The ultimate objective of all geospatial data and technologies, after all, is to produce knowledge. Most of us are interested in data only to the extent that they can be used to help understand the world around us, and to make better decisions. Decision making processes vary a lot from one organization to another. In general, however, the first steps in making a decision are to articulate the questions that need to be answered, and to gather and organize the data needed to answer the questions (Nyerges & Golledge, 1997).
Geographic data and information technologies can be very effective in helping to answer certain kinds of questions. The expensive, long-term investments required to build and sustain GIS infrastructures can be justified only if the questions that confront an organization can be stated in terms that GIS is equipped to answer. As a specialist in the field, you may be expected to advise clients and colleagues on the strengths and weaknesses of GIS as a decision support tool. To follow are examples of the kinds of questions that are amenable to GIS analyses, along with questions that GIS is not so well suited to help answer.
Questions concerning individual geographic entities
The simplest geographic questions pertain to individual entities. Such questions include:
Questions about space
- Where is the entity located?
- What is its extent?
Questions about attributes
- What are the attributes of the entity located there?
- Do its attributes match one or more criteria?
Questions about time
- When were the entity's location, extent or attributes measured?
- Has the entity's location, extent, or attributes changed over time?
Simple questions like these can be answered effectively with a good printed map, of course. GIS becomes increasingly attractive as the number of people asking the questions grows, especially if they lack access to the required paper maps.
Questions concerning multiple geographic entities
Harder questions arise when we consider relationships among two or more entities. For instance, we can ask:
Questions about spatial relationships
- Do the entities contain one another?
- Do they overlap?
- Are they connected?
- Are they situated within a certain distance of one another?
- What is the best route from one entity to the others?
- Where are entities with similar attributes located?
Questions about attribute relationships
- Do the entities share attributes that match one or more criteria?
- Are the attributes of one entity influenced by changes in another entity?
Questions about temporal relationships
- Have the entities' locations, extents, or attributes changed over time?
Geographic data and information technologies are very well suited to answering moderately complex questions like these. GIS is most valuable to large organizations that need to answer such questions often.
Questions that GIS is not particularly good at answering
Harder still, however, are explanatory questions--such as why entities are located where they are, why they have the attributes they do, and why they have changed as they have. In addition, organizations are often concerned with predictive questions--such as what will happen at this location if thus-and-so happens at that location? In general, commercial GIS software packages cannot be expected to provide clear-cut answers to explanatory and predictive questions right out of the box. Typically, analysts must turn to specialized statistical packages and simulation routines. Information produced by these analytical tools may then be re-introduced into the GIS database, if necessary. Research and development efforts intended to more tightly couple analytical software with GIS software are underway within the GIScience community. It is important to keep in mind that decision support tools like GIS are no substitutes for human experience, insight, and judgment.
At the outset of the chapter, I suggested that producing information by analyzing data is something like producing energy by burning coal. In both cases, technology is used to realize the potential value of a raw material. Also, in both cases, the production process yields some undesirable by-products. Similarly, in the process of answering certain geographic questions, GIS tends to raise others, such as:
- Given the intrinsic imperfections of the data, how reliable are the results of the GIS analysis?
- Does the information produced through GIS analysis tend to systematically benefit some constituent groups at the expense of others?
- Should the data used to make the decision be made public?
- Does the use of GIS affect the organization's decision-making processes in ways that are beneficial to its management, its employees, and its customers?
As is the case in so many endeavors, the answer to a geographic question usually includes more questions.
Can you cite an example of a "hard" question that you and your GIS system have been called upon to address? Registered students are welcome to post comments to the Discussion Forum in the Chapter 1 module in Canvas.