously or asynchronously. In asynchronous mode (Greif and Sarin, 1987), group members use the system at different times, and post messages informing other members about what they have done and the current status of the decision process. In a synchronous application, on the other hand, the group meets and uses the system simultaneously, again, normally in a decision room (see Nunamaker et al., 1991). At present, this type of synchronous groupware is most commonly used.

Collective decision-making activities can be supported by enabling each member of a group to share a common view of a problem as they would when looking at a diagram on a chalkboard. Though this process is especially effective in decision room environments in which the participants are in close proximity (Desanctis and Gallupe, 1985), it can be extrapolated to environments in which the participants are dispersed if high bandwidth communication technology is available (see Newton, Zwart and Cavill, 1992).

Stefik et al. (1987) describe a decision room environment in which each participant in a group views the current state of the problem they are attempting to solve; in such WYSIWIS (What You See Is What I See) environments, each group member has a display (or views a collective display) that can be altered by other group members to reflect different views of a problem, and these modifications are then propagated to other displays. Several steps in the decision process have been observed when a WYSIWIS interface is supported (Stefik et al., 1987). The first is a free-form stage in which rough ideas are put before the group using a variety of computer tools (e.g. typing, drawing). In the second stage, ideas are sorted and evaluated as the plan begins to take shape. During this stage there is greater chance for conflict because specific aspects of alternatives are discussed, evaluated and possibly discarded. During the final stage, a plan is formalized and articulated through the system. These stages parallel closely those observed when an SDSS is used to solve a locational problem.

2.1.1 Group use of spatial decision support systems

When decision-makers use an SDSS they become involved in the process of seeking a solution, and they often generate and evaluate several scenarios that result from the application of models that employ different criteria or constraints. In this iterative process, they typically pass through several stages: Though we will focus on each of these stages and develop principles to guide the development of CSDM environments, we will place a specific emphasis on the second and third stages of group use of spatial decision support systems.

2.1.2 Scenario specification

Using locational decision-making as an example, the crux of the group decision-making process is the generation and presentation of alternative scenarios to group members. Each scenario that arises from suggestions made by members of a group is created from a sequence of actions. Consider, for example, the following sequence of steps that are performed when constructing a prototypical scenario:
  1. compute distances between locations,
  2. compute shortest paths,
  3. apply optimization software, and
  4. create maps and tables.
Each of these steps may be decomposed into a set of additional tasks, each of which may be the subject of group discussion (e.g. choice of a distance metric or objective function). The specification and creation of a scenario, therefore, normally requires that several computational steps be concatenated in a way that is satisfactory to one or more group members to produce a single desired result. Moreover, the decision-making style employed by SDSS users (successive refinement) means that these steps will need to be taken repeatedly as users generate and evaluate scenarios. Because of this, group SDSS software should enable users to produce and evaluate scenarios in both their intermediate and final forms. Existing systems, however, do not provide adequate support for groups to participate in these activities.

2.1.3 Scenario evaluation

When numerous scenarios are generated by group members, a mechanism must be established to provide them with a way of discriminating between alternatives. An effective system would provide at least three ways for making comparisons: statistical, visual and using methods of multi-criteria decision-making (MCDM). In each case, the process of comparing and evaluating scenarios can be supported most effectively in environments that permit decision-makers to evaluate collectively the alternatives under consideration by the group.

2.1.4 Conflict resolution

Because decision processes and methods vary among individuals, group decision support tools must not only enable group members to specify their preferences, but they must also enable them to highlight differences and similarities among alternative scenarios and resolve conflicts that will inevitably arise. Additional work also should determine the kinds of tools that are most effective in promoting discussion and in persuading opinion when problems are confronted by groups.

In CSDM, a scenario can be supported or objected to by other members of the group using statistical evidence (e.g. the value of an objective function), maps that illustrate the advantages or limitations of a scenario, knowledge about the problem domain and study area, or even intuition. Since haggling and discussion about the merits of scenarios are important aspects of decision-making, especially when there is no clear single "optimal" solution, the system must provide a way for decision-makers to interact with, and to redesign, alternatives.

