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The cities and communities ....the present and the future - urban change.NET -
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IM Systems Big Data #Geospatial Analysis | #bigdata #datascience

A demonstration of infrastructure network faults from numerous sources using big data technology with Geospatial Analysis. 


Via Yves Mulkers
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Welcome to Dataland | #sensors #bigdata

Welcome to Dataland | #sensors #bigdata | The urban.NET | Scoop.it
Design fiction at the most magical place on Earth

Via 15marches
luiy's insight:

The MagicBand is the world’s largest and most diverse experiment in wearable data fashion. And like all fashion, MagicBands are classist. Automatic visits to Dataland are limited to guests who book their stay on Disney property. Those who visit Disney World for a day trip or who stay in a nearby, non-Disney owned hotel are limited to the old RFID credit card for their park tickets. But fear not, for MagicBands can be purchased for $12.95 at any Disney theme park gift shop. And everyone is allowed the opportunity to customize and personalize their MagicBands: “MagicSliders” sleeves and “MagicBandits” charms that bear the images of Disney characters can be purchased ($6.95-14.95) and attached to a MagicBand.

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Watch_Dogs WeAreData | #smartcities #opendata

Watch_Dogs WeAreData | #smartcities #opendata | The urban.NET | Scoop.it
Discover how data controls the cities of Paris, London and Berlin in these hyperconnected times.
luiy's insight:

Watch_Dogs WeareData gathers available geolocated datain a non-exhaustive way: we only display the information for which we have been given the authorization by the sources. Yet, it is already a huge amount of data. You may even watch what other users are looking at on the website through Facebook connect.

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Emeric Nectoux's curator insight, June 3, 2014 2:50 PM

Good visualization of streaming data geo-located. 

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"Natural #Cities" Emerge from Social Media Location #Data | #context #planing

"Natural #Cities" Emerge from Social Media Location #Data | #context #planing | The urban.NET | Scoop.it
Nobody agrees on how to define a city. But the emergence of “natural cities” from social media data sets may change that, say computational geographers.
luiy's insight:

Jiang and Miao began with a dataset from the Brightkite social network, which was active between 2008 and 2010. The site encouraged users to log in with their location details so that they could see other users nearby. So the dataset consists of almost 3 million locations in the US and the dates on which they were logged.

To start off, Jiang and Miao simply placed a dot on a map at the location of each login. They then connected these dots to their neighbours to form triangles that end up covering the entire mainland US.

 

Next, they calculated the size of each triangle on the map and plotted this size distribution, which turns out to follow a power law. So there are lots of tiny triangles but only a few large ones.

 

Finally, the calculated the average size of the triangles and then coloured in all those that were smaller than average. The coloured areas are “natural cities”, say Jiang and Miao.

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Mining #bicycle sharing data for generating insights into #sustainable transport systems I #smartcities #bigdata

luiy's insight:

The latest bike-share systems enable users to monitor cycle availability and docking station spaces via near real-time online maps. These websites often specify and supply an applications pro- gramming interface (API) for external software developers to ac- cess the underlying data. In addition, a number of system operators release datasets pertaining to individual journeys made over a particular time period. Both types of data offer insights in the usage of particular bike-shares and provide a ready basis for utilisation in transport research. A small number of previous stud- ies have been undertaken and generally concern the characteristics of a single city’s system, often with a focus on user demographics. Jensen et al. (2010), for example, analysed 11.6 million journeys of the Vélo’v bicycle sharing system in Lyon, constructing a map showing the likely flows of the bicycles across the city. Several characteristics emerged; namely greatly enhanced usage during public transport strikes, and variations in average speeds through the day such as for example, a small but significant increase in speed just before 9 a.m. as cycle commuters hurry to complete their journeys before the start of normal working hours. One intriguing result was that the average speed during the morning commute was greatest on Wednesdays, the authors conjecturing that this was due to a greater proportion of users on Wednesdays being men, due to the tradition of at-home childcare by women on this day. 

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Urban #Observatory Compare Cities | #smartcities #opendata

Urban #Observatory Compare Cities | #smartcities #opendata | The urban.NET | Scoop.it

Via bart rosseau
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bart rosseau's curator insight, July 15, 2013 4:14 AM

great concept, great layout and design. Curious to see if this will last!

luiy's comment, March 1, 2014 11:36 AM
I can see the interesting application in the are of #eDemocracy
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Measure of Landmark #Semantic Salience through #Geosocial Data Streams | #wayfinding #bigdata

Measure of Landmark #Semantic Salience through #Geosocial Data Streams | #wayfinding #bigdata | The urban.NET | Scoop.it
Research in the area of spatial cognition demonstrated that references to landmarks are essential in the communication and the interpretation of wayfinding instructions for human being. In order to detect landmarks, a model for the assessment of their salience has been previously developed by Raubal and Winter. According to their model, landmark salience is divided into three categories: visual, structural, and semantic. Several solutions have been proposed to automatically detect landmarks on t
luiy's insight:

Thus, we are asking the following global research question as a starting point: can we improve the urban intelligence using geosocial data generated by users of online social networks? We argue that geolocated content published on Facebook and Swarm can be exploited to enhance citizens’ spatial literacy. More precisely, check-ins datasets can be used to improve human wayfinding and smart mobility by detecting relevant semantic landmarks. Lots of research in wayfinding is done in order to enable individuals to reach as quickly as possible a desired destination, to help people with disabilities by designing cognitively appropriate orientation signs, and reduce the fact of being lost [16]. Therefore, designing tools that effectively support people’s wayfinding remains a major concern.

