Archiving my last tumblr blog – Urban Storytelling

Urban Storytelling Animation

Back in 2015,  Jessica Broscheit, Hannes Sieg and myself created a tumblr blog to collect thoughts on urban storytelling, data driven narratives and visualisation of urban data, digital and tangible designs as well as art installations in urban spaces. All this related to research into data driven storytelling, open government data, knowledge discovery in databases (KDD), rapid prototyping and design thinking.

Some of the work led to projects such as How Will We Breath Tomorrow, a workshop led by Jessica Broscheit during A/D/A Hamburg 2016, as well as me participating as a mentor in Jeremy Bailey’s The Lean Artist Accelerator, a seed accelerator program for artists.

Since we all moved on, completed our research and are now involved in subsequent or different projects, no more content has been added to urban-storytelling.com for quite some time. In addition to the latest developments around tumblr and yahoo it makes no sense for me to keep the content up, so I cancelled the domain and closed the urban storytelling blog on tumblr for good.

Some of the content can be found on this website, but most posts were just links to interesting stuff related to urban storytelling, urban data, visualisations, map technology and data journalism. The links might be useful in the future and maybe I will put a post containing a list of them at some point.

How Will We Breathe Tomorrow? – Working with Open Government Data

As mentioned before, Jessica Broscheit is conducting a workshop about air quality and urban data at the Creative Space for Technical Innovations at Hamburg’s University of Applied Sciences. It’s called “How Will We Breathe Tomorrow” and is part of the A/D/A Hamburg 2016, a conference about future utopias for today’s urban citizen. During the workshop people can learn about government efforts to collect and share air quality data in open government data platforms and develop their own air quality monitoring device to experiment with visual, haptic and acoustic ways to explore data.


AIR MASK

Last year I worked with Jessica Broscheit und Hannes Sieg on another project within the “Next Media” master program at the University of Applied Sciences Hamburg (HAW Hamburg), called “Air Mask”. It involved research into air quality data and open government data platforms and lead to the development of a design fiction prototype of an air mask used for monitoring environmental data.

The collected data can be compared globally through a developed standardisation process and local air quality data was visualised on the mask itself in an easy to understand 3-colored alarm system. Just recently, Jessica created a website to document these projects.

Air Mask from Jessica Broscheit on Vimeo.

 

The Art Of Telling No Story – Data-Driven Journalism

311 calls New York
There were 34,522 complaints called in to 311 between September 8 and September 15, 2010. Here are the most common, plotted by time of day. Illustration: Pitch Interactive

Recently I wrote about data-driven journalism and whether it is worth the effort in regards to their monetisation potential for publishing companies. Although there are definitely great and interesting stories to be told with large data sets, it seems unlikely that the immense costs involved in the process of creating these stories can be justified within the current framework of digital business models within the publishing industry.

Still many data-driven stories and corresponding data visualisations seem interesting (e.g. in form of infographics) or even insanely beautiful (e.g. in form of maps or graphs). There is one problem with some kind of data visualisations in terms of storytelling though: they tell no story.

Consider the prominent visualisations of the 311 calls in the city of New York for instance. Although immensely beautiful and acknowledged by design experts around the globe, it’s hard to find any substantial story within the data or its visualisations. As shown above a plot of 311 calls by time of day with different colors for different types of complaints surely leads to a beautiful image, but there is no real story behind it.

The facts that there are more calls during the day, complaints about street condition seem to drop during the night and noise complaints are on the rise during the evening are hardly surprising. Even if these calls are plotted on a map, an attempt also explored with the 311 data, things do not get more interesting.

Still, the visualisations of the 311 calls not only look awesome, they received high praise and are on display at the Museum of Modern Art in NYC. I am not disputing the aesthetic qualities of the visualisations, but in terms of data-driven journalism or data-driven storytelling, there is not much to be found here.


 DISCLAIMER: This post has been written for the seminar “Online and Mobile Media” during an international research exchange at the University of New South Wales (UNSW) in Sydney, Australia, within the “Next Media” master program at the University of Applied Sciences Hamburg (HAW Hamburg) in 2016. For more information or any questions please contact me at mail@moritzrecke.com.

Is Data Journalism Worth The Effort?

The Wikileaks War Logs (The Guardian)
The Wikileaks War Logs (The Guardian)

Data-driven Journalism is grounded in calls for open access to information and transparency and has strong links government related open data initiatives, making public data available in standardised and open formats. It aims at the process of filtering data and telling new and interesting stories with conditioned data sets rather than just using the data as a source.

The most prominent example of data-driven journalism is the case of The Guardian and Wikileaks, where data has been transformed into interactive visualisations to allow a exploration of the data by the user itself.

It is clear by the amount of data alone, that these interactive visualisations can not be created manually. They need to be created with designers and developers working hand in hand, automating data processing and filtering to allow for the story to be explored by the user. This is a complete game changer for most news publishing corporations who traditionally had only journalists and maybe illustrators or photographers telling stories.

Ever since data-driven journalism became a mainstream element for many major stories, the newsroom process became much more technical and complex. This has also risen the cost for the newsroom staff to create the content for the publisher’s website. Since developers are in high demand all around the world, it is safe to assume that the costs for publisher’s grew substantially in this regard.

Considering the difficulties most publishers have to monetise their digital efforts successfully, it is doubtful that expensive data-driven stories will be able to compensate for that. As desirable as great stories such as the Wikileaks example might be, it is hard to find evidence that it is helping publishing companies to find new and working business models on the internet.


 DISCLAIMER: This post has been written for the seminar “Online and Mobile Media” during an international research exchange at the University of New South Wales (UNSW) in Sydney, Australia, within the “Next Media” master program at the University of Applied Sciences Hamburg (HAW Hamburg) in 2016. For more information or any questions please contact me at mail@moritzrecke.com.

Eric Fischer’s visual representation of pictures taken in San Francisco by tourists and locals

Eric Fischer - locals and tourists - San Francisco

datarep:

A visual representation of where pictures are taken in San Francisco as tourists and locals.

Source: Eric Fischer (flickr)

Looks nice, doesn’t it? Data artist Eric Fischer also build a worldwide map of local allegiances with MapBox and Twitter.

Some of his visualisations are exhibited at the MoMa, utilising the Flickr and Picasa API (like the image of San Francisco above), showing locals and tourists in metropolitan areas around the world. Berlin is among them as well.

Airbnb vs. Berlin? Was sagen die Daten?

Airbnb vs. Berlin? Was sagen die Daten?