Editorial thinking

Editorial thinking deals with making decisions where a data analyst chooses relevant charts in the whole set of visualizations, should be creative enough to know what #visualizations would be of interest to the views of the visualizations. Instances where a writer is trying to tell a story using #data. This can be done by the use of keen filtering skills and being able to discern what to display for viewers and what to leave out.
It relies based on the editor’s opinion, their point of view, and how they interpreted the data. This step is crucial as it comes before the design phase. The aspects that an editor may consider are such as the #colorchoices, and the types of #charts and #graphs concerning multiple data types available in their #dataset.
The three main perspectives of editorial thinking are
angle –The approach that will be taken to answer the question at hand. i.e. where is Ebola mostly spread and fatal globally? This would need the use of a map feature. What other visualizations can help satisfy your curiosity. This can be characterized by the focus and trying as much as possible not to take many angles when analyzing data.
framing : In the large dataset with different datatypes. Having in mind what data to put and what to leave out on specific graphs and plots. Some visualizations work best with categorical data. In this stage, an editor should look at how complex the data is before visualizing it. From a picture perspective, there cannot be everything in a frame.
Focus: This now supersedes framing. After the data is selected, there should be a consideration of what data to emphasize. This is what catches the users' attention. It needs an editor to select features that they believe are more important than others. This may need an editor to use aspects such as color highlighting. #design