Consider some of the reflection questions embedded in the training. For example, what do you notice about the data and how it could be mapped? What do you notice about your visualization as you change its drawing style and customize its appearance?
ArcGIS, as a mapping tool, is rooted in geospatial data but can also represent other kinds of data based on these geographic points. A category of data could be represented in terms of size (which can be represented as points with different colors or different sizes of points), different types, a heat map, or as uniform single points. Except for the heat map, the program provides the ability to cluster the points to varying degrees to promote analysis. (Assumedly, the heat map has this as a built-in feature.)
The basemaps, the template maps that ArcGIS embeds this tool with, offer the user the ability to customize their map (ex: blueprint, chartered territory, street). Having a pleasant contrast between the points and the map is good for accessibility reasons.
How would you feel about helping someone else learn how to use ArcGIS Online? What did you find most interesting? What did you find most frustrating? What questions do you still have, and what parts of the tool do you want to explore more deeply?
ArcGIS Online is a tool that my project lead and I are currently learning together. Using the training data set, I was able to test out a variety of ArcGIS features easily. Some of the buttons are not clearly defined, but after playing around with the tool, I think this becomes a matter of familiarity that others can pick up on. Dealing with a dataset that has not been perfectly configured for ArcGIS, on the other hand, has definitely been a challenge. Because of some contested geographic areas and the subjectivity of what the world “really looks like,” having to subscribe to and/or circumvent ArcGIS’s interpretation of the world can be frustrating.
Something my project lead and I discuss a lot is when a digital map is just a bunch of points versus a visual display conducive to storytelling and analysis. We want to further explore how to best represent our data with this map.