In addition to a standard set of mapping and report generation tools, a free-form sketching facility would enable users to annotate and highlight specific aspects of a map or table to bring out salient problems or advantages of specific locational configurations in a scenario. When users are so empowered, solutions are no longer viewed with suspicion. At present, however, there is insufficient knowledge about the kinds of drawing tools that are best applied to highlight the salient characteristics of scenarios and differences among them.

Ultimately, when different positions are articulated by group members, an agreed upon process of resolving deadlocks must be implemented. This process itself may occur in stages and Nunamaker et al. (1991) describe several tools that can be used. Electronic questionnaires, for example, can be used to determine the degree and nature of disagreement among group members. A group matrix tool can be used to build consensus by enabling individuals to place their questionnaire responses in a group context. In a shared workspace, users are able to alter their responses in a matrix; these alterations are broadcast to other group members. Because these alterations are visible, group matrices are useful for promoting discussion about different positions. A person who holds a position contrary to others, but who may not have good support for it, also may decide to move with the consensus view when group matrix information is made available to them. Finally, different types of voting strategies (e.g. majority, plurality) can be used in cases where complete consensus cannot be established.

2.2 Impediments

Several impediments must be overcome before effective CSDM environments can be implemented. Research must be conducted into the design of user interfaces for the groupware tools described in the previous section. New technology and algorithms also must be developed and applied to support interaction and to meet the increased computational demands that will be created by group-based modeling, communication and display of spatial information.

2.2.1 User interfaces

The design of user interfaces that will effectively support group decision-making and enable individuals to resolve conflicts promises to be a challenging task. Designers concerned with single-user systems are finding that appropriate metaphors for interfaces (e.g. desktop, rooms) are difficult to specify for geographical domains (e.g. Kuhn, 1991; Kuhn, 1992; Mark, 1992). In addition to metaphors, interface designers must concern themselves with the set of tasks that must be accomplished by users. Task analysis (Rasmussen, 1986) and knowledge elicitation procedures (Greenwell, 1988) can be used to determine these required activities so that appropriate options are made available in a logical and consistent sequence for system users. The ultimate goal of these research and development activities is to provide interfaces that enable users with no prior collaborative experience to work together to solve complex locational problems.

For example, specific facility locations could be selected by pointing, and their positions could be dragged to show how an alternative configuration of supply would affect reassignment of demand. The magnitude and location of demand also could be altered, thus permitting decision-makers to evaluate the impact of development plans under different assumptions of growth or decline of demand for services. Other structures or metaphors will need to be developed for group SDSS applications.

A WYSIWIS system holds considerable promise in locational decision-making contexts, because maps are an essential and often requested SDSS decision aid (Armstrong et al., 1991; 1992). Decision-makers, for example, often wish to create maps that show an existing service system and the relationship between supply locations and demand for service. Solutions provided by spatial models (e.g. location-allocation) also are more easily interpreted when viewed as maps (Harris, 1988; Armstrong et al., 1992). Furthermore, maps serve as an effective and data-dense mechanism for exchange of locational scenarios, and consequently, they can serve as the basic "token" of interchange among locational decision-makers as they evaluate and compare scenarios and serve as an effective mechanism for promoting discussion of alternative results. They enable the outcome of a decision process to be modified by unmodeled aspects of the decision. Additional research, however, must be conducted to determine the kinds of map displays that are most effective in communicating spatial information to groups, and whether different kinds of maps are most effective during different stages of group decision-making.

