Pre-publication version of a chapter by Matthew Zook, Mark Graham and Andrew Boulton in S. Mains, J. Cupples, and C. Lukinbeal. Mediated Geographies/Geographies of Media. Springer Science International Handbooks in Human Geography, (Forthcoming): “A key and distinguishing feature of society today is that its increasingly documented by crowd-sourced social media discourse about public experiences. Much of this social media content is geo-referenced and exists in layers of information draped over the physical world, invisible to the naked eye but accessible to range of digital (and often) mobile devices. When we access these information layers, they mediate the mundane practices of everyday life, (e.g., What or who is nearby? How do I move from point A to B) through the creation of augmented realities, i.e., unstable, context dependent representations of places brought temporary into being by combining the space of material and virtual experience.
These augmented realities, as particular representations of locations, places and events, are vigorously promoted or contested and thus become important spots in which power is exercised, much in the same way that maps have long had power to reinforce or challenge the status quo. However, because many of the processes and practices behind the creation of augmented realities are unseen, its power is often overlooked in the process of representation or place-making. This paper highlights the points at which power acts and demonstrate that all representations of place – including augmented realities derived from social media – are products of and productive of, social relationships and associated power relations.”
Building upon a case study of Abbottabad, Pakistan after the raid on Osama bin Laden’s compound we construct a four-part typology of the power relations emerging from social practices that enact augmented realities. These include: Distributed power, the complex and socially/spatially distributed authorship of user-generated geospatial content; Communication power, the ways in which particular representations gain prominence; language is a particularly key variable; Code power, the autonomy of software code to regulate actions, or mediate content, or ordering representations in particular ways; and Timeless power, the ways in which digital representations of place reconfigure temporal relationships, particularly sequence and duration, between people and events.
Business Models That Take Advantage of Open Data Opportunities
The OKFestival—hosted by the Open Knowledge Foundation—brought together more than 1,000 participants from around the globe working on various aspects of the open data agenda: the use of corporate data, open science research, government open data and crowdsourced data projects.
In a session held on the first day of the event, Borlongan facilitated an interactive workshop to help would-be entrepreneurs understand how startups are building business models that take advantage of open data opportunities to create sustainable, employment-generating businesses.
Citing research from the McKinsey Institute that calculates the value of open data to be worth $3 trillion globally, Borlongan said: “So the understanding of the open data process is usually: We throw open data over the wall, then we hold a hackathon, and then people will start making products off it, and then we make the $3 trillion.”
Borlongan argued that it is actually a “blurry identity to be an open data startup” and encouraged participants to unpack, with each of the startups presenting exactly how income can be generated and a viable business built in this space.
Jeni Tennison, from the U.K.’s Open Data Institute (which supports 15 businesses in its Startup Programme) categorizes two types of business models:
In a session held on the first day of the event, Borlongan facilitated an interactive workshop to help would-be entrepreneurs understand how startups are building business models that take advantage of open data opportunities to create sustainable, employment-generating businesses.
Citing research from the McKinsey Institute that calculates the value of open data to be worth $3 trillion globally, Borlongan said: “So the understanding of the open data process is usually: We throw open data over the wall, then we hold a hackathon, and then people will start making products off it, and then we make the $3 trillion.”
Borlongan argued that it is actually a “blurry identity to be an open data startup” and encouraged participants to unpack, with each of the startups presenting exactly how income can be generated and a viable business built in this space.
Jeni Tennison, from the U.K.’s Open Data Institute (which supports 15 businesses in its Startup Programme) categorizes two types of business models:
- Businesses that publish (but do not sell) open data.
- Businesses built on top of using open data.
Businesses That Publish but Do Not Sell Open Data
At the Open Data Institute, Tennison is investigating the possibility of an open address database that would provide street address data for every property in the U.K. She describes three types of business models that could be created by projects that generated and published such data:
Freemium: In this model, the bulk data of open addresses could be made available freely, “but if you want an API service, then you would pay for it.” Tennison pointed to lots of opportunities also to degrade the freemium-level data—for example, having it available in bulk but not at a particularly granular level (unless you pay for it), or by provisioning reuse on a share-only basis, but you would pay if you wanted the data for corporate use cases (similar to how OpenCorporates sells access to its data).
