Layering Data

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Visualization Center

The Viz Center takes data sets and analyzes them for patterns or prepares the data in a way that can be easily accessed and presented to a variety of crowds.  The main method of looking at this data and getting a good understanding of what it has to offer is to look at it in various layers.  It is this process that is repeated again and again in varying ways to produce easily readable data sets.  This data could be visualized in multiple layers on a GIS map, or as a graph just to name two methods.  The variant here is simply the manner in which the data is presented, but the methods of analyzing the data through layers remains the same.  

Conceptually, the focus is on how best to translate the data into an appropriate form of visualization.  Data comes in two different forms, structured and unstructured.  Structured data is any set that is easily charted and sorted.  This may be anything from values to dates and attendance numbers. Unstructured data is mainly text based and can be things such as social media feeds or academic papers.  Structured data is fairly straightforward and can be organized in charts and graphs for numbers, or by mapping out various zones in a GIS map.   Unstructured text data can be organized by word frequency in a word cloud formation, traffic amount in the case of social media, or subject focus in reference to an academic paper.  These methods are a way to take the unstructured data and give it a framework so that it can be treated as a type of structured data and arranged easily into charts, graphs, maps, etc.

Evaluating this data is dependent on what one is looking to get out of it. It is this criterion that makes layers so very important.  This method of presentation can offer those looking at the data a way in which to examine it that they may not have thought of before. Examining cross sections of data is comparable to a method of lateral thinking in design.  Examine a wide range of possibilities and then proceed with them narrowing it down until eventually reaching a conclusion.  This process can be easily applied in the same way to examining data.  Look at a wide range of related data and pull various connections together until a clear evaluation of the data presents itself.