I’m going to hit a few of the things I’ve done with people around open educational resource creation.Looking back at the list, it’s clearly heavy on non-textbook models (which other people deal with better and more deeply than I) and heavier on student creation/participation. Many of these are tier-one data entry elements that would provide additional levels of sophistication as the data is aggregated. In the discussion, I’m going to ignore some complexities around the term ‘open’ in order to avoiding dragging the whole post down. My personal definition of open is very liberalIn certain ways I feel fighting for the use of material under copyright is a must in order to reclaim/maintain rights and prevent things from becoming more restrictive. I can also see how people want to completely avoid any chance of drama or legal fees. although I can see the value of Wiley’s R framework in a variety of conversations. Once again, I’ll try to move from simpler to more complex options. The Judah Will The Judah Will is a will that was transcribed and annotated in the digital history class this semester. Ryan Smith is the history professor behind the idea and has been more than awesome to work with. Right now the work is all in Google Docs but we’re looking at paths/tools/display options that […]
I often want to know just a bit more about numbers I see in tables. As I was looking at some thing today, I stumbled on the Wikipedia page for “List of Most Viewed YouTube Videos“. After being more than a bit amazed at the utterly staggering numbers. I wanted to know what they translated to in terms of years because the numbers were just too big. I remembered that Google Spreadsheets will let you pull in a table from a website with no fuss. All I needed to do was put =IMPORTHTML(“http://en.wikipedia.org/wiki/List_of_most_viewed_YouTube_videos”,”table”,1) in the first cell on the spreadsheet and viola the table is transcluded. I can now add a few more calculations to figure out the import stuff – like how many years worth of time have been spent watching Gangnam Style (16,274.24 years for the recordAssuming I didn’t screw something up.). You can go mess around with the data here.
See the Pen text analysis color viz – step 1 by Tom (@twwoodward) on CodePen. Assuming you have sentences, phrases, or words you’d like to categorize . . . you could do something like this to create a visualization. This one is using CSS but it could be done in any basic word processing software. Setting levels of opacity would allow for multiple-overlapping categorizations. See the Pen text analysis color viz – step 2 by Tom (@twwoodward) on CodePen. Playing with font size and the rotation of the paragraph also opens up some doors . . . as does doing different rotations at the sentence level depending on the categorization of the sentence. You could get even more granular with stuff like that using data attributes and CSS. See the Pen text analysis color viz – step 4 by Tom (@twwoodward) on CodePen. A Bit Odder See the Pen text analysis color viz – step 5 by Tom (@twwoodward) on CodePen.