Geographic information science (GIScience) has three common definitions. This tutorial will focus on the first of these three definitions:
- GIS as a tool in scientific inquiry: The use of geographic information systems (GIS) to provide "insight, explanation, and understanding" in "supporting those sciences for which geography is a significant key" (Goodchild 1992)
- The Science of GIS: The exploration of scientific questions about GIS that are "generic, rather than specific to particular fields of application and particular contexts" (Goodchild 1992)
- Information Science: A related definition sees GIScience as a subfield of information science, which is " the science and practice dealing with the effective collection, storage, retrieval, and use of information." (Saracevic 2009). This begins to touch on the emerging field of data science
Geographic Information Systems
Defining GIScience in terms of GIS requires defining GIS.
Geographic information systems (GIS) are computer systems used for capturing, storing, processing, analyzing, and communicating geospatial data. GIS is a specific type of information technology (IT).
GIS is the use of information technology to store information about what is where.
Defining GIScience as the use of GIS in scientific inquiry requires defining what science is.
Science is a political term that has a wide variety of meanings in common usage. However, for the purposes of this tutorial science will be defined as knowledge or a system of knowledge covering general truths or the operation of general laws especially as obtained and tested through scientific method (Merriam-Webster 2019).
The key terms in that definition are scientific method and general truths.
The Scientific Method
Science as an activity is often performed using the scientific method (more-formally known as the hypothetico-deductive model) which is principles and procedures for the systematic pursuit of knowledge involving:
- The recognition and formulation of a problem
- The collection of data through observation and experiment
- The formulation and testing of hypotheses
The successful end of this process is a new, updated, or corroborated theory, which is a plausible or scientifically acceptable general principle or body of principles offered to explain phenomena.
General vs. Specific Knowledge
Specific knowledge is knowledge restricted to a particular individual, situation, relation, or effect.
In contrast, general knowledge is knowledge involving, relating to, or applicable to every member of a class, kind, or group.
While GIS is used to answer specific questions about what is where, GIScience deals with general questions about why is it there, or what general knowledge the spatial distribution of a phenomena tells us about that phenomena.
For example, GIS was used in the Long Island Breast Cancer Study Project (LIBCSP) to explore the unusually high breast cancer rates on Long Island, NY. In it's simplest usage, GIS was used to create maps of specific information about what is where like this map of cancer rates relative to the rest of the state:
However, what is more important is general information about why is it there: why are breast cancer rates high, and what can be done to reduce those rates?
Continuing the example above, Long Island is the home of numerous industrial sites from the past and present that have released toxic chemicals into the environment. Again, this is specific information about what is where that can be mapped:
One hypothesis was that these chemicals were a significant cause of breast cancer. However, using GIS and other statistical techniques with survey data to test that hypothesis, the study did not find a clear link (general knowledge) between levels of hazardous chemicals and breast cancer levels.
What the study did find is that women on Long Island had higher prevalence of other known risk factors (general knowledge), such as having children later in life, high alcohol consumption, and family history of breast cancer. (Maurer Foundation 2012).
Inductive vs Deductive Research
The relationship between the general and the specific goes in two directions, and there are two broad research approaches to dealing with general truths and the specifics of particular geographic situations (Trochim 2006):
- Inductive research starts with specific situations and seeks to infer general theories that can be applied in other times and places other than the specific situations being studied
- Deductive research starts with existing general theories and investigates whether those theories explain what is happening in a specific situation being studied
The Long Island breast cancer study described above is an example of deductive research: starting with general information about known possible causes like carcinogenic chemicals and lifestyle risk factors, and testing to see if those explained the specific patterns of breast cancer rates seen on Long Island.
In contrast, an example of inductive research is a study by Athas et al (2000) studied women in New Mexico who had breast cancer surgery (specific information) and used GIS to determine how far the women lived from a radiotherapy center where they could get follow-up radiation treatment. The researchers found that the farther a woman lived from the center, the less likely she was to get treatment (general information).
In a case like this where there were a large number of points, and privacy concerns for the women being studied, a map would not be useful or appropriate. In this case a graph of a mathematical model comparing distance (x-axis) with likelyhood of getting treatment (y-axis) was a more-effective visualization.
Exploratory Data Analysis
The idealized world of the scientific method is question-driven, with the collection and analysis of data determined by questions and hypotheses.
However, in some cases, especially at the early states of research, a data-driven approach may be more appropriate. This reverses the question-driven process, with the data coming first and animating a process of exploratory data analysis:
The ability to create maps with geospatial data facilitates quick visualization to observe spatial patterns, such as clusters, that raise questions and offer options for building hypotheses.
One common technique used with point data like crime or disease is the creation of heat maps. In such cases, there are often too many points to make pattern recognition possible.
However, heat maps show areas where there are high spatial concentrations (clusters) of activity. While observation of these clusters by themselves may not have clear significance, identification of clusters along with other spatial information, or simply from personal knowledge, can inform specific interventions, or general theories of the causes (and solutions) to the problems causing such clusters.
There are also statistical mapping techniques like hot-spot analysis using the Getis-Ord GI* algorithm to identify hot-spots and cold-spots where the concentration of points is higher or lower, respectively, from what might be expected from a purely random distribution of points.
Research Proposals and Reports
Science involves research, and research involves documentation at all stages of the process.
Research proposals describe planned research and research reports describe completed research. Proposals and reports for research involving geospatial data come in a wide variety of different structures and styles, but these documents commonly have some variant on the following sections.
- Introduction: This section gives a general introduction to the research topic, background on the motivations that led to the research.
- Literature Review: A summary of existing research on the topic. Researchers commonly seek to identify gaps in the literature that they can fill with new research.
- Study Area: For research that focuses on specific geographical areas, an overview of the history and significant characteristics of the area is useful for readers unfamiliar with that area.
- Question and Hypothesis: This section poses the question(s) that the research hopes to answer. It also then suggests hypotheses of what the answer to those question(s) might be. The research then involves the testing of those hypothesis to either corroborate or falsify them. These elements are sometimes included in the introduction.
- Methods and Data Sources: A description of the sources of data used in the research and the methods that will be used to analyze that data. This section also includes limitations and caveats, such as issues with data quality, availability, or scale.
- (Preliminary) Results: A summary of the results of the execution of the methods described in the prior section. Description of whether the hypotheses were corroborated or falsified, or whether the results are inconclusive. With research proposals, this is used to summarize any preliminary research done on the topic.
- Conclusions, Significance, Future Research: Interpretation of the what the results mean, why those results are important, and what further questions this research raises.
Additional sections that are often also included in papers and reports:
- Abstract: This is a one-paragraph summary of the research topic, questions, and results. The abstract is placed under the title at the beginning of the article and gives readers a quick way to evaluate whether the research is relevant to their work and deserving of further reading.
- Bibliography / References: A list of the literature referenced throughout the document.
- Appendices: Graphs, data tables, computer source code, etc. that can be used to more deeply investigate or validate the results of the research.