Distinctions & Data Literacy

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It is tempting to think all data arrives in an organized spreadsheet with labeled columns. But typically someone or something collected that data and assembled it into the spreadsheet's tabular perspective.  Before organizing data, there are high-level Distinctions one can make about data.

Data may present in a spreadsheet (structured) or perhaps in a more primitive form (unstructured) such as a collection of images. It may present as a hybrid (semi-structured) such as emails that have defined fields with free-text content. 

Individual data may be labeled (or tagged) or unlabeled.  For example, if you take a photo with your smartphone, it will also record metadata about that image such as date taken, file size, the type of phone, photographic attributes, and location. Conversely, if you take a photo with an older SLR camera with film, that camera is not recording and attaching attributes to that image. 

If reviewing a data set or a report, ask what is included and what is excluded.  Were these inclusions and exclusions intentional? Are there assumptions or unintentional omissions? Do they contribute to an outcome prone to biases?  

In considering data reports, ask what is its purpose. 

• Is a report descriptive of a current or past situation? 
• Is it prescriptive -- using data to recommend an approach to a problem?
• Is it predictive -- using data and statistical methods to predict a future situation?