Inside the ‘Wikipedia of Maps,’ Tensions Grow Over Corporate Influence


Corey Dickinson at Bloomberg: “What do Lyft, Facebook, the International Red Cross, the U.N., the government of Nepal and Pokémon Go have in common? They all use the same source of geospatial data: OpenStreetMap, a free, open-source online mapping service akin to Google Maps or Apple Maps. But unlike those corporate-owned mapping platforms, OSM is built on a network of mostly volunteer contributors. Researchers have described it as the “Wikipedia for maps.”

Since it launched in 2004, OpenStreetMap has become an essential part of the world’s technology infrastructure. Hundreds of millions of monthly users interact with services derived from its data, from ridehailing apps, to social media geotagging on Snapchat and Instagram, to humanitarian relief operations in the wake of natural disasters. 

But recently the map has been changing, due the growing impact of private sector companies that rely on it. In a 2019 paper published in the ISPRS International Journal of Geo-Information, a cross-institutional team of researchers traced how Facebook, Apple, Microsoft and other companies have gained prominence as editors of the map. Their priorities, the researchers say, are driving significant change to what is being mapped compared to the past. 

“OpenStreetMap’s data is crowdsourced, which has always made spectators to the project a bit wary about the quality of the data,” says Dipto Sarkar, a professor of geoscience at Carleton University in Ottawa, and one of the paper’s co-authors. “As the data becomes more valuable and is used for an ever-increasing list of projects, the integrity of the information has to be almost perfect. These companies need to make sure there’s a good map of the places they want to expand in, and nobody else is offering that, so they’ve decided to fill it in themselves.”…(More)”.

Public Policy Analytics: Code & Context for Data Science in Government


Open Access Book by Ken Steif: “… teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R. Each of the eight chapters provides a detailed case study, showing readers: how to develop exploratory indicators; understand ‘spatial process’ and develop spatial analytics; how to develop ‘useful’ predictive analytics; how to convey these outputs to non-technical decision-makers through the medium of data visualization; and why, ultimately, data science and ‘Planning’ are one and the same. A graduate-level introduction to data science, this book will appeal to researchers and data scientists at the intersection of data analytics and public policy, as well as readers who wish to understand how algorithms will affect the future of government….(More)”.

Spatial information and the legibility of urban form: Big data in urban morphology


Paper by Geoff Boeing: “Urban planning and morphology have relied on analytical cartography and visual communication tools for centuries to illustrate spatial patterns, conceptualize proposed designs, compare alternatives, and engage the public. Classic urban form visualizations – from Giambattista Nolli’s ichnographic maps of Rome to Allan Jacobs’s figure-ground diagrams of city streets – have compressed physical urban complexity into easily comprehensible information artifacts. Today we can enhance these traditional workflows through the Smart Cities paradigm of understanding cities via user-generated content and harvested data in an information management context. New spatial technology platforms and big data offer new lenses to understand, evaluate, monitor, and manage urban form and evolution. This paper builds on the theoretical framework of visual cultures in urban planning and morphology to introduce and situate computational data science processes for exploring urban fabric patterns and spatial order. It demonstrates these workflows with OSMnx and data from OpenStreetMap, a collaborative spatial information system and mapping platform, to examine street network patterns, orientations, and configurations in different study sites around the world, considering what these reveal about the urban fabric. The age of ubiquitous urban data and computational toolkits opens up a new era of worldwide urban form analysis from integrated quantitative and qualitative perspectives….(More)”.

The Rise of Urban Commons


Blogpost by Alessandra Quarta and Antonio Vercellone: “In the last ten years, the concept of the commons became popular in social studies and political activism and in some countries domestic lawyers have shared the interest for this notion. Even if an (existing or proposed) statutory definition of the commons is still very rare, lawyers get familiar with the concept of the commons through the filter of property law, where such a concept has been quite discredited. In fact, approaching property law, many students of different legal traditions learn the origins of property rights revolving on the “tragedy of the commons”, the “parable” made famous by Garrett Hardin in the late nineteen-sixties. According to this widespread narrative, the impossibility to avoid the over-exploitation of those resources managed through an open-access regime determines the necessity of allocating private property rights. In this classic argument, the commons appear in a negative light: they represent the impossibility for a community to manage shared resources without concentrating all the decision-making powers in the hand of a single owner or of a central government. Moreover, they represent the wasteful inefficiency of the Feudal World.