Cross-subsidy: In this approach, the data would be available, and the opportunities to generate income would come from providing extra services, like consultancy or white labeling data services alongside publishing the open data.
Network: In this business model, value is created by generating a network effect around the core business interest, which may not be the open data itself. As an example, Tennison suggested that if a post office or delivery company were to create the open address database, it might be interested in encouraging private citizens to collaboratively maintain or crowdsource the quality of the data. The revenue generated by this open data would then come from reductions in the cost of delivery services as the data improved accuracy.
Businesses Built on Top of Open Data
Six startups working in unique ways to make use of available open data also presented their business models to OKFestival attendees: Development Seed, Mapbox, OpenDataSoft, Enigma.io, Open Bank API, and Snips.
Startup: Development Seed
What it does: Builds solutions for development, public health and citizen democracy challenges by creating open source tools and utilizing open data.
Open data API focus: Regularly uses open data APIs in its projects. For example, it worked with the World Bank to create a data visualization website built on top of the World Bank API.
Type of business model: Consultancy, but it has also created new businesses out of the products developed as part of its work, most notably Mapbox (see below).
Startup: Enigma.io
What it does: Open data platform with advanced discovery and search functions.
Open data API focus: Provides the Enigma API to allow programmatic access to all data sets and some analytics from the Enigma platform.
Type of business model: SaaS including a freemium plan with no degradation of data and with access to API calls; some venture funding; some contracting services to particular enterprises; creating new products in Enigma Labs for potential later sale.
Startup: Mapbox
What it does: Enables users to design and publish maps based on crowdsourced OpenStreetMap data.
Open data API focus: Uses OpenStreetMap APIs to draw data into its map-creation interface; provides the Mapbox API to allow programmatic creation of maps using Mapbox web services.
Type of business model: SaaS including freemium plan; some tailored contracts for big map users such as Foursquare and Evernote.
Startup: Open Bank Project
What it does: Creates an open source API for use by banks.
Open data API focus: Its core product is to build an API so that banks can use a standard, open source API tool when creating applications and web services for their clients.
Type of business model: Contract license with tiered SLAs depending on the number of applications built using the API; IT consultancy projects.
Startup: OpenDataSoft
What it does: Provides an open data publishing platform so that cities, governments, utilities and companies can publish their own data portal for internal and public use.
Open data API focus: It’s able to route data sources into the portal from a publisher’s APIs; provides automatic API-creation tools so that any data set uploaded to the portal is then available as an API.
Type of business model: SaaS model with freemium plan, pricing by number of data sets published and number of API calls made against the data, with free access for academic and civic initiatives.
Startup: Snips
What it does: Predictive modeling for smart cities.
Open data API focus: Channels some open and client proprietary data into its modeling algorithm calculations via API; provides a predictive modeling API for clients’ use to programmatically generate solutions based on their data.
Type of business model: Creating one B2C app product for sale as a revenue-generation product; individual contracts with cities and companies to solve particular pain points, such as using predictive modeling to help a post office company better manage staff rosters (matched to sales needs) and a consultancy project to create a visualization mapping tool that can predict the risk of car accidents for a city….”
A framework for measuring smart cities
Paper by Félix Herrera Priano and Cristina Fajardo Guerra for the Proceedings of the 15th Annual International Conference on Digital Government Research: “Smart cities are an international phenomenon. Many cities are actively working to build or transform their models toward that of a Smart City. There is constant research and reports devoted to measuring the intelligence of cities through establishing specific methodologies and indicators (grouped by various criteria).
We believe the subject lacks a certain uniformity, which we aim to redress in this paper by suggesting a framework for properly measuring the smart level of a city.
Cities are complex and heterogeneous structures, which complicates comparisons between them. To address this we propose an N–dimensional measurement framework where each level or dimension supplies information of interest that is evaluated independently. As a result, the measure of a city’s intelligence is the result of the evaluations obtained for each of these levels.
To this end, we have typified the transformation (city to smart city) and the measurement (smart city ranking) processes.”
Big Money, Uncertain Return
Mary K. Pratt in a MIT Technology Review Special Report on Data-Driven Health Care: “Hospitals are spending billions collecting and analyzing medical data. The one data point no one is tracking: the payoff…. Ten years ago, Kaiser Permanente began building a $4 billion electronic-health-record system that includes a comprehensive collection of health-care data ranging from patients’ treatment records to research-based clinical advice. Now Kaiser has added advanced analytics tools and data from more sources, including a pilot program that integrates information from patients’ medical devices.
