Today I decided to try my hand at minimalist interface design whilst dealing with an issue I want to include in Level 2 Digital Media skills next academic year: Open Data.
Open data is the idea that certain data should be freely available to everyone to use and republish as they wish, without restrictions from copyright, patents or other mechanisms of control. The goals of the open data movement are similar to those of other “Open” movements such as open source, open hardware, open content, and open access. The philosophy behind open data has been long established (for example in the Mertonian tradition of science), but the term “open data” itself is recent, gaining popularity with the rise of the Internet and World Wide Web and, especially, with the launch of open-data government initiatives such as Data.gov and Data.gov.uk.
This is a fundamental aspect of all information powered Apps / Web Apps and will continue to be important as long as our need to share, consume and analyze data exists.
Visualising this data falls into two main flavors in my opinion. Everyday and Big data.
Everyday data is the small, snippets of information that we use or consume frequently in a short space of time. We simply glance at it, extract what we need and then we’re done with it. Some examples that you’re probably familiar with:
- News headlines
- Sports results
- Meter Readings
- Stock Market
- Exchange Rates
- Instant Messages / SMS
- Twitter / Facebook Posts / Comments
Data isn’t always numbers (although for analysis it is easier if it is). Take this map below that shows a families movements around their living space. Although this data can be broken down into numerical data (coordinates) it is far more human-friendly in this visual map form as it’s placed in a context we all understand:
One method to display data that is just a procedure or doesn’t contain many values is to create an info-graphic:
Big data on the other hand is the complex relationships between numerous data sets and sources. This can range from small-scoped data such as comparing a school register over different time periods to data so complicated that digesting and analyzing in its raw form would be almost impossible.
When numbers become too large to imagine and when data combines large numbers with another associated value, such as location (as shown below), then for human consumption at least, there are better ways of displaying it:
There is a difference too in the way would approach displaying these two types of data. For a start, the scope of the project is directly affected by the complexity of the data and this in-turn will affect how, I don’t want to say ‘creative’ because displaying big data visually requires a very creative approach. Perhaps ‘experimental’ is the correct word because with big data the output and accuracy is everything – a viewer should not have to work out what they are looking at. With Everyday data however, the context will be set and will be something we are accustom to which allows freedom with its presentation.
With this in mind it seemed only right to choose some Everyday data to display for my desire to work on a minimalist interface. Such an approach would not do justice to Big Data!
I decided therefore to tackle displaying weather data… but, before you yawn and say “so what?” consider this: there are several weather visualisations and Apps but where do they fall in terms of form over function?
Many of them suffer from either too much data on display or not enough that they become abstract and besides which, weather data is accessible as Open Data, something else I wanted to incorporate.
My next post will look at the competition and some sources of inspiration.