2.2.2 System response

Decision-makers must be provided with the means to interact with problems in near-real-time so that they may visualize the effects of making adjustments to the parameters that define the solution space of a problem. Currently, locational models are so computationally intensive (Armstrong and Densham, 1992) that near-real-time interaction is precluded except for trivial or small problems. Instead, the state-of-the-practice is to create scenarios in what amounts to batch mode because realistic problems require several minutes of execution time, even on the current generation of high-end workstations. Research must be performed to determine how computer architectures can be exploited to improve performance to a level that is required to support true interactive modeling and design of service systems in a group SDSS environment. Such capabilities can be supported by multi-processor systems, in which different processors are assigned specific tasks (e.g. modeling with alternative criteria) that ultimately lead to the creation of a completed scenario. Alternatively, a single locational problem can be decomposed into a set of independent constituent parts to improve solution times through parallel processing (e.g. Armstrong and Densham, 1992). The use of coordinated ensembles of processors (Carriero and Gelernter, 1990; Karp et al., 1993) appears to be especially promising for parallel processing of locational problems. Note, however, that such ensembles will require greatly improved network bandwidth to be effective. Myers (1993) describes one ensemble, as a "metacomputer" that requires a one gigabit-per-second network to link heterogeneous computational resources.

When response times improve to permit real-time interaction, users will be able to manipulate directly two (or perhaps more) parameters or constraints much like a driver simultaneously releases the clutch and presses the accelerator in an automobile with a manual transmission (Armstrong, Densham and Lolonis, 1991). For example, in many analyses the imposition of a maximum travel distance constraint will lead to infeasibility of solutions when there are too few facilities to serve demand. By being able to visualize and evaluate the interplay between these two parameters and how it affects solutions (in this example the size and location of unserved areas), decision-makers will gain new insight into the nature of trade-offs in multi-objective decisions.

2.3 Knowledge-based systems

Although decision-makers are knowledgeable, they typically are not experts in methods of spatial analysis and decision analysis. Consequently, a CSDM environment must actively help decision-makers employ its often complex analytical and evaluative capabilities (Armstrong et al., 1990). One way to provide this assistance is to incorporate knowledge in a CSDM system.

Environmental knowledge describes the problem domain. While some environmental knowledge can be captured and represented within a system - including spatial relationships and patterns of spatial interaction - other forms of environmental knowledge are brought into the decision-making process by individuals - an understanding of the local political milieu, for example.

Procedural knowledge is domain-dependent knowledge which can be used to restrict the solution space that will be searched. Computer systems that successfully exploit procedural knowledge often are called "intelligent" and increasingly are used in diagnostic tasks ranging from medicine to automobile maintenance. In a spatial context, procedural knowledge can be used to select a general problem-solving strategy or a specific analytical approach.

Structural knowledge is used to reduce the amount of computation required when an algorithm is applied to a particular problem. Structural knowledge consists of representations of the spatial relationships which are being analysed; exploiting this structure can reap large savings in computation.

To build knowledge-based CSDM environments, we must answer four questions:

In a CSDM system, procedural and structural knowledge can be used to help decision-makers select from the analytical methods and spatial models incorporated in the system. This knowledge also can be used to organize the representation and storage of spatial modelling capabilities.

2.4 Collaborative spatial modeling

Complex spatial problems often contain aspects that are poorly defined. This lack of structure makes it difficult for individuals to understand the relationships among different components of a problem. Individual decision-makers often adopt problem-solving strategies that are consistent with their experiences, problem-solving style, and organizational context. Furthermore, a decision-maker may find that their objectives for a solution conflict with each other and with the objectives of other decision-makers. Consequently, individuals may wish to investigate different aspects of the problem using their own problem-solving strategies. Consider, for example, a decision-maker who wants to know the effects of relocating a school. Systems that support analyses of this type can be very difficult to use because they are oriented more towards the expert locational analyst than the knowledgeable decision-maker. Human-computer interaction would be enhanced greatly if each user could articulate their ideas about alternative locations by interacting directly with graphical representations of their problem, such as dragging the symbol for the school to different locations on the map and watching the system enumerate and display the changes in real time. In visual interactive modelling environments of this kind, tabular views linked to map windows will help groups of decision-makers understand and reconcile depictions of spatial pattern with statistical reports about locational configurations.