Faced with new government regulations and insurer pressure to control costs, other health-care organizations are following Kaiser’s example and increasing their use of analytics. The belief: that mining their vast quantities of patient data will yield insights into the best treatments at the lowest cost.
But just how big will the financial payoff be? Terhilda Garrido, vice president of health IT transformation and analytics at Kaiser, admits she doesn’t know. Nor do other health-care leaders. The return on investment for health-care analytics programs remains elusive and nearly impossible for most to calculate…
Opportunities to identify the most effective treatments could slip away if CIOs and their teams aren’t able to quantify the return on their analytics investments. Health-care providers are under increasing pressure to cut costs in an era of capped billing, and executives at medical organizations won’t okay spending their increasingly limited dollars on data warehouses, analytics software, and data scientists if they can’t be sure they’ll see real benefit.
A new initiative at Cleveland Clinic shows the opportunities and challenges. By analyzing patients’ records on their overall health and medical conditions, the medical center determines which patients coming in for hip and knee replacements can get postoperative services in their own homes (the most cost-effective option), which ones will need a short stay in a skilled nursing facility, and which ones will have longer stints in a skilled nursing facility (the most costly option). The classifications control costs while still ensuring the best possible medical outcomes, says CIO C. Martin Harris.
That does translate into real—and significant—financial benefits, but Harris wonders how to calculate the payoff from his data investment. Should the costs of every system from which patient data is pulled be part of the equation in addition to the costs of the data warehouse and analytics tools? Calculating how much money is saved by implementing better protocols is not straightforward either. Harris hesitates to attribute better, more cost-effective patient outcomes solely to analytics when many other factors are also likely contributors…”
The People’s Platform
Book Review by Tim Wu in the New York Times: “Astra Taylor is a documentary filmmaker who has described her work as the “steamed broccoli” in our cultural diet. Her last film, “Examined Life,” depicted philosophers walking around and talking about their ideas. She’s the kind of creative person who was supposed to benefit when the Internet revolution collapsed old media hierarchies. But two decades since that revolution began, she’s not impressed: “We are at risk of starving in the midst of plenty,” Taylor writes. “Free culture, like cheap food, incurs hidden costs.” Instead of serving as the great equalizer, the web has created an abhorrent cultural feudalism. The creative masses connect, create and labor, while Google, Facebook and Amazon collect the cash.
Taylor’s thesis is simply stated. The pre-Internet cultural industry, populated mainly by exploitative conglomerates, was far from perfect, but at least the ancien régime felt some need to cultivate cultural institutions, and to pay for talent at all levels. Along came the web, which swept away hierarchies — as well as paychecks, leaving behind creators of all kinds only the chance to be fleetingly “Internet famous.” And anyhow, she says, the web never really threatened to overthrow the old media’s upper echelons, whether defined as superstars, like Beyoncé, big broadcast television shows or Hollywood studios. Instead, it was the cultural industry’s middle classes that have been wiped out and replaced by new cultural plantations ruled over by the West Coast aggregators.
It is hard to know if the title, “The People’s Platform,” is aspirational or sarcastic, since Taylor believes the classless aura of the web masks an unfair power structure. “Open systems can be starkly inegalitarian,” she says, arguing that the web is afflicted by what the feminist scholar Jo Freeman termed a “tyranny of structurelessness.” Because there is supposedly no hierarchy, elites can happily deny their own existence. (“We just run a platform.”) But the effects are real: The web has reduced professional creators to begging for scraps of attention from a spoiled public, and forced creators to be their own brand.
…
The tech industry might be tempted to dismiss Taylor’s arguments as merely a version of typewriter manufacturers’ complaints circa 1984, but that would be a mistake. “The People’s Platform” should be taken as a challenge by the new media that have long claimed to be improving on the old order. Can they prove they are capable of supporting a sustainable cultural ecosystem, in a way that goes beyond just hosting parties at the Sundance Film Festival?
We see some of this in the tech firms that have begun to pay for original content, as with Netflix’s investments in projects like “Orange Is the New Black.” It’s also worth pointing out that the support of culture is actually pretty cheap. Consider the nonprofit ProPublica, which employs investigative journalists, and has already won two Pulitzers, all on a budget of just over $10 million a year. That kind of money is a rounding error for much of Silicon Valley, where losing billions on bad acquisitions is routinely defended as “strategic.” If Google, Apple, Facebook and Amazon truly believe they’re better than the old guard, let’s see it.”
See : THE PEOPLE’S PLATFORM. Taking Back Power and Culture in the Digital Age By Astra Taylor, 276 pp. Metropolitan Books/Henry Holt & Company.
Indonesian techies crowdsource election results
The Indonesian techies, who work for multinational companies, were spurred into action after both presidential candidates claimed victory and accused each other of trying to rig the convoluted counting process, raising fears that the country’s young democracy was under threat.
Mr Najib and two friends took advantage of the decision by the national election commission (KPU) to upload the individual results from Indonesia’s 480,000 polling stations to its website for the first time, in an attempt to counter widespread fears about electoral fraud.
The three Indonesians scraped the voting data from the KPU website on to a database and then recruited 700 friends and acquaintances through Facebook to type in the results and check them. They uploaded the data to a website called kawalpemilu.org, which means “guard the election” in Indonesian.
Throughout the process, Mr Najib said he had to fend off hacking attacks, forcing him to shift data storage to a cloud-based service. The whole exercise cost $10 for a domain name and $0.10 for the data storage….”
Countable Wants To Make Politics A ‘Continual Conversation’
Cat Zakrzewski in Techcrunch: “Telling your senator how to vote is as easy as “liking” a Facebook picture, thanks to a new app from the creators of TV streaming service SideReel.
Countable, available for iOS and coming to Android soon, presents a succinct summary of each piece of legislation Congress is considering, along with a short one-sentence argument in favor of the bill or against it. You are then able to vote “yay” or “nay.” When you are logged in through Facebook, Countable can automatically generate a message and send it to your representatives based on your location.
Countable also keeps track of how the lawmakers vote and then informs you how your representatives’ votes stack up to your own, generating “compatibility rankings.”
Co-founders Bart Myers and Peter Arzhintar came up with Countable when trying to figure out their next move after selling SideReel in 2011. Myers said they wanted to move away from TV and into something Myers said was more meaningful. As they brainstormed ideas, they kept coming back to one.
“We kept coming back to the disconnect that the American people feel with their representatives, that disconnect that we felt ourselves,” Myers says. “We decided to take a new bent at it … create a product where … what my representatives are doing can basically be made bite-sized, pushed to me like updates from our friends pushed through Facebook.”
And browsing the app’s colorful interface feels a lot more like swiping through friends’ pictures than wading through pages of lengthy bills. Countable’s team, which includes writers and consultants with experience in both the Democratic and Republican parties, has prepared short summaries and explanations that are easy to understand. Myers says the app allows users to go as deep into an issue as they want, linking to media coverage and the full text of the bill…”
European Commission encourages re-use of public sector data
Press Release: “Today, the European Commission is publishing guidelines to help Member States benefit from the revised Directive on the re-use of public sector information (PSI Directive). These guidelines explain for example how to give access to weather data, traffic data, property asset data and maps. Open data can be used as the basis for innovative value-added services and products, such as mobile apps, which encourage investment in data-driven sectors. The guidelines published today are based on a detailed consultation and cover issues such as:
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Licencing: guidelines on when public bodies can allow the re-use of documents without conditions or licences; gives conditions under which the re-use of personal data is possible. For example:
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Public sector bodies should not impose licences when a simple notice is sufficient;
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Open licences available on the web, such as several “Creative Commons” licences can facilitate the re-use of public sector data without the need to develop custom-made licences;
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Attribution requirement is sufficient in most cases of PSI re-use.
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Datasets: presents five thematic dataset categories that businesses and other potential re-users are mostly interested in and could thus be given priority for being made available for re-use. For example:
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Postcodes, national and local maps;
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Weather, land and water quality, energy consumption, emission levels and other environmental and earth data;
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Transport data: public transport timetables, road works, traffic information;
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Statistics: GDP, age, health, unemployment, income, education etc.;
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Company and business registers.