This vision has dominated social and economic studies until 1998, when Elinor Ostrom published her famous book Governing the commons, offering the results of her research on resources managed by communities in different parts of the world. Ostrom, awarded with the Nobel Prize in 2009, demonstrated that the commons are not necessarily a tragedy and a place of no-law. In fact, local communities generally define principles for their government and sharing in a resilient way avoiding the tragedy to occur. Moreover, Ostrom defined a set of principles for checking if the commons are managed efficiently and can compete with both private and public arrangements of resource management.

Later on, under an institutional perspective, the commons became the tool of contestation of political and economic mainstream dogmas, including the unquestionable efficiency of both the market and private property in the allocation of resources. The research of new tools for managing resources has been carried out in several experimentations that generally occurs at the local and urban level: scholars and practitioners define these experiences as ‘urban commons’….(More)”.

Nowcasting Gentrification Using Airbnb Data


Paper by Shomik Jain, Davide Proserpio, Giovanni Quattrone, and Daniele Quercia: “There is a rumbling debate over the impact of gentrification: presumed gentrifiers have been the target of protests and attacks in some cities, while they have been welcome as generators of new jobs and taxes in others. Census data fails to measure neighborhood change in real-time since it is usually updated every ten years. This work shows that Airbnb data can be used to quantify and track neighborhood changes. Specifically, we consider both structured data (e.g. number of listings, number of reviews, listing information) and unstructured data (e.g. user-generated reviews processed with natural language processing and machine learning algorithms) for three major cities, New York City (US), Los Angeles (US), and Greater London (UK). We find that Airbnb data (especially its unstructured part) appears to nowcast neighborhood gentrification, measured as changes in housing affordability and demographics. Overall, our results suggest that user-generated data from online platforms can be used to create socioeconomic indices to complement traditional measures that are less granular, not in real-time, and more costly to obtain….(More)”.

An Open Data Team Experiments with a New Way to Tell City Stories


Article by  Sean Finnan: “Can you see me?” says Mark Linnane, over Zoom, as he walks around a plastic structure on the floor of an office at Maynooth University. “That gives you some sense of the size of it. It’s 3.5 metres by 2.”

Linnane trails his laptop’s webcam over the surface of the off-white 3D model, giving a birds-eye view of tens of thousands of tiny buildings, the trails of roads and the clear pathway of the Liffey.

This replica of the heart of the city from Phoenix Park to Dublin Port was created to scale by the university’s Building City Dashboards team, using data from the Ordnance Survey Ireland.

In the five years since they started to grapple with the question of how to present data about the city in an engaging and accessible way, the team has experimented with virtual reality, and augmented reality – and most recently, with this new form of mapping, which blends the lego-like miniature of Dublin’s centre with changeable data projected on.

This could really come into its own as a public exhibit if they start to tell meaningful data-driven and empirical stories, says Linnane, a digital exhibition developer at Maynooth University.

Stories that are “relevant in terms of the everyday daily lives of people who will be coming to see it”, he says.

Layers of Meaning

Getting the projector that throws the visualisations onto the model to work right was Linnane’s job, he says.

He had to mesh the Ordnance Survey data with others that showed building heights for example. “Every single building down to the sheds in someone’s garden have a unique identifier,” says Linnane.

Projectors are built to project onto flat surfaces and not 3D models so that had to be finessed, too, he says. “Every step on the way was a new development. There wasn’t really a process there before.”

The printed 3D model shows 7km by 4km of Dublin and 122,355 structures, says Linnane. That includes bigger buildings but also small outbuildings, railway platforms, public toilets and glasshouses – all mocked up and serving as a canvas for a kaleidoscope of data.

“We’re just projecting data on to it and seeing what’s going on with that,” says Rob Kitchin, principal investigator at Maynooth University’s Programmable City project….(More)”

Image of model courtesy of Mark Linnane.

Participation and the pandemic: how planners are keeping democracy alive, online


Viewpoint by Dan Milz and Curt D. Gervich: “….The COVID-19 pandemic has paved the way for a multitude of experiments in e-democracy as local governments strive to continue to hold public meetings; make and implement plans; issue permits, variances and zoning decisions; and gather public input while under quarantine. This paper anecdotally discusses the role of online participatory technologies (OPTs) during this time.

Amidst the obvious impacts, COVID-19 also represents a threat to public participation. Because meeting in person is too risky, local leaders are cautious about hosting meetings in which citizens, government agents and elected officials gather together in one place. Consequently, municipal and county governments, among others, are taking the public’s business online. The purpose of this Viewpoint is to jump-start a conversation about how we prepare planners for a future in which in-person meetings are not guaranteed and how planners might continue to incorporate new technologies when face-to-face meetings resume….(More)”.