 

In order to defend our argument, we detail in the following section a brief state of art related to the concept of wayfinding. Then, we focus both on landmarks and systems designed for their automatic detection. The fourth section puts forward the reasons why check-ins are, in our opinion, a reliable source of information to identify semantic landmarks. More precisely, three scores based on Facebook and Swarm check-ins are suggested in order to measure landmark semantic salience. Finally, the last section of this article presents concrete examples where these scores are applied with real check-ins datasets harvested from Facebook and Foursquare APIs.

 

- See more at: http://www.mdpi.com/2220-9964/4/1/1/htm?utm_content=buffer9f115&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer#sthash.ohDKdQEJ.dpuf

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The #Algorithmic City | #smartcities #opendata

The #Algorithmic City | #smartcities #opendata | The urban.NET | Scoop.it
:snips - We Scale Cities
luiy's insight:

What else can we predict? In theory, any event that is not random, provided we have enough data to model the context. Examples include passenger load in public transports, availability of parking spots, traffic jams, waste production, energy consumption and revenues of a shop in a specific street. These all share a common underlying principle: use context rather than history to predict behavior.

 

In themselves, each of these predictions could lead to amazing new products and services. The real power though comes from integrating everything together and modeling an entire city and its interactions with people. For instance, if you can predict where people will need to go tomorrow, then you can create optimal bus routes, minimizing time to destination and walking distance, taking into account predicted traffic, weather and garbage collection schedules. In this ideal system, all services would be optimal and available to citizens at anytime. We call this new way of designing cities "Algorithmic Urbanism".

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Data Visualization Site's Running Route City Maps Look Like Prismacolor ID Sketches | #dataviz #urbanism

Data Visualization Site's Running Route City Maps Look Like Prismacolor ID Sketches | #dataviz #urbanism | The urban.NET | Scoop.it
"It nearly moved me to tears," a Ford executive once said of a Michael Santoro car design. "It's the best set of proportions I've ever seen on a sedan." In the early '90s Santoro was an upstart designer largely responsible for turning Chrysler's fortunes around with his radical cab-forward concepts and dropped-headlight-fender trucks, and me and my ID classmates were lucky enough to visit his Detroit studio. There we saw some of the most mind-blowing ID sketching I've ever

Via Siarhei Mardovich
luiy's insight:

By using data from fitness & location tracking apps, Yau is able to overlay hundreds of individual joggers' routes, just like Santoro's magic hands wielding a Prismacolor; but rather than newsprint, Yau's canvasses are maps of cities like New York, London, Paris, Chicago and more. In the cities with waterfronts, you can see that people really do like to run alongside water; and the build-up of lines looks like Santoro delineating a fender.

 

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Imagining the Future City: London 2062 I #smartcities #sustainability #freebook

Imagining the Future City: London 2062 I #smartcities #sustainability #freebook | The urban.NET | Scoop.it

As part of the UCL Grand Challenge of Sustainable Cities, the London 2062 project is gathering evidence about the forces and factors that shape London, identifying decision points, and debating how the city will change over the five decades between London 2012 and London 2062. This process involves synthesising the diverse expertise within the academic community at UCL and elsewhere, together with London’s citizens, government, professions, artists, media and other public institutions.


Via Claudia Mihai
luiy's insight:

Imagining the Future City: London 2062 (free download) is an edited collection based on the London 2062 project from UCL’s Grand Challenge of Sustainable Cities. The London 2062 project engaged academics, policy makers and practitioners, providing a forum for serious debate about the challenges and opportunities for London in the five decades following the Olympics.


The book is divided into four sections, considering London in terms of Things, Connections, Powerand Dreams. The book features contributions from leading academic thinkers at UCL and from those involved in shaping London on the ground, through policy and practice. The authors consider the future of London from multiple viewpoints, including transport, energy, smart infrastructure, water, population, housing and the economy.

 

The aim of this book, and the London 2062 programme, is to open discussion about the future of London. What is the future we want to see for London? Which priorities for a global city are in opposition? How can we meet carbon emission targets and deliver new infrastructure in the 21st Century?

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Intriguing Networks's curator insight, December 8, 2013 5:58 PM

LONDON CALLING - How will you influence the shape of your city get involved folks! Thank you @plevy

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#SmartCities of the future I #urban #bigdata

luiy's insight:

The concept of the smart city emerged during the last decade as a fusion of ideas about how information and communications technologies might improve the functioning of cities, enhancing their efficiency, improving their competitiveness, and providing new ways in which problems of poverty, social deprivation, and poor envi- ronment might be addressed [26]. The essence of the idea revolves around the need to coordinate and integrate technologies that have hitherto been developed separately from one another but have clear synergies in their operation and need to be coupled so that many new opportunities which will improve the quality of life can be realized. The term smart city in fact has many faces [40]. Intelligent cities, virtual cities, digital cities, information cities are all perspectives on the idea that ICT is central to the operation of the future city [1]. Our research will embrace this challenge in the belief that coupling, coordination and integration are required so that future and emerging technologies can best be exploited in the interests of the community at large. An essential strand in our approach is to use ICT to engage the community through diverse instruments and initiatives that build upon online engagement in solving the key problems of cities, using the kinds of computer-based tools, techniques, methods and organisational structures that we will research here. To focus our research, we define seven goals. 

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