Data Urbanism

Using data to understand and describe the city. Alvin Chua RxD, ASRO, KU Leuven

[mostlysignssomeportents]

Spoofing GPS is surprisingly easy; detecting it is surprisingly hard

GPS security is increasingly implicated in both physical and information security: from steering a super-yacht (or a super-tanker) into pirate-friendly waters to diverting self-driving cars or even unlocking geo-tagged tokens and AR game objectives.

GPS receivers compare timestamped signals from a constellation of satellites, inferring their position through calculations on the lightspeed lag from each signal. Faking the signal from these distant satellites with nearby spoofing stations isn’t trivial, but it’s not transcendentally hard, either – and there’s plenty of reason to suspect that it will get easier, thanks to faster, cheaper computers, carried by autonomous vehicles (both ground- and air-based).

Detecting a spoofed GPS signal is hard. The computational load associated with cryptographic signatures on the signal is high, and the inability to interact with the sending satellites makes it impossible to use a challenge-response protocol where the receiver generates a random number, signs it with the satellite’s public key, sends it to the satellite and then gets it back from the satellite signed with the sat’s private key, then sets up a one-time session key.

Other tactics for validating signals involve direction-detection (raising the bar on spoofers, who’d have to physically array their fake base-stations in spatially plausible locations – think of a cluster of drones) and distortion-detection.

But both of these tactics have easily imagined countermeasures, and both are difficult/costly to implement.

The US military has an encrypted, hardened GPS system for its own use, but that is also potentially vulnerable, and in any event, they’re not interested in sharing.

http://boingboing.net/2016/08/04/spoofing-gps-is-surprisingly-e.html

[dataurbanism]

The term intuitive was used when participants discussed creating a visualization for a specific type of user. [...] intuitive visuals often appeal to what they termed tough critics of their scientific findings. Intuitive visuals were desired, too, to simplify difficult concepts and data transformations.

A conceptual model for characterizing the problem domain. Winters et al. 2015

[dataurbanism]

Interactive maps: What we know and what we need to know. Robert E. Roth. 2013

[dataurbanism]

City Cybernetics. Robert Brown. 1969.

[futuramb]

[…]it is not population or territorial size that drives world-city status, but economic weight, proximity to zones of growth, political stability, and attractiveness for foreign capital. In other words, connectivity matters more than size.

[dataurbanism]

Strategic spatial planning: a historical review of approaches, its recent revival, and an overview of the state of the art in Italy. Francesca Sartorio. 2005.

[purestform]

[dataurbanism]

Visual clutter remains a challenge in cartography, especially for web maps depicting voluminous, unfiltered collections of point type data. This issue is particularly prevalent in datasets generated in cities due to urban density. Professor Andrew Vande Moere and myself developed BinSq  (abbreviated Bin2), a novel gridded dot density mapping technique to overcome this challenge. We demonstrate this technique on a large dataset of language referenced, geotagged tweets to reveal language communities in Brussels. The figure above compares our technique to the [a] standard dot map and six related solutions namely: [b] jittering, [c] refinement, [d] distortion with pixel map as well as [e] aggregation with categorical binning, [f] splatter plot and [g] dot density map. Our output is depicted in [h]. An implementation of BinSq in Java is avaliable on GitHub. Read our paper for a complete description of the technique.

[dataurbanism]

Can Engineers Build Inclusive Smart Cities?

Dr. Anthony Townsend, Delft University of Technology, January 9, 2015

"The smart city will — to a great extent — will be exclusionary by default. [...] This is the great downside of ubiquity. The smart city is full of barriers. First you must be able to connect to the network. Then you must show your credentials by logging in. It’s like showing your passport to take a walk in the park. [...]" Good insight into tomorrow’s issues on living in the smart cities. However, other solutions exists apart from adding (yet more layers of) inclusionary measures. Perhaps not all cities need to be smart. Perhaps not everyone needs to live in cities either. Maybe effective urban-rural zoning policies can address this challenge in certain ways.

[dataurbanism]

Using MapTable® to Learn About Sustainable Urban Development. Pelzer et al. 2013

[dataurbanism]

"In science, if you know what you are doing, you should not be doing it. In engineering, if you do not know what you are doing, you should not be doing it. Of course, you seldom, if ever, see either pure state."

The Art of Doing Science and Engineering. Richard Hamming. 1997

[dataurbanism]

I first wrote about `smart cities' almost as soon as I began writing these editorials in the early 1980s. Back then, the PC (personal computer) or micro (microcomputer) was sweeping the world of computing and hard on its heels came the development of local area networks (LANs). In fact, LANs, as many other features of the PC, had been invented in the 1970s at Xerox Parc but it was not until the 1980s that they became ubiquitous and this heralded an age of wide area networks (WANs) that paralleled the Internet in general. What I remember most of those years were my visits to the Far Eastöin 1986 to Japan where I saw for the first time large-screen technologies in shopping centres and the implementation of fibre optic networks for wide-area Internet access, in the name of regenerating old industrial landscapes as they prepared for the postindustrial age (Batty, 1987). In the late 1980s, when I visited Singapore, the city-state advertised itself as the `Intelligent Island', and my visits to the National Computer Board mightily impressed me. I heard about how routine services could be delivered to the entire population through WANs (Batty, 1997), two or so years before the World Wide Web was invented. What then came to pass in the 1990s was the fact that services everywhere could be delivered in similar ways across the web. Singapore is still in the vanguard.

Smart Cities, big Data. Michael Batty. 2012

[dataurbanism]

Ludwig Wittgenstein’s early definition “a model is a picture of reality” (1921, 8) suggests that the basic idea of a model is rooted in the philosophy of science and in scientific method. Yet it was not until the 1950s that the idea of a model began to be used widely in science, and then the classic definition of model was as “a simplification” rather than “a picture of reality” (Lowry 1965). This was the meaning ascribed to its use in the 1960s as the idea of a model gathered pace as a vehicle on which to develop good theory and applications in countless areas of the physical and social sciences.

New Developments in Urban Modeling: Simulation, Representation, and Visualisation. Michael Batty. 2003

[purestform]

If nothing else, boundaries could no longer be seen as a neutral graphic convenience. They carry too much conceptual baggage; they provide answers that are too easy. But searching for cartographies that don’t rely exclusively on borders is not just a question of deleting some lines. What’s needed is deep engagement with massive amounts of data: discovering variations in space becomes a design problem in itself, where the challenge is to navigate between the hopelessly simple and the hopelessly complex.

Cartography and the Reality of Boundaries. Bill Rankin. 2001. (via purestform)

[purestform]

Megalomaniacs confuse the map and the territory and think they can dominate all of Paris just because they do, indeed, have all of Paris before their eyes. Paranoiacs confuse the territory and the map and think they are dominated, observed, watched, just because a blind person absent-mindedly looks at some obscure signs in a four-by-eight meter room in a secret place

La Découverte.  Latour and Hermant. 1998 (via purestform)

[dataurbanism]

Skills & challenges involved in visualisation design in A nested model for visualization design and validation. Munzner. 2009.

[dataurbanism]

Primary data collection, to be useful, must be representative of the studied population and must be as free as possible from systematic bias.

A Method to Collect Detailed Tourist Flow Information. Gartner and Hunt. 1988

[dataurbanism]

Travel is the minimum price we pay to participate in out-of-home activities as individuals. Networks are the infrastructure we provide collectively to reduce these costs. Increasing urbanisation in conjunction with the growing depth of networks in terms of technologies put an emphasis on our ability to grow these networks in a way which strikes a compromise between their current and future costs, reliability and resilience.

Smart cities of the future, M. Batty et al. 2012