Part 2. The FLOAT Method
2.1 What is the FLOAT Method?
What is the FLOAT Method?
The FLOAT Method is a five-step process that facilitates your ability to outline your project by (1) conceiving of a research question, (2) explaining how you locate, (3) organize, and (4) analyze a given data source, and finally, (5) transforming your findings into a visualization.
Finding Pearls with the FLOAT Method
In Storytelling with Data, Cole Nussbaumer Knaflic brings attention to two types of analyses that relate to the visualization process: exploratory and explanatory analysis. Exploratory analysis is what you do to understand the data and figure out what might be noteworthy or interesting to highlight. Explanatory analysis is when you settle on a specific finding you want to explain – or, a specific story you want to tell.
She writes, “We might have to open 100 oysters (test 100 different hypotheses or look at the data in 100 different ways) to find perhaps two pearls.” She goes on to note people too often overwhelm audiences by trying to show 100 oysters, that is, in other words too much. The more ideal situation is this: “Concentrate on the pearls, the information your audience needs to know.”
The FLOAT process enables you to focus on pearls and communicate insightful findings to your audience. Data analysis can be part of a study, which involves the development of research design, data collection, and interpretation. The process of exploring data brings about different possibilities for deriving insight about a particular finding.
The FLOAT Method (Extended)
F – Formulate (a good research question)
- The first step is FORMULATING an insightful and feasible research question, which will define the parameters of your project and guide your analysis.
- Exploratory Question: This initial question is broad in scope and tends to lack specificity. How difficult would it be to locate the data should be taken into consideration during this phase.
- Explanatory Question: Researchers usually revise this question after analyzing the data source in-depth. This revised question is more targeted in scope and reflects the limits of a given data source.
L – Locate (a sustainable data source)
- The second step involves LOCATING a suitable data source to answer your research question.
O – Organize (your data source)
- The third step is ORGANIZING your data to make sure it is cleaned and in a suitable format to be manipulated using data-analysis and visualization software.
A – Analyze (your data source)
- The fourth step is ANALYZING data in order to identify trends and other patterns that help to answer your overall research question(s).
T – Tell (a data-driven story)
- The final step, TELLING a story, involves composing a narrative to effectively convey your findings. To tell the story, you will need to choose a suitable visualization medium. The explanatory research questions facilitate the creation of useful visualizations.
Setting Expectations
To be comfortable withi