The human mind can only hold so much information at a given time. 

Most of us have played the memory game where the host brings out a tray of assorted knick-knacks and gives us a few moments to stare at it before it is whisked away and we are asked to recall as many items as we can.

Generally speaking, this number falls within the “seven plus or minus two” range. One of the most highly cited papers in psychology, “The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information,” speaks to this phenomenon.

Recent advances in Big Data have great promise for solving some of society’s most challenging problems, but how does the human mind handle staring at over a thousand different data points?

Big Data Analytics methods typically require the expertise of a highly skilled analyst. The “human in the loop” method of analysis allows the user to change the outcome of an event or process by modeling different scenarios. Analysts sort through large, complex collections of data sets by employing different models and running simulations. However, most researchers do not possess this level of analytics expertise, and although companies are investing large sums of money to gain insight from the surplus of publically streaming information, they often do not have employees on staff who are able to make much sense of it.

A recent grant award from the National Science Foundation aims to change all of that. Chris North, a professor of computer science and associate director of the Institute for Critical Technology and Applied Science’s Discovery Analytics Center and his well-seasoned team of researchers have won a $1 million grant award to make Big Data Analytics more user-friendly.


The team is using a spatial metaphor system, known as Andromeda, to bring large data clouds down to manageable working sets.

In this system, similar objects are placed in closer proximity. When the user changes the layout of the items, the system updates and learns which data features make those items similar. When people re-organize the data, the data responds and the user is able to learn what features are responsible for that change.

Think back to the aforementioned memory game. Imagine how many more items you could remember if you were able to manipulate the tray and group like objects together to create patterns of similarity. Andromeda allows users to visually interact with the data and glean more meaning from the data points. And using it doesn’t require a Ph.D.

North is excited about the fact that people can apply their own knowledge on the subject area and recognize interesting, new patterns when they arise. The visualization is then tailored to how a person thinks about the data, and the tasks of organization and discovery can occur simultaneously.

By making Big Data a “meaningful picture that users can manipulate,” North and his team are bringing Big Data Analytics to the masses.


Written by Emily Kathleen Alberts