Science 2.0: “Open Collaboration, defined in a new paper as “any system of innovation or production that relies on goal-oriented yet loosely coordinated participants who interact to create a product (or service) of economic value, which they make available to contributors and non-contributors alike” brought the world Wikipedia, Bitcoin and, yes, even Science 2.0.
But what does that mean, really? That’s the first problem with vague terms in an open environment. It is anything people want it to be and sometimes what people want it to be is money, but hidden behind a guise of public weal.
TED’s lesser cousin TEDx is a result of open collaboration but there is no doubt it has successfully leveraged the marketing of TED to sell seats in auditoriums, just as it was designed to do. Generally, Open Collaboration now is less like its early days, where a group of like-minded people got together to create an Open Source tool, and more like corporations. Only they avoid the label, they are not quite non-profits and not quite corporations.
And because they are neither they can operate free of the cultural stigma. Despite efforts to claim that Wikipedia is a hotbed of misogyny and blocks out minorities, the online encyclopedia has endured just fine. Their defense is a simple one; they have no idea what gender or race or religion anyone is and anyone can contribute – it is a true open collaboration. Open Collaboration is goal-oriented, they lack the infrastructure to obey demands that they become about social justice, so the environments can be less touchy-feely than corporations and avoid the social authoritarianism of academia.
Many open collaborations perform well even in ‘harsh’ environments, where some minorities are underrepresented and diversity is lacking or when products by different groups rival one another. It’s a real puzzle for sociologists. The authors conclude that open collaboration is likely to expand into new domains, displacing traditional organizations, because it is so mission-oriented. Business executives and civic leaders should take heed – the future could look a lot more like the 1940s.”
See also: Sheen S. Levine, Michael J. Prietula, ‘Open Collaboration for Innovation: Principles and Performance’, Organization Science December 30, 2014 DOI:10.1287/orsc.2013.0872
The GovLab Index: Open Data
Please find below the latest installment in The GovLab Index series, inspired by Harper’s Index. “The GovLab Index: Open Data — December 2013” provides an update on our previous Open Data installment, and highlights global trends in Open Data and the release of public sector information. Previous installments include Measuring Impact with Evidence, The Data Universe, Participation and Civic Engagement and Trust in Institutions.
Value and Impact
- Potential global value of open data estimated by McKinsey: $3 trillion annually
- Potential yearly value for the United States: $1.1 trillion
- Europe: $900 billion
- Rest of the world: $1.7 trillion
- How much the value of open data is estimated to grow per year in the European Union: 7% annually
- Value of releasing UK’s geospatial data as open data: 13 million pounds per year by 2016
- Estimated worth of business reuse of public sector data in Denmark in 2010: more than €80 million a year
- Estimated worth of business reuse of public sector data across the European Union in 2010: €27 billion a year
- Total direct and indirect economic gains from easier public sector information re-use across the whole European Union economy, as of May 2013: €140 billion annually
- Economic value of publishing data on adult cardiac surgery in the U.K., as of May 2013: £400 million
- Economic value of time saved for users of live data from the Transport for London apps, as of May 2013: between £15 million and £58 million
- Estimated increase in GDP in England and Wales in 2008-2009 due to the adoption of geospatial information by local public services providers: +£320m
- Average decrease in borrowing costs in sovereign bond markets for emerging market economies when implementing transparent practices (measured by accuracy and frequency according to IMF policies, across 23 countries from 1999-2002): 11%
- Open weather data supports an estimated $1.5 billion in applications in the secondary insurance market – but much greater value comes from accurate weather predictions, which save the U.S. annually more than $30 billion
- Estimated value of GPS data: $90 billion
Efforts and Involvement
- Number of U.S. based companies identified by the GovLab that use government data in innovative ways: 500
- Number of open data initiatives worldwide in 2009: 2
- Number of open data initiatives worldwide in 2013: over 300
- Number of countries with open data portals: more than 40
- Countries who share more information online than the U.S.: 14
- Number of cities globally that participated in 2013 International Open Data Hackathon Day: 102
- Number of U.S. cities with Open Data Sites in 2013: 43
- U.S. states with open data initiatives: 40
- Membership growth in the Open Government Partnership in two years: from 8 to 59 countries
- Number of time series indicators (GDP, foreign direct investment, life expectancy, internet users, etc.) in the World Bank Open Data Catalog: over 8,000
- How many of 77 countries surveyed by the Open Data Barometer have some form of Open Government Data Initiative: over 55%
- How many OGD initiatives have dedicated resources with senior level political backing: over 25%
- How many countries are in the Open Data Index: 70
- How many of the 700 key datasets in the Index are open: 84
- Number of countries in the Open Data Census: 77
- How many of the 727 key datasets in the Census are open: 95
- How many countries surveyed have formal data policies in 2013: 55%
- Those who have machine-readable data available: 25%
- Top 5 countries in Open Data rankings: United Kingdom, United States, Sweden, New Zealand, Norway
- The different levels of Open Data Certificates a data user or publisher can achieve “along the way to world-class open data”: 4 levels, Raw, Pilot, Standard and Expert
- The number of data ecosystems categories identified by the OECD: 3, data producers, infomediaries, and users
Examining Datasets…
FULL VERSION AT http://thegovlab.org/govlab-index-open-data-updated/
Building Creative Commons: The Five Pillars Of Open Source Finance
Brett Scott: “This is an article about Open Source Finance. It’s an idea I first sketched out at a talk I gave at the Open Data Institute in London. By ‘Open Source Finance’, I don’t just mean open source software programmes. Rather, I’m referring to something much deeper and broader. It’s a way of framing an overall change we might want to see in the financial system….
You can thus take on five conceptually separate, but mutualistic roles: Producer, consumer, validator, community member, or (competitive or complementary) breakaway. And these same five elements can underpin a future system of Open Source Finance. I’m framing this as an overall change we might want to see in the financial system, but perhaps we are already seeing it happening. So let’s look briefly at each pillar in turn.
Pillar 1: Access to the means of financial production
Very few of us perceive ourselves as offering financial services when we deposit our money in banks. Mostly we perceive ourselves as passive recipients of services. Put another way, we frequently don’t imagine we have the capability to produce financial services, even though the entire financial system is foundationally constructed from the actions of small-scale players depositing money into banks and funds, buying the products of companies that receive loans, and culturally validating the money system that the banks uphold. Let’s look though, at a few examples of prototypes that are breaking this down:
Pillar 1: Access to the means of financial production
Very few of us perceive ourselves as offering financial services when we deposit our money in banks. Mostly we perceive ourselves as passive recipients of services. Put another way, we frequently don’t imagine we have the capability to produce financial services, even though the entire financial system is foundationally constructed from the actions of small-scale players depositing money into banks and funds, buying the products of companies that receive loans, and culturally validating the money system that the banks uphold. Let’s look though, at a few examples of prototypes that are breaking this down:
- Peer-to-peer finance models: If you decide to lend money to your friend, you directly perceive yourself as offering them a service. P2P finance platforms extend that concept far beyond your circle of close contacts, so that you can directly offer a financial service to someone who needs it. In essence, such platforms offer you access to an active, direct role in producing financial services, rather than an indirect, passive one.
- There are many interesting examples of actual open source financial software aimed at helping to fulfil the overall mission of an open source financial system. Check out Mifos and Cyclos, and Hamlets (developed by Community Forge’s Matthew Slater and others), all of which are designed to help people set up their own financial institutions
- Alternative currencies: There’s a reason why the broader public are suddenly interested in understanding Bitcoin. It’s a currency that people have produced themselves. As a member of the Bitcoin community, I am much more aware of my role in upholding – or producing – the system, than I am when using normal money, which I had no conscious role in producing. The scope toinvent your own currency goes far beyond crypto-currencies though: local currencies, time-banks, and mutual credit systems are emerging all over
- The Open Bank Project is trying to open up banks to third party apps that would allow a depositor to have much greater customisability of their bank account. It’s not aimed at bypassing banks in the way that P2P is, but it’s seeking to create an environment where an ecosystem of alternative systems can plug into the underlying infrastructure provided by banks
Pillar 2: Widespread distribution
Financial intermediaries like banks and funds serve as powerful gatekeepers to access to financing. To some extent this is a valid role – much like a publisher or music label will attempt to only publish books or music that they believe are high quality enough – but on the other hand, this leads to excessive power vested in the intermediaries, and systematic bias in what gets to survive. When combined with a lack of democratic accountability on the part of the intermediaries, you can have whole societies held hostage to the (arbitrary) whims, prejudices and interests of such intermediaries. Expanding access to financial services is thus a big front in the battle for financial democratisation. In addition to more traditional means to buildingfinancial inclusion – such as credit unions and microfinance – here are two areas to look at:
- Crowdfunding: In the dominant financial system, you have to suck up to a single set of gatekeepers to get financing, hoping they won’t exclude you. Crowdfunding though, has expanded access to receiving financial services to a whole host of people who previously wouldn’t have access, such as artists, small-scale filmmakers, activists, and entrepreneurs with no track record. Crowdfunding can serve as a micro redistribution system in society, offering people a direct way to transfer wealth to areas that traditional welfare systems might neglect
- Mobile banking: This is a big area, with important implications for international development and ICT4D. Check out innovations like M-Pesain Kenya, a technology to use mobile phones as proto-bank accounts. This in itself doesn’t necessarily guarantee inclusion, but it expands potential access to the system to people that most banks ignore
Pillar 3: The ability to monitor
Do you know where the money in the big banks goes? No, of course not. They don’t publish it, under the guise of commercial secrecy and confidentiality. It’s like they want to have their cake and eat it: “We’ll act as intermediaries on your behalf, but don’t ever ask for any accountability”. And what about the money in your pension fund? Also very little accountability. The intermediary system is incredibly opaque, but attempts to make it more transparent are emerging. Here are some examples:
- Triodos Bank and Charity Bank are examples of banks that publish exactly what projects they lend to. This gives you the ability to hold them to account in a way that no other bank will allow you to do
- Corporations are vehicles for extracting value out of assets and then distributing that value via financial instruments to shareholders and creditors. Corporate structures though, including those used by banks themselves, have reached a level of complexity approaching pure obsfucation. There can be no democratic accountability when you can’t even see who owns what, and how the money flows. Groups likeOpenCorporates and Open Oil though, are offering new open data tools to shine a light on the shadowy world of tax havens, ownership structures and contracts
- Embedded in peer-to-peer models is a new model of accountability too. When people are treated as mere account numbers with credit scores by banks, the people in return feel little accountability towards the banks. On the other hand, if an individual has directly placed trust in me, I feel much more compelled to respect that
Pillar 4: An ethos of non-prescriptive DIY collaboration
At the heart of open source movements is a deep DIY ethos. This is in part about the sheer joy of producing things, but also about asserting individual power over institutionalised arrangements and pre-established officialdom. Alongside this, and deeply tied to the DIY ethos, is the search to remove individual alienation: You are not a cog in a wheel, producing stuff you don’t have a stake in, in order to consume stuff that you don’t know the origins of. Unalienated labour includes the right to produce where you feel most capable or excited.
This ethos of individual responsibility and creativity stands in contrast to the traditional passive frame of finance that is frequently found on both the Right and Left of the political spectrum. Indeed, the debates around ‘socially useful finance’ are seldom about reducing the alienation of people from their financial lives. They’re mostly about turning the existing financial sector into a slightly more benign dictatorship. The essence of DIY though, is to band together, not via the enforced hierarchy of the corporation or bureaucracy, but as part of a likeminded community of individuals creatively offering services to each other. So let’s take a look at a few examples of this
- BrewDog’s ‘Equity for Punks‘ share offering is probably only going to attract beer-lovers, but that’s the point – you get together as a group who has a mutual appreciation for a project, and you finance it, and then when you’re drinking the beer you’ll know you helped make it happen in a small way
- Community shares offer local groups the ability to finance projects that are meaningful to them in a local area. Here’s one for a solar co-operative, a pub, and a ferry boat service in Bristol
- We’ve already discussed how crowdfunding platforms open access to finance to people excluded from it, but they do this by offering would-be crowdfunders the chance to support things that excite them. I don’t have much cash, so I’m not in a position to actively finance people, but in my Indiegogo profile you can see I make an effort helping to publicise campaigns that I want to receive financing
Pillar 5: The right to fork
The right to dissent is a crucial component of a democratic society. But for dissent to be effective, it has to be informed and constructive, rather than reactive and regressive. There is much dissent towards the current financial system, but while people are free to voice their displeasure, they find it very difficult to actually act on their displeasure. We may loathe the smug banking oligopoly, but we’re frequently compelled to use them.
Furthermore, much dissent doesn’t have a clear vision of what alternative is sought. This is partially due to the fact that access to financial ‘source code’ is so limited. It’s hard to articulate ideas about what’s wrong when one cannot articulate how the current system operates. Most financial knowledge is held in proprietary formulations and obscure jargon-laden language within the financial sector, and this needs to change. It’s for this reason that I’m building the London School of Financial Activism, so ordinary people can explore the layers of financial code, from the deepest layer – the money itself – and then on to the institutions, instruments and networks that move it around….”
6 New Year’s Strategies for Open Data Entrepreneurs
The GovLab’s Senior Advisor Joel Gurin: “Open Data has fueled a wide range of startups, including consumer-focused websites, business-to-business services, data-management tech firms, and more. Many of the companies in the Open Data 500 study are new ones like these. New Year’s is a classic time to start new ventures, and with 2014 looking like a hot year for Open Data, we can expect more startups using this abundant, free resource. For my new book, Open Data Now, I interviewed dozens of entrepreneurs and distilled six of the basic strategies that they’ve used.
1. Learn how to add value to free Open Data. We’re seeing an inversion of the value proposition for data. It used to be that whoever owned the data—particularly Big Data—had greater opportunities than those who didn’t. While this is still true in many areas, it’s also clear that successful businesses can be built on free Open Data that anyone can use. The value isn’t in the data itself but rather in the analytical tools, expertise, and interpretation that’s brought to bear. One oft-cited example: The Climate Corporation, which built a billion-dollar business out of government weather and satellite data that’s freely available for use.
