This chapter discusses the first step of the SGAM, highlighted below in gold, the Analytic Question.
The question, or analytical problem, can be viewed as an active two-way interface between the client requiring the information and the geospatial analyst supplying it. The problem defines the geospatial patterns the analyst is seeking. Foraging and sensemaking define the nature of the analysis and quality in this context defined as satisfying the client. A geospatial question that leads to the sensemaking process must meet three criteria of:
Therefore, the problem possesses a highly strategic significance. The figure below depicts a three-way connection between the client and analyst’s domain:
Before beginning, ask the following questions:
The question focuses the analyst on the nature of the spatial and temporal patterns the analyst is seeking to identify and understand. Many new geospatial analysts struggle to translate the question into the context of spatial concepts. To overcome this, we stress the importance of understanding the general analytical question and developing a spatial corollary of this broader question.
What is an analytic question? There are significant differences between a “factoid question,” which are the most common in Geospatial Intelligence, and an “analytical question.” A factoid question seeks a piece of information that would be answered with a corresponding true statement. For example:
Question: “How many miles are between two shooter events?”
Answer: “There are 5 miles between events."
In general, a factoid question usually has just one correct answer that can be easily judged for its truthfulness. Answers to factoid questions are important as evidence but are not to be the focus of an analytic effort. Data foraging provides factoids (or evidence), a small but potentially important bit of information. In contrast to a factoid question, an analytical question has a less certain relationship with expected answer. For example:
Question: “Who is the DC Shooter?”
Answer: “The shooter could be a foreign terrorist or a serial killer.”
In general, an analytical question has many possibly correct answers that cannot be easily judged for truthfulness. An analytical question is generally quite flexible in the sense that there is always a strong possibility that we may not arrive at the “expected” answer. Thus, a change of analytic strategy, and even the initial expectations of the analysis, may be warranted. This suggests a solution to an analytic question must involve iterative information foraging and sensemaking.
The Geospatial Corollary is a highly spatial problem statement which follows readily from the broader analytic problem, and suggests a narrowly focused spectrum of geospatial questions. The evidence developed as part of the spatial corollary contributes to the larger body of evidence of the initial analytic problem; the spatial corollary is unlikely to be as significant to the stakeholder as those of initial analytic problem statement. The development of this spatial corollary involves an active two-way discussion between the client requiring the information and the geospatial analyst supplying it. For example, “What geospatial aspects of the events help to explain if the DC Shooter is a foreign terrorist?” The spatial corollary must be “analytic” which means four conditions are met:
Action 1: Develop an understanding of the general analytic question. Understanding the general question will require a two-way dialog between the client requiring information and the geospatial analyst supplying it. The distinguishing characteristics of an “analytical question” in geospatial intelligence are:
Action 2: Familiarize yourself to the problem. Before finalizing the question, the analyst must have a preliminary and broad base of knowledge about the problem. When dealing with a new and unfamiliar subject, the uncritical and relatively non-selective accumulation and review of information is necessary. This is a process of absorbing information, not analyzing it.
Action 3: Think about the Spaces. An object or event can be specified relative to the observer, to the environment, to its own intrinsic structure, or to other objects in the environment. Each instance requires the adoption of specific spatial frames of reference or context. The spatial context is critical because it is the space the data is in that ultimately determines its interpretation. There are three spatial contexts within which we can make the data-to-information transition. In all cases, space provides an interpretive context that gives meaning to the data. These include:
Action 4: Think about the fundamental spatial questions. When making sense about the spaces (Gershmehl and Gershmehl, 2006) the analyst first asks and answers the following questions each of the life, physical, and intellectual spaces:
Action 5: Think about the qualities of the objects or events for each space. The analyst then proceeds to examine the object or events for each space by asking the following questions:
Action 6: Think about the relationship between the objects and event for each space. Last, the comparisons are placed into the context of space and time. This is spatiotemporal thinking which asks the questions:
Action 7: Write the Geospatial Corollary. The geospatial corollary is a highly spatial problem statement which follows readily from the broader analytic problem, and suggests a narrowly focused spectrum of geospatial questions. The evidence developed as part of the spatial corollary contributes to the larger body of evidence of the initial analytic problem; the spatial corollary is unlikely to be as significant to the stakeholder as those of initial analytic problem statement. The development of this spatial corollary involves an active two-way discussion between the client requiring the information and the geospatial analyst supplying it. The spatial corollary must be “analytic” which means four conditions are met: