Digital Currency Timeline

I’m currently writing an article on digital currencies for a future, small-run magazine edited by Crazy Little Things. To complement the article, and to try to learn some new data-journalism skills I decided to do also a timeline of the most relevant digital currencies for the past 20+ years. This is the result:

How it’s done

I used Inkscape to draw the SVG file: timeline, bars and text, and create the layout. Then I added basic interactivity by hand using a text-editor. The content is based on my own research for the article. I plan to include in further releases a csv with the source data used in the timeline so it’s easier for others to replicate it using other tools.

Regarding interactivity, right now you can uncover some contextual information hovering your mouse over certain years, and click on the names of the digital currencies to go to their website or get more information. I plan to add more contextual information on the currencies, explaining the type of currency and the reason it dissapeared, if needed.

Improve it

The project (just an SVG file) is hosted on Github. You can download it, fork it, open a new issue, send ideas or suggestions. The project is under a NC-BY-SA Creative Commons licence. This is my first time using Git and Github for a project like this, and I’ll share my experience in a separate post. I can tell you now that I’ll definitely keep using it.

I’m also open to criticism on the timeline content: Did I miss a critical digital currency project? Should I remove something from the timeline? Is any of the data wrong? I’m all ears.

Top 5 essential skills for a data journalist

New York Times’ Aron Pilhofer answer to that question on the NICAR-L mailing list:

My top five (in order of importance):

  1. Know that the most important part of data journalism is… journalism. Reporting. In other words, you know how to report a story, you understand how to treat data as a source. You know how to pick up a phone, and not just assume that everything you get in data form (especially government data) is complete and accurate.
  2. You have at least basic data skills — meaning, you know your way around a spreadsheet. You can figure out for yourself how to import data, and do something with it. You also understand the basics of data analysis: rates, ratios, sums, averages, medians, and how to use them.
  3. You have command of more advanced data analysis skills, such as GIS, basic statistics, advanced SQL, etc. You also may know some basic programming techniques (using the language of your choice… Python, Perl, Ruby. ILENE.. shoot, even .NET) to scrape the web, get and clean data.
  4. You can apply your basic programming techniques to the creation of data-driven news applications using off-the-shelf tools like Google maps, MapBox, Fusion Tables, etc. At this point, you are not running servers, or serving database-driven apps. But you are creatively using what is available to you to add to your reporting online. This is probably where you need to get on the Javascript train.
  5. You have some skills with a web framework (Django, Rails, Grails) in order to enhance your reporting online through data-driven applications that you create from scratch and host.

CartoDB workshop in Barcelona

Last Monday I attended a workshop about CartoDB, organized by Media140 (with whom I’ve also collaborated: 1 and 2) and presented by Sergio Álvarez.

CartoDB is a powerful and open source geospatial data management and visualization tool. It does everything Google Fusion Tables does, and more. If you’re comfortable with SQL queries and CSS (CartoDB uses Carto, a stylesheet language from Mapbox similar to CSS), you can get amazing results, including hexagonal density grids, or editable and interactive maps. They have more case examples in the gallery, and you can find many more examples online.

In the workshop we learned how to do the basic stuff: upload different kinds of data, visualize them, merge them and tinker a bit with the SQL queries and Carto stylings. We did two maps during the workshop: Spanish unemployment by provinces and life-expectancy rates by country:

I had a CartoDB account way before the workshop but I never got around to try it. I don’t know why, but I thought it was harder to use than Google Fusion Tables, so I was pleasantly surprised to discover how easy it was to work with it. Now I’m looking forward to see how can I use CartoDB in my projects.