Mapping urban temperature using crowd-sensing data and machine learning


Paper by Marius Zumwald, Benedikt Knüsel, David N.Bresch and Reto Knutti: :”Understanding the patterns of urban temperature a high spatial and temporal resolution is of large importance for urban heat adaptation and mitigation. Machine learning offers promising tools for high-resolution modeling of urban heat, but it requires large amounts of data. Measurements from official weather stations are too sparse but could be complemented by crowd-sensed measurements from citizen weather stations (CWS). Here we present an approach to model urban temperature using the quantile regression forest algorithm and CWS, open government and remote sensing data. The analysis is based on data from 691 sensors in the city of Zurich (Switzerland) during a heat wave using data from for 25-30th June 2019. We trained the model using hourly data from for 25-29th June (n = 71,837) and evaluate the model using data from June 30th (n = 14,105). Based on the model, spatiotemporal temperature maps of 10 × 10 m resolution were produced. We demonstrate that our approach can accurately map urban heat at high spatial and temporal resolution without additional measurement infrastructure. We furthermore critically discuss and spatially map estimated prediction and extrapolation uncertainty. Our approach is able to inform highly localized urban policy and decision-making….(More)”.

Silicon Valley’s next goal is 3D maps of the world — made by us


Tim Bradshaw at the Financial Times: “When technology transformed the camera, the shift from film to digital sensors was just the beginning. As standalone cameras were absorbed into our phones, they gained software smarts, enabling them not only to capture light but also to understand the contents of a photo and even recognise people in it.

A similar transformation is now starting to happen to maps — and it too is powered by those advances in camera technology. In the next 20 years, our collective understanding of a “map” will be unrecognisable from the familiar grid of roads and places that has endured even as the A-Z street atlas has been supplanted by Google Maps.

Before long, countless objects and places will be captured and recreated in 3D digital models that we can view through our phones or even, at some stage, on headsets. This digital world might be populated by our avatars, turned into a playing field for new kinds of games or used to discover routes, buildings and services around us. 

Nobody seems sure yet what the killer app for this “digital twin” of Planet Earth might be, but that hasn’t stopped Silicon Valley from racing to build it anyway. Facebook, Apple, Google and Microsoft, as well as the developers of Snapchat and Pokémon Go, are all hoping to bring this “mirrorworld” to life, as a precursor to the augmented-reality (AR) glasses that many in tech see as the next big thing.

To place virtual objects in our world, our devices need to know the textures and contours of their surroundings, which GPS cannot see. But instead of sending out cars with protruding cameras to scan the world, as Google did to build Street View over the past decade and a half, these maps will be plotted by hundreds of millions of users like you and me. The question is whether we even realise that we have been dragooned into Silicon Valley’s army of cartographers. They cannot do it without us.

This month, Google said it would ask Maps users to upload photos to Street View using their smartphones for the first time. Only handsets running its AR software can contribute.  As Michael Abrash, chief scientist at Facebook’s Oculus headset unit, recently told Fast Company magazine: “Crowdsourcing has to be the primary way that this works. There is no other way to scale.”…(More)”.

For America’s New Mayors, a Chance to Lead with Data


Article by Zachary Markovits and Molly Daniell:”While the presidential race drew much of the nation’s attention this year, voters also chose leaders in 346 mayoral elections, as well as many more city and county commission and council races, reshaping the character of government leadership from coast to coast.

These newly elected and re-elected leaders will enter office facing an unprecedented set of challenges: a worsening pandemic, weakened local economies, budget shortfalls and a reckoning over how government policies have contributed to racial injustice. To help their communities “build back better”—in the words of the new President-elect—these leaders will need not just more federal support, but also a strategy that is data-driven in order to protect their residents and ensure that resources are invested where they are needed most.

For America’s new mayors, it’s a chance to show the public what effective leadership looks like after a chaotic federal response to Covid-19—and no response can be fully effective without putting data at the center of how leaders make decisions.

Throughout 2020, we’ve been documenting the key steps that local leaders can take to advance a culture of data-informed decision-making. Here are five lessons that can help guide these new leaders as they seek to meet this moment of national crisis:

1. Articulate a vision

The voice of the chief executive is galvanizing and unlike any other in city hall. That’s why the vision for data-driven government must be articulated from the top. From the moment they are sworn in, mayors have the opportunity to lean forward and use their authority to communicate to the whole administration, council members and city employees about the shift to using data to drive policymaking.

Consider Los Angeles Mayor Eric Garcetti who, upon coming into office, spearheaded an internal review process culminating in this memo to all general managers stressing the need for a culture of both continuous learning and performance. In this memo, he creates urgency, articulates precisely what will change and how it will affect the success of the organization as well as build a data-driven culture….(More)”.