Problem: Framing the question

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Problem: Framing the question

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Understanding and defining the problem to be studied is often a substantial part of the overall analytical process — clarity at the start is obviously a key factor in determining whether a programme of analysis is a success or a failure. Success here is defined in terms of outcomes rather than methods. And outcomes are typically judged and evaluated by third parties — customers, supervisors, employers — so their active involvement in problem specification and sometimes throughout the entire process is essential. Breaking problems down into key components, and simplifying problems to focus on their essential and most important and relevant components, are often very effective first steps. This not only helps identify many of the issues to be addressed, likely data requirements, tools and procedures, but also can be used within the iterative process of clarifying the customer’s requirements and expectations. Problems that involve a large number of key components tend to be more complex and take more time than problems which involve a more limited set. This is fairly obvious — but perhaps less obvious is the need to examine the interactions and dependencies between these key components. The greater the number of such interactions and dependencies the more complex the problem will be to address, and as the numbers increase complexity tends to grow exponentially.

Analysis of existing information, traditionally described as “desk research”, is an essential part of this process and far more straightforward now with the advantage of online/Internet-based resources. Obtaining relevant information from the client/sponsor (if any), interested third parties, information gatekeepers and any regulatory authorities, forms a further and fundamental aspect to problem formulation and specification.

Spatial analysts also need to be particularly aware of a number of well-known problems associated with grouped data in general, and spatial data in particular. This applies to both problems in which the analyst contributes to the entire PPDAC process as well as the common situation in which the analyst is presented with the problem or task and maybe the (broad) approach to be taken by another party (for example an academic or business supervisor, a technical committee, or even a client). Issues requiring particular attention in the case of spatial problems include:

spatial scale factors: over what study region is the work to be carried out, and what are the implications of altering this for some or all datasets? Do the same scale factors apply for all the data of interest?
statistical scale factors: at what levels of grouping are data to be analyzed and reported?
spatial arrangement factors: does the specification of the spatial arrangement or re-arrangement of subsections of the study area have an impact on the analysis?
does the problem formulation require data of types, sizes or quality standards that are available, within the time, budget and resources available? if not, compromises will be necessary
are conclusions regarding spatially grouped data being sought that imply the grouping (e.g. at the county level, at the farm level) is truly representative of all the components in the group (e.g. individuals living within the county, fields within the farm)? If so, the grouped regions must be entirely or largely homogeneous in order to avoid the so-called ecological fallacy — ascribing characteristics to members of a group when only the overall group characteristics are known (special statistical techniques have been devised to address certain problems of this type, for example as discussed in King et al., 2004)
are conclusions regarding spatial grouped data being sought based on the measured characteristics of sampled individuals? If so, the sample must be entirely or highly representative of the grouping in order to avoid the so-called atomistic fallacy — ascribing characteristics to members of a group based on a potentially unrepresentative sample of members

Framing the question is not always a one-time exercise. Once an initial problem specification has been drafted, it may be altered in the light of preliminary investigations, technical or commercial considerations, or unforeseen events (Figure 3‑3, feedback loops). As far as possible, however, only essential changes should be made (and documented as such) once problem formulation has been completed and documented, and all interested parties have agreed on problem content. GIS has a particular role to play here, in providing tools (principally mapping related) for storing and visualizing existing data and facilitating discussion of aspects of the problem prior to subsequent stages in the process. This role may continue throughout the various stages of a project, assisting in the interpretation, analysis and presentation of results. Careful consideration should be given to change control management, documentation and reporting, especially in commercial and governmental environments.

Note that in many instances it will be difficult if not impossible to compute the timescale and budget required to address a particular problem without a preliminary study or project. For example, it is quite common for there to be preliminary project involving the preparation of a detailed Requirements Specification (RS) and/or undertaking a smaller-scale or feasibility project, e.g. confined to a small, but representative, area.