Supporting visual interactive modelling for groups requires a fresh approach to the design, representation and implementation of spatial models. One approach is to develop a model base management system (MBMS) that enables users to access spatial modelling capabilities and to combine them in flexible sequences (Densham, 1991). In a MBMS, models typically are reduced to some set of atomic components which can be stored, manipulated, and recombined to yield the original algorithms. If they can be made independent of each other, model atoms can be combined in new ways. The ability to combine atoms in a flexible manner greatly extends the capabilities of the model base. Moreover, defining procedural knowledge for atoms is much simpler than for whole algorithms. The design and implementation of MBMS for CSDM environments raises several questions:

2.5 Evaluating alternative solutions

CSDM systems provide capabilities that enable individual decision-makers to place different degrees of emphasis on the various components of a problem and to generate a large number of alternative scenarios. For example, changing the weighting strategies applied to the individual layers in a GIS yields numerous different results in an overlay operation. Decision-makers require methods for evaluating their own scenarios and for comparing them with those generated by other decision-makers. A large and mature literature exists on the application of methods of decision analysis and multi-criteria decision-making. Although this literature addresses the use of methods in both individual and group decision-making contexts, it has largely been ignored by the developers of GIS and SDSS software - a few notable exceptions include Carver (1991) and Eastman et al. (1993). The incorporation of these methods in CSDM systems raises a series of fundamental questions:

3. PLANS FOR THE INITIATIVE

3.1 Progress with the Initiative to date

The initiative is at an early stage of planning: approval in principle was granted at the June, 1993, Board Meeting.

3.2 Suggestions for substantive research activities following the Specialist Meeting

We have identified four areas of research for which substantive results are required to support the development of CSDM environments. We anticipate that these four areas also will be identified at the Specialist Meeting. These four areas are: the development of a metaplanning capability; strategies for the design and implementation of a MBMS; the design and implementation of components for a group-based user interface; and the identification, selection and incorporation of methods for resolving spatial conflicts.

3.2.1 The metaplanner

In a CSDM environment, methods for representing procedural and structural knowledge are required to make the system accessible to a diverse group of users. While some of this knowledge will be generic, other types of knowledge will be domain-specific requiring the selection of several application areas for study. We intend to continue our work in locational and environmental modelling (Armstrong et al., 1991; DePinto et al., 1994; Honey et al., 1991; Malanson et al., 1993) but other areas may be identified at the Specialist Meeting. A key aspect of the metaplanner will be its scenario management capabilities. There are two components to this capability. First, maintaining information about the lineage of a scenario's development (Lanter, 1991) (which we refer to as intra-scenario management) and, second, tracking group responses and modifications to a scenario when it is made available to the group (inter-scenario management).

3.2.2 Modelbase management systems

Several strategies have been developed for the construction of MBMS. In a CSDM environment, two levels of decomposition must be considered. First, decomposition of individual models and algorithms at the atomic level is required. This decomposition identifies those elements of models and algorithms that are held in common and can be shared. A second level of decomposition is required for heterogeneous processing environments because individual components of the modelbase must be matched to the most appropriate architecture in the available suite (Densham and Armstrong, 1993). While these two types of decomposition are not independent, decomposition to the atomic level must be completed before suitability of an appropriate architecture can be determined.

3.2.3 User interfaces

Methodologies for the design of user interfaces include task analysis (Rasmussen, 1986). Task analysis is used to decompose a user's actions into a set of modular elements that can be design the commands and options made available in the user interface. Though some of these user actions will be generic, other actions will be specific to a particular situation. Several application areas will be studied to determine which user actions are performed repetitively across different application areas and, consequently, should be included in all CSDM environments. An allied question relates to cartographic displays: which types of display transcend particular applications and should be considered core displays for CSDM environments?

