Visual data analysis time to adoption horizon four to five years
Download
1 / 11

Visual Data Analysis Time-to-Adoption Horizon: Four to Five Years - PowerPoint PPT Presentation


  • 125 Views
  • Uploaded on

Visual Data Analysis Time-to-Adoption Horizon: Four to Five Years. Tonia Collier-Ross Ke Shanda Golden Allison Jones Rudi Roberson. Overview.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Visual Data Analysis Time-to-Adoption Horizon: Four to Five Years' - rusti


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Visual data analysis time to adoption horizon four to five years

Visual Data AnalysisTime-to-Adoption Horizon: Four to Five Years

Tonia Collier-Ross

KeShanda Golden

Allison Jones

Rudi Roberson


Overview
Overview

  • Over the past century, data collection, storage, transmission, and display has changed dramatically, and scholars have undergone a profound transformation in the way they approach data-related tasks.


  • Blending of these disciplines has given rise to the new field of visual data analysis, which is not only characterized by its focus on making use of the pattern making skills that seem to be hard- wired into the brain, but also in the way in which it facilitates the work of teams working in concert to tease out meaning from complex sets of information.


Tools used
Tools Used field of visual data analysis, which is not only characterized by its focus on making use of the pattern making skills that seem to be hard- wired into the brain, but also in the way in which it facilitates the work of teams working in concert to tease out meaning from complex sets of information.

  • Self organizing maps- an approach that mimics the way our brains organize multi-faceted relationships.

  • Cluster analysis- set of mathematical techniques for partitioning a series of data objects into a smaller amount of groups, or clusters, so that the data objects within one cluster are more similar to each other than to those in other clusters.


  • Visual, interactive principal components analysis- field of visual data analysis, which is not only characterized by its focus on making use of the pattern making skills that seem to be hard- wired into the brain, but also in the way in which it facilitates the work of teams working in concert to tease out meaning from complex sets of information. a technique once only available to statisticians that is now commonly used to identify hidden trends and data correlations in multidimensional data sets.

  • The tools are finding their way into common use, making it more available for the use of anyone

    • Many are free or very inexpensive


Relevance for Teaching, Learning, field of visual data analysis, which is not only characterized by its focus on making use of the pattern making skills that seem to be hard- wired into the brain, but also in the way in which it facilitates the work of teams working in concert to tease out meaning from complex sets of information.

or Creative Inquiry


  • Natural abilities humans have to seek and find patterns in what they see.

  • Manipulating variables, or seeing them change over time. If patterns exist (or if they don’t), that fact is easily discoverable. Such tools have applicability in nearly every field.

  • Creative inquiry is benefiting from a wide range of new tools that are exposing trends and relationships among both qualitative and quantitative variables in real time.


Examples
Examples what they see.

  • Models of complex processes in quantum physics, organic chemistry, medicine, or economics are just a few of the ways in which the outcomes of visual data analysis can be applied to learning situations.

  • Using tools like “Many Eyes” and “Wordle”, students can easily analyze the contents of their papers visually for insights into what points might need further development, and whether or not certain language has been overused.


Visual data analysis applications
Visual Data Analysis Applications what they see.

  • Astrophysics. Harvard scientists are using data visualization from the Chandra X-Ray Observatory to measure the expansion velocity of supernova remnants.

  • Fluid Dynamics and Human Physiology. Researchers working with Amira, a visual data analysis tool have created a range of models of biological processes from MRI data, fluid flows, and other complex datasets.

  • Marine Geology. similar to Google Earth, offers students a three-dimensional view of the Earth’s oceans

  • Composition and Rhetoric. students can analyze the contents of their papers visually for insights into what points might need further development, and whether or not certain language has been overused



Youtube video of chandra x ray
YouTube video of Chandra X-Ray what they see.

M31 in 60 seconds

World Mapper


ad