Most open data repositories publish their data sets in large, downloadable files for analysis. Data visualization approaches can offer insights into complex data sets not readily apparent using other data analysis methods.
About
Data visualization is the presentation of data in a pictorial or graphical format. It enables decision makers to see analytics presented visually, so they can grasp difficult concepts or identify new patterns. With interactive visualization, you can take the concept a step further by using technology to drill down into charts and graphs for more detail, interactively changing what data you see and how it’s processed.
What to Do
The growth in open data collections has spurred development of a wide range of tools for data visualization and analysis. There are many tools to choose from, but we are going to explore the following free applications:
- Roambi
- Vizable
- RAWGraphs
Most open data repositories provide datasets in a number of formats. For the purposes of this exercise, we are going to browse open data repositories looking for a dataset in .CSV format.
Some open data repositories to consider:
- Datos Abiertos de México
- Datos Web Service
- OECD Data
- OpenAIRE
- Explore one of the open data repositories above.
- Find an open data collection available in .CSV format. For example: the front page of Datos Abiertos de México has a number of data sets available in .CSV
- Chose one of the free open data visualization tools above.
- Copy and paste the link to the .CSV file into one of the apps and explore different data visualization options.
- Try visualizing the same set of data with each of the three tools. Were there options and techniques in a particular application you found most useful?
- If you generate a data visualization you find compelling, consider taking a screenshot of it and sharing it on Twitter with #muraludg or at the Acumulador
Featured Image: Matrixy Mural flickr photo by cogdogblog shared under a Creative Commons (BY) license