3.2.4 Spatial conflict resolution

We have identified a nascent literature on the integration of methods of MCDM with GIS and SDSS. We will survey this literature and the literatures of the decision sciences to determine which methods of MCDM hold particular promise for use in CSDM environments.

3.3 Research infrastructure

Research into CSDM environments and their constituent parts requires a laboratory in which to develop and evaluate prototypes. At NCGIA Buffalo, networks of Sun Workstations, IBM compatible PCs, and Macintoshes are available; IBM RS 6000 Workstations and IBM compatible PCs can be used for this purpose at The University of Iowa and at NCGIA Santa Barbara. We have worked with several programming tools that can be used to build CSDM environments at the most basic level: PCS-Linda is a parallel processing environment for networks of PCs, Sun and RS 6000 versions are available; Mosaic is a distributed multi-media development tool for systems running X Windows available from NCSA (Macintosh and Windows versions also are available); all three sites also have access to ARC/INFO which now has the capability to display the same image on multiple networked workstations. Technology is changing rapidly and the selection of an appropriate environment would be premature at this juncture.

REFERENCES

Armstrong, M.P., Densham, P.J. and Lolonis, P. (1991) Cartographic visualization and user interfaces in spatial decision support systems. Proceedings of GIS/LIS `91, Volume 1, Bethesda, MD: American Congress on Surveying and Mapping, pp. 321-330.

Armstrong, M.P., De, S., Densham, P.J., Lolonis, P., Rushton, G. and Tewari, V. (1990) A knowledge based approach for supporting locational decision-making. Environment and Planning B: Planning and Design, 17: 341-364.

Armstrong, M.P., Rushton, G., Honey, R., Dalziel, B.T., Lolonis, P., De, S., and Densham, P.J. (1991) A decision support system for regionalizing service delivery systems. Computers, Environment and Urban Systems, 15 (1), 37-53.

Armstrong, M.P. and Densham, P.J. (1992) Domain decomposition for parallel processing of spatial problems. Computers, Environment and Urban Systems, 16 (6), 497-513.

Armstrong, M.P., Densham, P.J., Lolonis, P., and Rushton, G. (1992) Cartographic displays to support locational decision-making. Cartography and Geographic Information Systems, 19 (2), 154-164.

Carriero, N. and Gelernter, D. (1990) How to Write Parallel Programs: A First Course. MIT Press, Cambridge, MA.

Carver, S.J. (1991) Integrating multi-criteria evaluation with geographical information systems. International Journal of Geographical Information Systems, 5(3), 321-339.

Conklin, J., and Begeman, M.L. (1988) gIBIS: A hypertext tool for exploratory policy discussion. ACM Transactions on Office Information Systems, 6 (4), 303-331.

Densham, P.J. (1991) Spatial decision support systems. In D.J. Maguire, M.F. Goodchild and D.W. Rhind (eds) Geographical Information Systems: Principles and Applications, Longman, London, pp. 403-412.

Densham, P.J., and Armstrong, M.P. (1993) A Heterogeneous Processing Approach to Spatial Decision Support Systems. Manuscript available from the authors.

DePinto, J.V., H.W. Calkins, P.J. Densham, J. Atkinson, W. Guan and H. Lin (1994) Development of GEOWAMS: an approach to the integration of GIS and watershed analysis models. GIS and Civil Engineering, forthcoming.

DeSanctis, G., and Gallupe, B. (1985) Group decision support systems: a new frontier. Data Base, 16 (2), 3-10.

Eastman, J.R., Kyem, P.A.K., and Toledano, J. (1993) A procedure for multi-objective decision making in GIS under conditions of competing objectives. Proceedings, EGIS'93, 438-447.

Greenwell, M. (1988) Knowledge Engineering for Expert Systems. Ellis Horwood, Chichester.

Greif, I., and Sarin, S., (1987) Data sharing in group work. ACM Transactions on Office Information Systems, 5 (2), 187-211.