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Cost: gives an overview on how public sector bodies, including libraries, museums and archives, should calculate the amount they should charge re-users for data. For example:
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Where digital documents are downloaded electronically a no‑cost policy is recommended;
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For cost-recovery charging, any income generated in the process of collecting or producing documents, e.g. from registration fees or taxes, should be subtracted from the total costs incurred so as to establish the ‘net cost’ of collection, production, reproduction and dissemination.
European Commission Vice President @NeelieKroesEU said: “This guidance will help all of us benefit from the wealth of information public bodies hold. Opening and re-using this data will lead to many new businesses and convenient services.“
An independent report carried out by the consultants McKinsey in 2013 claimed that open data re-use could boost the global economy hugely; and a 2013 Spanish studyfound that commercial re-users in Spain could employ around 10,000 people and reach a business volume of €900 million….”
See also Speech by Neelie Kroes: Embracing the open opportunity
France: Rapport de la Commission Open Data en santé
“La Commission « open data en santé », qui s’est réunie de novembre 2013 à mai 2014, avait pour mission de débattre, dans un cadre pluraliste associant les parties prenantes, des enjeux et des propositions en matière d’accès aux données de santé.
Ce rapport, remis le 9 juillet 2014 à Marisol Touraine, Ministre des Affaires sociales et de la Santé, retrace les travaux et discussions de la Commission :
Ce rapport, remis le 9 juillet 2014 à Marisol Touraine, Ministre des Affaires sociales et de la Santé, retrace les travaux et discussions de la Commission :
- Un panorama de l’existant (partie 1) : définitions des concepts, état du droit, présentation de la gouvernance, présentation de l’accès aux données du SNIIRAM et du PMSI, cartographie des données de santé et enseignements tirés des expériences étrangères ;
- Les enjeux pour l’avenir (partie 2) ;
- Les actions à mener (partie 3) : données à ouvrir en open data, orientations en matière de données réidentifiantes, données relatives aux professionnels et aux établissements.
Ce rapport a été adopté consensuellement par l’ensemble des membres de la commission, qui partagent des attentes communes et fortes.”
Rapport final commission open data (pdf – 1 Mo) – [09/07/2014] – [MAJ : 09/07/2014]
Facebook Nation
Essay by Leonidas Donskis in the Hedgehog Review: “A German anthropologist who lived in England and was studying the society and culture of Kosovo Albanians once said something that lodged firmly in my memory: Whenever she wanted to make an interesting thought or position available to Albanian students or intellectuals, she simply published it on her Facebook page. “You don’t have to add a comment or explain anything,” she said with a smile. “The posting of it on Facebook is a sure sign that the message is a good one.”
She promised to perform this operation with a few thoughts of mine she had heard and liked in one of my lectures. When she noticed my surprise, she cheerfully explained that the Albanians considers themselves such a particularly dispersed lot, such a diaspora nation par excellence, that they are inclined to view themselves as a coherent collectivity only on Facebook. Without it, their friends, relatives, and family members living in Albania and elsewhere would have no tangible ties to one another.
This made me think that today’s version of Ahasver, the Wandering Jew of legend, is a Facebook user, and that Facebook—not the physical world—is where that displaced person wanders.
The Facebook Nation is host to an ongoing referendum in which its denizens cast their ballots daily, hourly, even minute by minute. Let’s make no mistake about what it means to be in this peculiar digital republic. For a lover, as Milan Kundera put it, to be is to live in the eye of one’s beloved. And what is it to be for people who don’t know where they are or where they want to be or even if they exist at all? Quite simply, it is to be liked on Facebook.
Facebook is where everyone becomes his or her own journalist, a situation that has forced real journalists to become Facebooking and tweeting simulacra of their former selves, or else to abandon journalism for other pursuits, whether literary or academic or something altogether different. Évariste Gamelin, the protagonist of Anatole France’s 1912 novel Les dieux ont soif (The Gods Are Thirsty), is a painter, a passionate disciple of Jacques Louis David, and a young fanatic who doesn’t know whether he is fatally in love with his charming girlfriend or with his mother, the Revolution. He believes that after the Revolution every citizen will become a judge of himself and of the Republic. But modernity plays a joke on him: It does not fulfill this promise. It had no intention of doing so. Instead of turning into judges, we all became journalists…”