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


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

Smart cities: the state-of-the-art and governance challenge


New Paper by Mark Deakin in Triple Helix – A Journal of University-Industry-Government Innovation and Entrepreneurship: “Reflecting on the governance of smart cities, the state-of-the-art this paper advances offers a critique of recent city ranking and future Internet accounts of their development. Armed with these critical insights, it goes on to explain smart cities in terms of the social networks, cultural attributes and environmental capacities, vis-a-vis, vital ecologies of the intellectual capital, wealth creation and standards of participatory governance regulating their development. The Triple Helix model which the paper advances to explain these performances in turn suggests that cities are smart when the ICTs of future Internet developments successfully embed the networks society needs for them to not only generate intellectual capital, or create wealth, but also cultivate the environmental capacity, ecology and vitality of those spaces which the direct democracy of their participatory governance open up, add value to and construct.”

Crowdsourcing and Humanitarian Action: Analysis of the Literature


Patrick Meier:  “Raphael Hörler from Zurich’s ETH University has just completed his thesis on the role of crowdsourcing in humanitarian action. His valuable research offers one of the most up-to-date and comprehensive reviews of the principal players and humanitarian technologies in action today. In short, I highly recommend this important resource. Raphael’s full thesis is available here (PDF).”

Challenging Critics of Transparency in Government


at Brookings’s FIXGOV: “Brookings today published my paper, “Why Critics of Transparency Are Wrong.” It describes and subsequently challenges a school of thinkers who in various ways object to government openness and transparency. They include some very distinguished scholars and practitioners from Francis Fukuyama to Brookings’ own Jonathan Rauch. My co-authors, Gary Bass and Danielle Brian, and I explain why they get it wrong—government needs more transparency, not less.

“Critics like these assert that transparency results in government indecision, poor performance, and stalemate. Their arguments are striking because they attack a widely-cherished value, openness, attempting to connect it to an unrelated malady, gridlock. But when you hold the ‘transparency is the problem’ hypothesis up to the sunlight, its gaping holes quickly become visible.”

There is no doubt that gridlock, government dysfunction, polarization and other suboptimal aspects of the current policy environment are frustrating. However, proposed solutions must factor in both the benefits and the expected negative consequences of such changes. Less openness and transparency may ameliorate some current challenges while returning the American political system to a pre-progressive reform era in which corruption precipitated serious social and political costs.

“Simply put, information is power, and keeping information secret only serves to keep power in the hands of a few. This is a key reason the latest group of transparency critics should not be shrugged off: if left unaddressed, their arguments will give those who want to operate in the shadows new excuses.”

It is difficult to imagine a context in which honest graft is not paired with dishonest graft. It is even harder to foresee a government that is effective at distinguishing between the two and rooting out the latter.

“Rather than demonizing transparency for today’s problems, we should look to factors such as political parties and congressional leadership, partisan groups, and social (and mainstream) media, all of which thrive on the gridlock and dysfunction in Washington.”….

Click to read “Why Critics of Transparency Are Wrong.”

Look to Government—Yes, Government—for New Social Innovations


Paper by Christian Bason and Philip Colligan: “If asked to identify the hotbed of social innovation right now, many people would likely point to the new philanthropy of Silicon Valley or the social entrepreneurship efforts supported by Ashoka, Echoing Green, and Skoll Foundation. Very few people, if any, would mention their state capital or Capitol Hill. While local and national governments may have promulgated some of the greatest advances in human history — from public education to putting a man on the moon — public bureaucracies are more commonly known to stifle innovation.
Yet, around the world, there are local, regional, and national government innovators who are challenging this paradigm. They are pioneering a new form of experimental government — bringing new knowledge and practices to the craft of governing and policy making; drawing on human-centered design, user engagement, open innovation, and cross-sector collaboration; and using data, evidence, and insights in new ways.
Earlier this year, Nesta, the UK’s innovation foundation (which Philip helps run), teamed up with Bloomberg Philanthropies to publish i-teams, the first global review of public innovation teams set up by national and city governments. The study profiled 20 of the most established i-teams from around the world, including:

  • French Experimental Fund for Youth, which has supported more than 554 experimental projects (such as one that reduces school drop-out rates) that have benefited over 480,000 young people;
  • Nesta’s Innovation Lab, which has run 70 open innovation challenges and programs supporting over 750 innovators working in fields as diverse as energy efficiency, healthcare, and digital education;
  • New Orleans’ Innovation and Delivery team, which achieved a 19% reduction in the number of murders in the city in 2013 compared to the previous year.

How are i-teams achieving these results? The most effective ones are explicit about the goal they seek – be it creating a solution to a specific policy challenge, engaging citizenry in behaviors that help the commonweal, or transforming the way government behaves. Importantly, these teams are also able to deploy the right skills, capabilities, and methods for the job.
In addition, ­i-teams have a strong bias toward action. They apply academic research in behavioral economics and psychology to public policy and services, focusing on rapid experimentation and iteration. The approach stands in stark contrast to the normal routines of government.
Take for example, The UK’s Behavioural Insights Team (BIT), often called the Nudge Unit. It sets clear goals, engages the right expertise to prototype means to the end, and tests innovations rapidly in the field, to learn what’s not working and rapidly scales what is.
One of BIT’s most famous projects changed taxpayer behavior. BIT’s team of economists, behavioral psychologists, and seasoned government staffers came up with minor changes to tax letters, sent out by the UK Government, that subtlety introduced positive peer pressure. By simply altering the letters to say that most people in their local area had already paid their taxes, BIT was able to boost repayment rates by around 5%. This trial was part of a range of interventions, which have helped forward over £200 million in additional tax revenue to HM Revenue & Customs, the UK’s tax authority.
The Danish government’s internal i-team, MindLab (which Christian ran for 8 years) has likewise influenced citizen behavior….”

A micro-democratic perspective on crowd-work


New paper by Karin Hansson: “Social media has provided governments with new means to improve efficiency and innovation, by engaging a crowd in the gathering and development of data. These collaborative processes are also described as a way to improve democracy by enabling a more transparent and deliberative democracy where citizens participate more directly in decision processes on different levels. However, the dominant research on the e-democratic field takes a government perspective rather then a citizen perspective. –democracy from the perspective of the individual actor, in a global context, is less developed.
In this paper I therefore develop a model for a democratic process outside the realm of the nation state, in a performative state where inequality is norm and the state is unclear and fluid. In this process e-participation means an ICT supported method to get a diversity of opinions and perspectives rather than one single. This micro perspective on democratic participation online might be useful for development of tools for more democratic online crowds…”

Personalised Health and Care 2020: Using Data and Technology to Transform Outcomes for Patients and Citizens


Report and Framework of Action by the UK National Information Board: “One of the greatest opportunities of the 21st century is the potential to safely harness the power of the technology revolution, which has transformed our society, to meet the challenges of improving health and providing better, safer, sustainable care for all. To date the health and care system has only begun to exploit the potential of using data and technology at a national or local level. Our ambition is for a health and care system that enables people to make healthier choices, to be more resilient, to deal more effectively with illness and disability when it arises, and to have happier, longer lives in old age; a health and care system where technology can help tackle inequalities and improve access to services for the vulnerable.
The purpose of this paper is to consider what progress the health and care system has already made and what can be learnt from other industries and the wider economy…”

The Reliability of Tweets as a Supplementary Method of Seasonal Influenza Surveillance


New Paper by Ming-Hsiang Tsou et al in the Journal of Medical Internet Research: “Existing influenza surveillance in the United States is focused on the collection of data from sentinel physicians and hospitals; however, the compilation and distribution of reports are usually delayed by up to 2 weeks. With the popularity of social media growing, the Internet is a source for syndromic surveillance due to the availability of large amounts of data. In this study, tweets, or posts of 140 characters or less, from the website Twitter were collected and analyzed for their potential as surveillance for seasonal influenza.
Objective: There were three aims: (1) to improve the correlation of tweets to sentinel-provided influenza-like illness (ILI) rates by city through filtering and a machine-learning classifier, (2) to observe correlations of tweets for emergency department ILI rates by city, and (3) to explore correlations for tweets to laboratory-confirmed influenza cases in San Diego.
Methods: Tweets containing the keyword “flu” were collected within a 17-mile radius from 11 US cities selected for population and availability of ILI data. At the end of the collection period, 159,802 tweets were used for correlation analyses with sentinel-provided ILI and emergency department ILI rates as reported by the corresponding city or county health department. Two separate methods were used to observe correlations between tweets and ILI rates: filtering the tweets by type (non-retweets, retweets, tweets with a URL, tweets without a URL), and the use of a machine-learning classifier that determined whether a tweet was “valid”, or from a user who was likely ill with the flu.
Results: Correlations varied by city but general trends were observed. Non-retweets and tweets without a URL had higher and more significant (P<.05) correlations than retweets and tweets with a URL. Correlations of tweets to emergency department ILI rates were higher than the correlations observed for sentinel-provided ILI for most of the cities. The machine-learning classifier yielded the highest correlations for many of the cities when using the sentinel-provided or emergency department ILI as well as the number of laboratory-confirmed influenza cases in San Diego. High correlation values (r=.93) with significance at P<.001 were observed for laboratory-confirmed influenza cases for most categories and tweets determined to be valid by the classifier.
Conclusions: Compared to tweet analyses in the previous influenza season, this study demonstrated increased accuracy in using Twitter as a supplementary surveillance tool for influenza as better filtering and classification methods yielded higher correlations for the 2013-2014 influenza season than those found for tweets in the previous influenza season, where emergency department ILI rates were better correlated to tweets than sentinel-provided ILI rates. Further investigations in the field would require expansion with regard to the location that the tweets are collected from, as well as the availability of more ILI data…”