Greif, I. (1988) Computer-Supported Cooperative Work: A Book of Readings. Morgan Kaufman Publishers, San Mateo, CA.

Grudin, J. (1990) Groupware and cooperative work: Problems and prospects. In Laurel, B. (ed.) The Art of Human-Computer Interface Design. Addison-Wesley, Reading, MA, pp. 171-185.

Guariso, G., and Werthner, H. (1989) Environmental Decision Support Systems. John Wiley, New York, NY.

Harris, B. (1988) Prospects for computing in environmental and urban affairs. Computers, Environment and Urban Systems, 12 (1), 3-12.

Honey, R., Rushton, G., Armstrong, M.P., Lolonis, P., Dalziel, B.T., De, S. and Densham, P.J. (1991) Stages in the adoption of a spatial decision support system for reorganizing service delivery regions. Environment and Planning C: Government and Policy, 9 (1), 51-63.

Karp, A.H., Miura, K., and Simon, H. (1993) The 1992 Gordon Bell prize winners: Judges summary. IEEE Computer, 26 (1), 77-82.

Kaplan, S.M., Carroll, A.M. and MacGregor, K.J. (1991) Supporting collaboration processes with ConversationBuilder. ACM SIGOIS Bulletin, 12 (2&3), 69-79.

Kuhn, W. (1991) Are displays maps or views? Proceedings of the Tenth International Symposium on Computer-Assisted Cartography. American Congress on Surveying and Mapping, Bethesda, MD, pp. 261-274.

Kuhn, W. (1992) Paradigms of GIS use. Proceedings of the Fifth International Symposium on Spatial Data Handling. IGU Commission on GIS, Columbia, SC, pp. 91-103.

Lai, K., Malone, T., and Yu, K. (1988) Object Lens: A "spreadsheet" for cooperative work. ACM Transactions on Office Information Systems, 6 (4), 332-353.

Lanter D.P. (1991) Design of a lineage-based meta-data base for GIS. Cartography and Geographic Information Systems, 18 (4), 255-261.

Laurel, B. , ed. (1990) The Art of Human-Computer Interface Design. Addison-Wesley, Reading, MA.

Malanson, G.P., Armstrong, M.P. and Bennett, D.A. (1993) Fragmented forest response to climatic warming and disturbance. In press, Proceedings of the Second International Conference on Integrating Geographic Information Systems and Environmental Modeling, Breckenridge, CO, September.

Mark, D.M. (1992) Spatial metaphors for human-computer interaction. Proceedings of the Fifth International Symposium on Spatial Data Handling. IGU Commission on GIS, Columbia, SC, pp. 104-112.

Myers, W. (1993) Supercomputing 92 reaches down to the workstation. IEEE Computer, 26 (1), 113-117.

Newton, P.W., Zwart, P.R. and Cavill, M.E. (1992) Networking Spatial Information Systems. Bellhaven Press, New York, NY.

Nunamaker, J.F., Dennis, A.R., Valacich, J.S., Vogel, D.R., and George, J.F. (1991) Electronic meeting systems to support group work. Communications of the ACM, 34 (7), 40-61.

Press, L. (1992) Dynabook revisited- portable computers past, present and future. Communications of the ACM, 35 (3), 25-32.

Rasmussen, J. (1986) Information Processing and Human Machine Interaction: An Approach to Cognitive Engineering. North-Holland, New York, NY.

Stefik, M., Foster, G., Bobrow, D.G., Kahn, K., Lanning, S., and Suchman, L. (1987) Beyond the chalkboard: Computer support for collaboration and problem solving in meetings. Communications of the ACM, 30 (1), 32-47.

Tomlin, C.D. (1990) Geographic Information Systems and Cartographic Modeling. Prentice Hall, Englewood Cliffs, NJ.


   Go to Table of Contents


Posted April 3, 1996

Comments to Karen Kemp