OpenRefine brands itself as a “powerful tool for dealing with messy data.” This is an incredibly apt description of the program. I’m glad there was a tutorial to accompany OpenRefine since I feel that the program isn’t completely intuitive. Thankfully, OpenRefine opened itself to a semblance user friendliness after I fumbled around with the program for a bit. I couldn’t begin to imagine how difficult and tedious it would be to clean data without a tool like OpenRefine.
I belong to Group 12; we received a dataset concerning classicists and their work. This dataset, with its glaring omissions, typos, and ambiguities, has been a daunting thing to analyze. However using OpenRefine opened a lot of pathways for clarity in my dataset. The cluster tool was particularly revelatory for the dataset. Because the set was so disorganized, using clusters to establish parallel syntax throughout allowed for the holistic illumination of the set.
I agree that OpenRefine does clarify a lot of the data that might be too confusing to understand. I like that you provided a visual on how the program is helping you understand your dataset more.