Off the map


The Economist: “Rich countries are deluged with data; developing ones are suffering from drought…
AFRICA is the continent of missing data. Fewer than half of births are recorded; some countries have not taken a census in several decades. On maps only big cities and main streets are identified; the rest looks as empty as the Sahara. Lack of data afflicts other developing regions, too. The self-built slums that ring many Latin American cities are poorly mapped, and even estimates of their population are vague. Afghanistan is still using census figures from 1979—and that count was cut short after census-takers were killed by mujahideen.
As rich countries collect and analyse data from as many objects and activities as possible—including thermostats, fitness trackers and location-based services such as Foursquare—a data divide has opened up. The lack of reliable data in poor countries thwarts both development and disaster-relief. When Médecins Sans Frontières (MSF), a charity, moved into Liberia to combat Ebola earlier this year, maps of the capital, Monrovia, fell far short of what was needed to provide aid or track the disease’s spread. Major roads were marked, but not minor ones or individual buildings.
Poor data afflict even the highest-profile international development effort: the Millennium Development Goals (MDGs). The targets, which include ending extreme poverty, cutting infant mortality and getting all children into primary school, were set by UN members in 2000, to be achieved by 2015. But, according to a report by an independent UN advisory group published on November 6th, as the deadline approaches, the figures used to track progress are shaky. The availability of data on 55 core indicators for 157 countries has never exceeded 70%, it found (see chart)….
Some of the data gaps are now starting to be filled from non-government sources. A volunteer effort called Humanitarian OpenStreetMap Team (HOT) improves maps with information from locals and hosts “mapathons” to identify objects shown in satellite images. Spurred by pleas from those fighting Ebola, the group has intensified its efforts in Monrovia since August; most of the city’s roads and many buildings have now been filled in (see maps). Identifying individual buildings is essential, since in dense slums without formal roads they are the landmarks by which outbreaks can be tracked and assistance targeted.
On November 7th a group of charities including MSF, Red Cross and HOT unveiled MissingMaps.org, a joint initiative to produce free, detailed maps of cities across the developing world—before humanitarian crises erupt, not during them. The co-ordinated effort is needed, says Ivan Gayton of MSF: aid workers will not use a map with too little detail, and are unlikely, without a reason, to put work into improving a map they do not use. The hope is that the backing of large charities means the locals they work with will help.
In Kenya and Namibia mobile-phone operators have made call-data records available to researchers, who have used them to combat malaria. By comparing users’ movements with data on outbreaks, epidemiologists are better able to predict where the disease might spread. mTrac, a Ugandan programme that replaces paper reports from health workers with texts sent from their mobile phones, has made data on medical cases and supplies more complete and timely. The share of facilities that have run out of malaria treatments has fallen from 80% to 15% since it was introduced.
Private-sector data are also being used to spot trends before official sources become aware of them. Premise, a startup in Silicon Valley that compiles economics data in emerging markets, has found that as the number of cases of Ebola rose in Liberia, the price of staple foods soared: a health crisis risked becoming a hunger crisis. In recent weeks, as the number of new cases fell, prices did, too. The authorities already knew that travel restrictions and closed borders would push up food prices; they now have a way to measure and track price shifts as they happen….”

A New Taxonomy of Smart City Projects


New paper by Guido Perboli et al: “City logistics proposes an integrated vision of freight transportation systems within urban area and it aims at the optimization of them as a whole in terms of efficiency, security, safety, viability and environmental sustainability. Recently, this perspective has been extended by the Smart City concept in order to include other aspects of city management: building, energy, environment, government, living, mobility, education, health and so on. At the best of our knowledge, a classification of Smart City Projects has not been created yet. This paper introduces such a classification, highlighting success factors and analyzing new trends in Smart City.”