Street of Cities – ground sprawl

Information technology is shaping our relationship with the urban environment.

The internet and social media is a mirror of our societies and lifestyles.

We live in a society where our perception is based on millions of composed images.

 

The Hashtag is a lens, portraying a virtual space truer than the physical reality.

The database of #streets is a mirror of our navigation, perception and participation on public streets.

#Oxford Street is a parallel reality of Oxford street down the road, but more accurate.

It is made collectively by world sourcing.

Oxford Street as a physical entity, is a compound of collective architectures, but the Hashtag create hyper-multiplicity of authorships. The +600,000 images uploaded by 600,000 individual subject, are our acts of selective seeing and composing.

The taggable mirror street is a space of collective desires; comprised of different scales, different time frames, seasons, perspectives.

It is constantly under expansion and metamorphosis.

The lens of hashtag portrays streets with an alternate condition that is groundless, scale-less and timeless.

A new phenomenon of contemporary urban culture.

The project sees the necessity to celebrate public interactivity with the public street.

 

The Project is A Street of Cities.

The Street of Cities is a mirror of our collective desires in cities.

Each street is a microcosm of its belonged city, where material, façades, infrastructure, vegetation reflects its cultural identity.

Hashtag connects memories of streets from around the world.

They are memories of street fragment in a specific time, location, lighting, filter and ephemeral quality.

The Street of Cities is a condition where street fragments are detached from their contexts and conglomerate into a new virtual hybrid streetscape.

Street of Cities is simultaneously local and global, site-specific and site-less, singular and universal.

The Street of Cities sprawl like hyperlink connections, panning from image to image, panning between fragments of likeliness instead of proximity.

 

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