By rkrumhansl on September 13, 2016
What an expert sees in a data visualization is not what a novice sees. This is an important lesson learned from a two-year project undertaken by the Oceans of Data Institute, funded by the National Science Foundation.
By rkrumhansl on August 17, 2016
The Oceans of Data Institute has put considerable energy into understanding what it means to be data literate in the age of “big data”. We, of course, are not the only ones interested in this as awareness of the shifting landscape grows. An internet search we did recently revealed attempts by organizations around the world to describe data literacy with definitions that vary in length from a short sentence to more than 200 words.
By rkrumhansl on June 30, 2016
...this is a phrase I’ve heard repeatedly from expert big data analysts since we first launched the Oceans of Data Institute in 2013. Indeed, in ODI’s 2014 survey of close to 100 big data analysts, analytical thinking and critical thinking emerged at the top of the list of skills and knowledge essential to working with big-data across a broad spectrum of disciplines.
By rkrumhansl on March 10, 2016
Why Analytical Thinking?
In 2014, ODI gathered an expert panel of professionals that work with big data. After 2 days of intense discussion, this expert panel developed a list of the knowledge and skills essential to working with big data. Their work was then validated by almost 100 peers who work as big data analysts. As you can see below, Analytical Thinking ranked highest in both the knowledge AND skills essential to being an effective big data-enabled specialist.
By rkrumhansl on February 16, 2016
“Data drives discovery, decision-making, and innovation. … However, our current education systems have not been equipped to produce either the workforce or the citizenry with the skills, knowledge and judgment to make wise use of the data streams that our technologies are delivering.” – A Call for Action for Promote Data Literacy Workshop for Building Global Data Literacy, October 2015
