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The Four Features of Big Data

One of my favorite things about the Next Generation Science Standards is their elevation of the role of data in the scientific process.
It compels a big shift in science teaching and learning—from an approach where students are told that a phenomenon exists, to one where students explore the scientific evidence that supports it. This data-informed approach is becoming more and more critical in a data-rich world.
Students can build these analytical skills from a young age, too. But to do this, we need to build upon lessons using classroom-created data, and expand to data sets that look and feel more like those being used in industry and science. Specifically, big data.
So, what attributes of big data make it different from what is typically used in classrooms today? We've identified four key features. Big data is:

  • Complex. It includes multiple types of data, collected using a variety of instruments and methods.
  • Large. It contains information that is extraneous to the specific question a student is researching, requiring him/her to choose among different data to identify what is relevant to a particular inquiry.
  • Interactive. It is digital and allows for flexible exploration—for example, by creating different types of data visualizations, some of which may not turn out to be meaningful.
  • Professionally-collected. Big data may come from NOAA, or a local weather agency, or a national research firm. The important thing is that the data goes beyond what students, themselves, are able to collect.

Complex, Large, Interactive, and Professionally-collected—or CLIP, for short.
Now, our challenge is to develop classroom activities that build the skills necessary to work with CLIP data. We've developed some of these already, and we look forward to sharing more in the coming months.
The takeaway? It's possible to help students build big data skills without drowning them in big data. We want to provide that bridge.

Ruth Krumhansl, Director
The EDC Oceans of Data Institute

Student using Ocean Tracks
Want more CLIP data activities for middle and high school students? Check out Analyzing Ocean Tracks and some examples from the EDC Earth Science curriculum.
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