As part of a presentation I have to do in a couple of days, I’ve started to outline why I’ve chosen to design the news for my final years project. I’ve used the NABC approach to split my thoughts into segments.
Need
Alot of the news we receive is mostly through newspapers, and TV reports. This requires that the person be able to read, and/or understand the language that the news is broadcast in. I’d like to offer people a new way of looking at news by simplfying it, and perphaps even replacing the words all together with pictures, and self descriptive illustrations.
I also want to explore the categorisation of news. At the moment when news is reported on websites such as The Guardian or The Times, it is filed under a subject heading or category. This seems pretty vague to me, as the news can be tagged in multiple different ways to make it more searchable and more relevant to the end user.
For example with a typical news story, first file it in a general subject header, followed by categories that sit under that subject, and tags that are important keywords in the story. Make sure the story is filed with the date and time and the author of the story. Also tag it’s status, whether it’s a breaking story, a more informative write up, or a follow up story. Also whether or not it’s been updated or revised. We can then work out it’s relationship status, and link in other articles about the same story so the user can follow it’s development.
Meticulously tagging the articles then means we can offer accurate related stories by date, popularity, author, categories, tags, subjects, and more.
Approach
To demonstrate these ideas, I want to experiment with ways of communicating the news visually. These includes a series of posters and wallpapers using graphics to replace words, hopefully some animated diagnostics of the news, and some interactive visualisations using news based API’s from GoogleNews and Digg.
I want to apply a range of visual styles to the news, using a different style for each depending on the headline. This way I can create an emotive environment to frame the message of the news.
Benefits
Visualising the news will show people new ways of looking at a data form that is usually heavily text based. It will allow the user to see an overview of the story with the embedded emotion of the graphic.
Representing the words as pictures will allow the people who can’t read to understand the news, and organising the news into specific and meticulous categories will allow applications to use the data to create visualisations and systems that will allow the user to explore news in more depth.
Competition / Context
Mapping and visualising the news is nothing new. It has been done before in various ways. Jonathan Harris has done a number of visualisations and data manipulation projects including 10x10, and the labs at Digg.com have some really beautiful visualisations that use their social news networking data. These applications and others like them use the standard API’s that seem to be out there, but a more detailed and categorised story offer more options for visualisations.
Hopefully I will be able to come up with a concept that uses more meta data from the stories than has been used so far. At the moment, the Digg Arc seems to be the most detailed of the API visualisations offering a relationship status between the users and the story, and other stories that the users have ‘Dugg’.
3 Comments
Not sure if you’re aware of this, but Aaron Cope’s been extracting topical relationships from the NYT for a few years now, may make for useful source material: http://aaronland.info/nytimes/
I wasn’t aware but this is exactly what I’ve been looking at. Thanks Michal. I can see this is going to be useful!
Also, I love the work you guys do at Stamen, and have been following you since the first rollout of DiggLabs. Excellent stuff, and worth a look for anyone else interested in data visualisations.
Thanks!