City Memory Visualization update (2) / 2 comments

New York landscape populated with status updates

New York landscape populated with status updates

The visualization continues to take shape (see these earlier posts for context). We are now parsing live data from Twitter and image tiles from the Google Maps API for the surface mesh. The user interface remains the point of focus at this point in time, though we are beginning to look for data parsing solutions to help construct the semantic pathways between status updates. Below are a few images of the latest progress.

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City Memory Visualization update

Sketch of geolocated tweets, manipulating the mesh surface below

Sketch of geolocated tweets, manipulating the mesh surface below

Joining the project is Liangjie Xia, a programmer and media artist based in New York and a recent graduate from ITP.

The current project focus is on a data landscape comprised of geocoded social updates, forming narrative pathways according to themes (we are evaluating Twitter, Flickr and Foursquare as data sources). As they occur, updates add points to a basemap of Taipei, cumulatively changing the elevation of the landscape. Updates, represented as nodes, are selectable, and articulate the landscape based on other thematically related updates. Finally, we are exploring toggling between two views: the surface mesh outlined above, and a view exchanging the mesh for narrative pathways, represented by hairlines connecting nodes related by topic and time.

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A Visualization of Urban Collective Memory

I am currently working with Jason Hsu, organizer of TEDx Taipei, and Edward Shen, recent MIT Media Lab graduate, on a data visualization project aiming to document urban memory in Taipei. The project began with a dialog Jason and I started at TEDActive in Palm Springs earlier this year. Jason recently wrote a blog article comparing my earlier work Pastiche with Jonathan Harris’ We Feel Fine.  As the project progresses, I will continue to post updates here. Below is a proposal that captures my initial thoughts on issues the visualization might seek to address.

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Search: from tool to content platform

There is a shift happening in search. In my last post, I tried to make the case that web content is becoming more decentralized, with aggregators (RSS readers, search engines, and social networks) playing an increasingly large role for the way that we absorb information online, and that this tendency presents new opportunities for the design of information. With this decentralization (or centralization, depending on your perspective), search engines themselves are changing from navigational tools to content platforms.

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Design and the decentralization of web content

Websites are the predominant platform for most of the information we absorb. Of course, the site itself isn’t always the primary vehicle, with RSS having established itself as an alternate form of consumption, and search engines offering a similar yet broader form of aggregation. This has lead to two main content experiences. In one mode, content is presented in context of the full offering, as part of a structural framework reflecting the identity of the source. In the other, content is represented generically and modularly alongside content from other sources.

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