PPDAC Model

The PPDAC Model is a methodological framework for applying the scientific method to an analytical or research question. As defined by Mackay and Oldford, the PPDAC Model is a sequence of steps that describe the statistical method. The perspective of Mackay and Oldford will often focus on problems within scientific research and is too confined for the complexity of real-world applications and practical problems that GIS analysts are likely to encounter. The acronym PPDAC stands for these sequential steps: Problem, Plan, Data, Analysis, and Conclusions. The use of the PPDAC model in the context of spatial analysis requires that the "planning stage is much broader than in Mackay and Oldford's" explanation of the model. In the context of Geographic information systems organizing an analytical procedure, such as a scientific research project or a resource management decision, is often called a Project GIS.

The PPDAC Model was created by statisticians R.J. MaKay and R.W. Oldford as a framework for projects where statistical analysis is required, but can be applied to spatial analysis projects as well. The model is not a rigid, specific set of instructions, but instead is meant to be adaptable and flexible to the many different stages of a project. The PPDAC model is different from other models because it emphasizes the importance of including analysis as part of the overall process instead of considering it alone. Each stage of the model has some influence over other stages and oftentimes the later stages will feed back to previous stages. It is better to think of this as a cyclical process instead of a linear process.

Problem
Defining the problem is the first stage in this model. This stage includes determining what issues need to be addressed, what data will likely be needed, and what tools and procedures will be used. Defining the problem is a process that might require multiple drafts. However, it is important to have the problem clearly defined before beginning the following stages. Defining the problem is not always a single event in this process. The initial specifications of a problem may be altered after obtaining preliminary results, technical considerations, and unforeseen events. Because there is usually more than one party involved and interested in the outcome, it can be beneficial to maintain the initial outline of the problem. However, when a change is necessary each party should be in agreement.

Plan
Once the problem has been defined, the planning stage helps create an approach that is used to address the problem. This is completed by creating a detailed project plan, which may include the estimated cost of data, equipment required, an outline of tasks that should be completed, timelines for completing the work, and a list software tools that may be used. This often involves determining the major tasks, breaking them down into subtasks, and planning what needs to be done and the resources required to accomplish those tasks.

Data
As one executes the analysis plan, data must be collected to perform the desired analysis. Because not all datasets will be of the same quality, considerations must be made in order to account for issues that may exist, such as missing data, differences in availability, cost, resolution, formatting, or errors. GIS now frequently have tool sets in order to overcome these issues. For example, breaklines can handle lack of continuity in data and coding schemes can be used in order to overcome missing data. .

Analysis
Analysis can be seen as a multi-part exercise, moving through the following steps: review and manipulation of collected data to make it useable, study of the data to identify patterns relevant to the problem at hand, and use of data to make conclusions or to alter the plan made in the previous stage.

Conclusion
The conclusion stage, simply put, is where conclusions are drawn from data analysis and presented to others. Implementation of the conclusions is not included in this process. Conclusions can lead to more problems to be answered, additional analysis to finish answering the problem at hand, a complete overhaul of the plan to answer the problem at hand, or a plan to apply the conclusions to the problem. As stated by Mackay and Oldford:

"The purpose of the Conclusion stage is to report the results of the study in the language of the Problem. Concise numerical summaries and presentation graphics [tabulations, maps, geovisualizations] should be used to clarify the discussion. Statistical jargon should be avoided. As well, the Conclusion provides an opportunity to discuss the strengths and weaknesses of the Plan, Data and Analysis especially in regards to possible errors that may have arisen"