Mapping information economy business with big data: findings from the UK

Curated on Posted on by Stefaan Verhulst

NESTA: “This paper uses innovative ‘big data’ resources to measure the size of the information economy in the UK.

Key Findings

  • Counts of information economy firms are 42 per cent larger than SIC-based estimates
  • Using ‘big data’ estimates, the research finds 225,800 information economy businesses in the UK
  • Information economy businesses are highly clustered across the country, with very high counts in the Greater South East, notably London (especially central and east London), as well as big cities such as Manchester, Birmingham and Bristol
  • Looking at local clusters, we find hotspots in Middlesbrough, Aberdeen, Brighton, Cambridge and Coventry, among others

Information and Communications Technologies – and the digital economy they support – are of enduring interest to researchers and policymakers. National and local government are particularly keen to understand the characteristics and growth potential of ‘their’ digital businesses.
Given the recent resurgence of interest in industrial policy across many developed countries, there is now substantial policy interest in developing stronger, more competitive digital economies. For example, the UK’s current industrial strategy combines horizontal interventions with support for seven key sectors, of which the ‘information economy’ is one.
The desire to grow high–tech clusters is often prominent in the policy mix – for instance, the UK’s Tech City UK initiative, Regional Innovation Clusters in the US and elements of ‘smart specialisation’ policies in the EU.
In this paper, NIESR and Growth Intelligence use novel ‘big data’ sources to improve our understanding of information economy businesses in the UK – that is, those involved in the production of ICTs. We use this experience to critically reflect on some of the opportunities and challenges presented by big data tools and analytics for economic research and policymaking.”
– See more at: http://www.nesta.org.uk/publications/mapping-information-economy-business-big-data-findings-uk-0#sthash.2ismEMr2.dpuf

Hungry Planet: Can Big Data Help Feed 9 Billion Humans?

Curated on Posted on by Stefaan Verhulst

John Roach at NBC News: “With a population set to hit 9 billion human beings by 2050, the world needs to grow more food —without cutting down forests and jungles, which are the climate’s huge lungs.

The solution, according to one soil management scientist, is Big Data.

Kenneth Cassman, an agronomist at the University of Nebraska, Lincoln, recently unveiled a new interactive mapping tool that shows in fine-grain detail where higher crop yields are possible on current arable land.

“By some estimates, 20 to 30 percent of greenhouse gas emissions are associated with agriculture and of that a large portion is due to conversion of natural systems like rainforests or grassland savannahs to crop production, agriculture,” Cassman told NBC News at a conference in suburban Seattle.

The only practical way to stop the conversion of wild lands to farmland is grow more food on land already dedicated to agriculture, he said. Currently, the amount of farmland used to produce rice, wheat, maize and soybean, he noted, is expanding at a rate of about 20 million acres a year.

Cassman and colleagues unveiled the Global Yield Gap and Water Productivity Atlas in October at the Water for Food conference. The atlas was six years and $6 million in the making and contains site-specific data on soil, climate and cropping systems to determine potential yield versus actual yield farm by farm in nearly 20 countries around the world. Projects are ongoing to secure data for 30 more countries….

A key initiative going forward is to teach smallholder farmers how to use the atlas, Cassman said. Until now, the tool has largely rested with agricultural researchers who have validated its promise of delivering information that can help grow more food on existing farmland….

Can Government Mine Tweets to Assess Public Opinion?

Curated on Posted on by Stefaan Verhulst

at Government Technology: “What if instead of going to a city meeting, you could go on Twitter, tweet your opinion, and still be heard by those in government? New research suggests this is a possibility.
The Urban Attitudes Lab at Tufts University has conducted research on accessing “big data” on social networking sites for civic purposes, according to Justin Hollander, associate professor in the Department of Urban and Environmental Policy and Planning at Tufts.
About six months ago, Hollander began researching new ways of accessing how people think about the places they live, work and play. “We’re looking to see how tapping into social media data to understand attitudes and opinions can benefit both urban planning and public policy,” he said.
Harnessing natural comments — there are about one billion tweets per day — could help governments learn what people are saying and feeling, said Hollander. And while formal types of data can be used as proxies for how happy people are, people openly share their sentiments on social networking sites.
Twitter and other social media sites can also provide information in an unobtrusive way. “The idea is that we can capture a potentially more valid and reliable view [of people’s] opinions about the world,” he said. As an inexact science, social science relies on a wide range of data sources to inform research, including surveys, interviews and focus groups; but people respond to being the subject of study, possibly affecting outcomes, Hollander said.
Hollander is also interested in extracting data from social sites because it can be done on a 24/7 basis, which means not having to wait for government to administer surveys, like the Decennial Census. Information from Twitter can also be connected to place; Hollander has approximated that about 10 percent of all tweets are geotagged to location.
In its first study earlier this year, the lab looked at using big data to learn about people’s sentiments and civic interests in New Bedford, Mass., comparing Twitter messages with the city’s published meeting minutes.
To extract tweets over a six-week period from February to April, researchers used the lab’s own software to capture 122,186 tweets geotagged within the city that also had words pertaining to the New Bedford area. Hollander said anyone can get API information from Twitter to also mine data from an area as small as a neighborhood containing a couple hundred houses.
Researchers used IBM’s SPSS Modeler software, comparing this to custom-designed software, to leverage a sentiment dictionary of nearly 3,000 words, assigning a sentiment score to each phrase — ranging from -5 for awful feelings to +5 for feelings of elation. The lab did this for the Twitter messages, and found that about 7 percent were positive versus 5.5 percent negative, and correspondingly in the minutes, 1.7 percent were positive and .7 percent negative. In total, about 11,000 messages contained sentiments.
The lab also used NVivo qualitative software to analyze 24 key words in a one-year sample of the city’s meeting minutes. By searching for the same words in Twitter posts, the researchers found that “school,” “health,” “safety,” “parks,” “field” and “children” were used frequently across both mediums.
….
Next up for the lab is a new study contrasting Twitter posts from four Massachusetts cities with the recent election results.

Digital Sociology

Curated on Posted on by Stefaan Verhulst

New book by Deborah Lupton: “We now live in a digital society. New digital technologies have had a profound influence on everyday life, social relations, government, commerce, the economy and the production and dissemination of knowledge. People’s movements in space, their purchasing habits and their online communication with others are now monitored in detail by digital technologies. We are increasingly becoming digital data subjects, whether we like it or not, and whether we choose this or not.
The sub-discipline of digital sociology provides a means by which the impact, development and use of these technologies and their incorporation into social worlds, social institutions and concepts of selfhood and embodiment may be investigated, analysed and understood. This book introduces a range of interesting social, cultural and political dimensions of digital society and discusses some of the important debates occurring in research and scholarship on these aspects. It covers the new knowledge economy and big data, reconceptualising research in the digital era, the digitisation of higher education, the diversity of digital use, digital politics and citizen digital engagement, the politics of surveillance, privacy issues, the contribution of digital devices to embodiment and concepts of selfhood and many other topics.”

Spain is trialling city monitoring using sound

Curated on Posted on by Stefaan Verhulst

Springwise: “There’s more traffic on today’s city streets than there ever has been, and managing it all can prove to be a headache for local authorities and transport bodies. In the past, we’ve seen the City of Calgary in Canada detect drivers’ Bluetooth signals to develop a map of traffic congestion. Now the EAR-IT project in Santander, Spain, is using acoustic sensors to measure the sounds of city streets and determine real time activity on the ground.
Launched as part of the autonomous community’s SmartSantander initiative, the experimental scheme placed hundreds of acoustic processing units around the region. These pick up the sounds being made in any given area and, when processed through an audio recognition engine, can provide data about what’s going on on the street. Smaller ‘motes’ were also developed to provide more accurate location information about each sound.
Created by members of Portugal’s UNINOVA institute and IT consultants EGlobalMark, the system was able to use city noises to detect things such as traffic congestion, parking availability and the location of emergency vehicles based on their sirens. It could then automatically trigger smart signs to display up-to-date information, for example.
The team particularly focused on a junction near the city hospital that’s a hotspot for motor accidents. Rather than force ambulance drivers to risk passing through a red light and into lateral traffic, the sensors were able to detect when and where an emergency vehicle was coming through and automatically change the lights in their favor.
The system could also be used to pick up ‘sonic events’ such as gunshots or explosions and detect their location. The researchers have also trialled an indoor version that can sense if an elderly resident has fallen over or to turn lights off when the room becomes silent.”

Politics, Policy and Privatisation in the Everyday Experience of Big Data in the NHS

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Chapter by Andrew Goffey ; Lynne Pettinger and Ewen Speed in Martin Hand , Sam Hillyard (ed.) Big Data? Qualitative Approaches to Digital Research (Studies in Qualitative Methodology, Volume 13) : “This chapter explains how fundamental organisational change in the UK National Health Service (NHS) is being effected by new practices of digitised information gathering and use. It analyses the taken-for-granted IT infrastructures that lie behind digitisation and considers the relationship between digitisation and big data.
Design/methodology/approach

Qualitative research methods including discourse analysis, ethnography of software and key informant interviews were used. Actor-network theories, as developed by Science and technology Studies (STS) researchers were used to inform the research questions, data gathering and analysis. The chapter focuses on the aftermath of legislation to change the organisation of the NHS.

Findings

The chapter shows the benefits of qualitative research into specific manifestations information technology. It explains how apparently ‘objective’ and ‘neutral’ quantitative data gathering and analysis is mediated by complex software practices. It considers the political power of claims that data is neutral.

Originality/value

The chapter provides insight into a specific case of healthcare data and. It makes explicit the role of politics and the State in digitisation and shows how STS approaches can be used to understand political and technological practice.”

The collision between big data and privacy law

Curated on Posted on by Stefaan Verhulst
Paper by Stephen Wilson in the Australian Journal of Telecommunications and the Digital Economy : “We live in an age where billionaires are self-made on the back of the most intangible of assets – the information they have about us. The digital economy is awash with data. It’s a new and endlessly re-useable raw material, increasingly left behind by ordinary people going about their lives online. Many information businesses proceed on the basis that raw data is up for grabs; if an entrepreneur is clever enough to find a new vein of it, they can feel entitled to tap it in any way they like. However, some tacit assumptions underpinning today’s digital business models are naive. Conventional data protection laws, older than the Internet, limit how Personal Information is allowed to flow. These laws turn out to be surprisingly powerful in the face of ‘Big Data’ and the ‘Internet of Things’. On the other hand, orthodox privacy management was not framed for new Personal Information being synthesised tomorrow from raw data collected today. This paper seeks to bridge a conceptual gap between data analytics and privacy, and sets out extended Privacy Principles to better deal with Big Data.”

The New Thing in Google Flu Trends Is Traditional Data

Curated on Posted on by Stefaan Verhulst

in the New York Times: “Google is giving its Flu Trends service an overhaul — “a brand new engine,” as it announced in a blog post on Friday.

The new thing is actually traditional data from the Centers for Disease Control and Prevention that is being integrated into the Google flu-tracking model. The goal is greater accuracy after the Google service had been criticized for consistently over-estimating flu outbreaks in recent years.

The main critique came in an analysis done by four quantitative social scientists, published earlier this year in an article in Science magazine, “The Parable of Google Flu: Traps in Big Data Analysis.” The researchers found that the most accurate flu predictor was a data mash-up that combined Google Flu Trends, which monitored flu-related search terms, with the official C.D.C. reports from doctors on influenza-like illness.

The Google Flu Trends team is heeding that advice. In the blog post, written by Christian Stefansen, a Google senior software engineer, wrote, “We’re launching a new Flu Trends model in the United States that — like many of the best performing methods in the literature — takes official CDC flu data into account as the flu season progresses.”

Google’s flu-tracking service has had its ups and downs. Its triumph came in 2009, when it gave an advance signal of the severity of the H1N1 outbreak, two weeks or so ahead of official statistics. In a 2009 article in Nature explaining how Google Flu Trends worked, the company’s researchers did, as the Friday post notes, say that the Google service was not intended to replace official flu surveillance methods and that it was susceptible to “false alerts” — anything that might prompt a surge in flu-related search queries.

Yet those caveats came a couple of pages into the Nature article. And Google Flu Trends became a symbol of the superiority of the new, big data approach — computer algorithms mining data trails for collective intelligence in real time. To enthusiasts, it seemed so superior to the antiquated method of collecting health data that involved doctors talking to patients, inspecting them and filing reports.

But Google’s flu service greatly overestimated the number of cases in the United States in the 2012-13 flu season — a well-known miss — and, according to the research published this year, has persistently overstated flu cases over the years. In the Science article, the social scientists called it “big data hubris.”

Ebola and big data: Call for help

Curated on Posted on by Stefaan Verhulst

The Economist: “WITH at least 4,500 people dead, public-health authorities in west Africa and worldwide are struggling to contain Ebola. Borders have been closed, air passengers screened, schools suspended. But a promising tool for epidemiologists lies unused: mobile-phone data.
When people make mobile-phone calls, the network generates a call data record (CDR) containing such information as the phone numbers of the caller and receiver, the time of the call and the tower that handled it—which gives a rough indication of the device’s location. This information provides researchers with an insight into mobility patterns. Indeed phone companies use these data to decide where to build base stations and thus improve their networks, and city planners use them to identify places to extend public transport.
But perhaps the most exciting use of CDRs is in the field of epidemiology. Until recently the standard way to model the spread of a disease relied on extrapolating trends from census data and surveys. CDRs, by contrast, are empirical, immediate and updated in real time. You do not have to guess where people will flee to or move. Researchers have used them to map malaria outbreaks in Kenya and Namibia and to monitor the public response to government health warnings during Mexico’s swine-flu epidemic in 2009. Models of population movements during a cholera outbreak in Haiti following the earthquake in 2010 used CDRs and provided the best estimates of where aid was most needed.
Doing the same with Ebola would be hard: in west Africa most people do not own a phone. But CDRs are nevertheless better than simulations based on stale, unreliable statistics. If researchers could track population flows from an area where an outbreak had occurred, they could see where it would be likeliest to break out next—and therefore where they should deploy their limited resources. Yet despite months of talks, and the efforts of the mobile-network operators’ trade association and several smaller UN agencies, telecoms firms have not let researchers use the data (see article).
One excuse is privacy, which is certainly a legitimate worry, particularly in countries fresh from civil war, or where tribal tensions exist. But the phone data can be anonymised and aggregated in a way that alleviates these concerns. A bigger problem is institutional inertia. Big data is a new field. The people who grasp the benefits of examining mobile-phone usage tend to be young, and lack the clout to free them for research use.”

From the smart city to the wise city: The role of universities in place-based leadership

Curated on Posted on by Stefaan Verhulst

Paper by Hambleton, R.: “For a variety of reasons the notion of the smart city has grown in popularity and some even claim that all cities now have to be ‘smart’. For example, some digital enthusiasts argue that advances in Information and Communication Technologies (ICT) are ushering in a new era in which pervasive electronic connections will inevitably lead to significant changes that make cities more liveable and more democratic. This paper will cast a critical eye over these claims. It will unpack the smart city rhetoric and show that, in fact, three competing perspectives are struggling for ascendancy within the smart cities discourse: 1) The digital city (emphasising a strong commitment to the use of ICT in governance), 2) The green city (reflecting the growing use of the US phrase smart growth, which is concerned to apply sound urban planning principles), and 3) The learning city (emphasising the way in which cities learn, network and innovate). Five digital danger zones will be identified and discussed. This analysis will suggest that scholars and policy makers who wish to improve the quality of life in cities should focus their attention on wisdom, not smartness. Civic leaders need to exercise judgement based on values if they are to create inclusive, sustainable cities. It is not enough to be clever, quick, ingenious, nor will it help if Big Data is superseded by Even Bigger Data. Universities can play a much more active role in place-based leadership in the cities where they are located. To do this effectively they need to reconsider the nature of modern scholarship. The paper will show how a growing number of universities are doing precisely this. Two respected examples will be presented to show how urban universities, if they are committed to engaged scholarship, can make a significant contribution to the creation of the wise city.”