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The conceptual model takes analysis goals from reality to a spatial conceptualization. In accomplishing this task, the key components of the analysis are determined and the appropriate data identified. To illustrate the process of conceptualization, consider as an example the accessibility of prenatal care for low-income families at public health clinics.

A number of datasets would be useful in an analysis of this sort. The conceptualization phase is the point at which you begin to identify appropriate data by working through the “thought problem” of your analysis. Identifying data layers involves more than simply determining “I need a layer ‘X’ for my study”; it also includes specifications regarding what must be in the database to complete your analysis.

In this example, what data do you need? You need some demographic information, perhaps from the most recent US Census, which should give you some sense of socioeconomic characteristics as well as the location of these characteristics (to the census block level). A map of clinic locations is also essential. If no such map exists in a GIS format, you will need to explore other options for creating this layer (e.g., geocoding an existing map by street address). If detailed information about clinics exists, it may be possible to more specifically identify those in the database that provide prenatal care services. If the data on clinics do not exist, you will need to do some field research to create your own database.

Don’t forget a basemap; you will need to determine an appropriate scale for the analysis. Are you studying clinics in one city, an entire region, or an entire nation? For this example, assume a local-level study. Perhaps a city street map from a local city or county planning department would be most appropriate and up to date.

As a last, and likely most conceptually difficult, step, you will need to develop a working definition of accessibility that you can use throughout your study. We propose a few possibilities here, but in all likelihood, you could include additional conceptualizations in your analysis. One aspect of accessibility is related to transportation. You might expect a significant number of individuals in this study to rely on public transportation to get to the clinic, so route maps and schedules could be important data. Additionally, there may be time-related accessibility issues, such as work schedules, the ability to take time off from work, school start and release times, and so on. How do these time and transportation issues relate to where the clinics are located and open? All of these issues have a social-psychological component related to an individual’s willingness to go to the trouble of getting to the clinic. How far are prospective clients willing to travel, and how much time are they willing or able to spend in actually going to the clinic?

The list could go on to consider accessibility related to knowledge. Do the prospective clients of the clinics know the clinics are available? Are clinic staff members fluent in the appropriate languages for the populations they serve? Are printed materials at an accessible reading level for the clients? What about funding for the clinic? Can the clinic handle the demand? How long are people kept in the waiting room? Do clients know what health coverage is available to them, and can they navigate the paperwork to get it? Suddenly, what at first may seem like a simple concept rapidly balloons into something very complicated; of course, this is the nature of social science research.

In this laundry list of concepts, many are spatial, particularly those related to where the client base is located and how people will get to the clinic. Are people likely to be coming from their homes or from their workplaces? When looking at the willingness to travel, it might be possible to develop some values that make sense. For example, if you determined that a person would be willing to travel for one hour on public transportation, you could convert that time into a map of bus routes that are within one hour of clinics. In this way, the concept of willingness (with a series of variables that inform that concept) is operationalized into a map with a distinct spatial component. In other words, the GIS is used to integrate a set of concepts into something we can more easily analyze.

When going through thought exercises such as this one, it is sometimes helpful to sketch a figure or write an outline about your concept. Having a picture of your concept provides a framework of other important information, such as the type and source of the data you will need to create or find to complete your study. If the conceptualizations of your analysis result in datasets that cannot be located from an existing source, you will have a better sense of how much new data collection will be required.

This is also a good time to assess the feasibility of the study. Taking time to reevaluate each component of your developing model early can save a significant amount of time, money, and energy later in the analysis. After all, there is no sense in incorporating data that contribute only minimally to the overall model or that will present significant uncertainty in the final results. As in any study, relationships between variables should make sense, not just conceptually, but also practically. Some possible questions you might consider at this point are as follows:

Will the results of the model be useful?

Can actual, on-the-ground decisions be implemented based on results of the model?

Are the relationships in the data statistically significant?

Once you have considered each component, data availability or your ability to create it, and the overall use of the model, you are ready to move beyond thought problems. But remember, until you complete the thought problem, it is probably not a good idea to go rushing forward with a GIS analysis. As mentioned earlier, many people gloss over this stage of the GIS process and end up going down dead-end analysis pathways that result in wasted time, money, and effort. Once you are content with your conceptual model (figure 2.7), then you are ready to move on to the third phase of abstraction: the logical data model.

Figure 2.7 Sketching out the components of the conceptual model can greatly assist in identifying and organizing the information that will be necessary to complete a GIS analysis.

Defining terms or concepts is essential to developing a sound research project. This is especially true for names used to refer to phenomena. We advise you to conduct a complete literature review before beginning any type of research project to ensure you are aware of how different words are defined by others. It is likely that any concept you might want to name or investigate has a given name, and many concepts have multiple and, sometimes, competing definitions. The first step is to identify your concept, name it, and then define it. A literature review helps one to better understand the relationships that exist between different variables. Once you have identified your dependent variable, a literature review will further assist in explaining the relationships between the different variables. This is especially useful when you explore relationships between variables that have not been examined in the past. Once you have accomplished all of this, you are ready to plan your analytical approach.