2. Focus on big opportunities: health, finance, energy, education. A business can be built on just about any kind of Open Data. But the greatest number of startup opportunities will likely be in the four big areas where the federal government is focused on Open Data release. Last June’s Health Datapalooza showcased the opportunities in health. Companies like Opower in energy, GreatSchools in education, and Calcbench, SigFig, and Capital Cube in finance are examples in these other major sectors.
3. Explore choice engines and Smart Disclosure apps. Smart Disclosure – releasing data that consumers can use to make marketplace choices – is a powerful tool that can be the basis for a new sector of online startups. No one, it seems, has quite figured out how to make this form of Open Data work best, although sites like CompareTheMarket in the UK may be possible models. Business opportunities await anyone who can find ways to provide these much-needed consumer services. One example: Kayak, which competed in the crowded travel field by providing a great consumer interface, and which was sold to Priceline for $1.8 billion last year.
4. Help consumers tap the value of personal data. In a privacy-conscious society, more people will be interested in controlling their personal data and sharing it selectively for their own benefit. The value of personal data is just being recognized, and opportunities remain to be developed. There are business opportunities in setting up and providing “personal data vaults” and more opportunity in applying the many ways they can be used. Personal and Reputation.com are two leaders in this field.
5. Provide new data solutions to governments at all levels. Government datasets at the federal, state, and local level can be notoriously difficult to use. The good news is that these governments are now realizing that they need help. Data management for government is a growing industry, as Socrata, OpenGov, 3RoundStones, and others are finding, while companies like Enigma.io are turning government data into a more usable resource.
6. Look for unusual Open Data opportunities. Building a successful business by gathering data on restaurant menus and recipes is not an obvious route to success. But it’s working for Food Genius, whose founders showed a kind of genius in tapping an opportunity others had missed. While the big areas for Open Data are becoming clear, there are countless opportunities to build more niche businesses that can still be highly successful. If you have expertise in an area and see a customer need, there’s an increasingly good chance that the Open Data to help meet that need is somewhere to be found.”
Open Data in Action
Nick Sinai at the White House: “Over the past few years, the Administration has launched a series of Open Data Initiatives, which, have released troves of valuable data in areas such as health, energy, education, public safety, finance, and global development…
Today, in furtherance of this exciting economic dynamic, The Governance Lab (The GovLab) —a research institution at New York University—released the beta version of its Open Data 500 project—an initiative designed to identify, describe, and analyze companies that use open government data in order to study how these data can serve business needs more effectively. As part of this effort, the organization is compiling a list of 500+ companies that use open government data to generate new business and develop new products and services.
This working list of 500+ companies, from sectors ranging from real estate to agriculture to legal services, shines a spotlight on surprising array of innovative and creative ways that open government data is being used to grow the economy – across different company sizes, different geographies, and different industries. The project includes information about the companies and what government datasets they have identified as critical resources for their business.
Some of examples from the Open Data 500 Project include:
- Brightscope, a San Diego-based company that leverages data from the Department of Labor, the Security and Exchange Commission, and the Census Bureau to rate consumers’ 401k plans objectively on performance and fees, so companies can choose better plans and employees can make better decisions about their retirement options.
- AllTuition, a Chicago-based startup that provides services—powered by data from Department of Education on Federal student financial aid programs and student loans— to help students and parents manage the financial-aid process for college, in part by helping families keep track of deadlines, and walking them through the required forms.
- Archimedes, a San Francisco healthcare modeling and analytics company, that leverages Federal open data from the National Institutes of Health, the Centers for Disease Control and Prevention, and the Center for Medicaid and Medicare Services, to provide doctors more effective individualized treatment plans and to enable patients to make informed health decisions.
See also:
Open Government Data: Companies Cash In
Open data and transparency: a look back at 2013
Web-based technology continued to offer increasing numbers of people the ability to share standardised data and statistics to demand better governance and strengthen accountability. 2013 seemed to herald the moment that the open data/transparency movement entered the mainstream.
Yet for those who have long campaigned on the issue, the call was more than just a catchphrase, it was a unique opportunity. “If we do get a global drive towards open data in relation to development or anything else, that would be really transformative and it’s quite rare to see such bold statements at such an early stage of the process. I think it set the tone for a year in which transparency was front and centre of many people’s agendas,” says David Hall Matthews, of Publish What You Fund.
This year saw high level discussions translated into commitments at the policy level. David Cameron used the UK’s presidency of the G8 to trigger international action on the three Ts (tax, trade and transparency) through the IF campaign. The pledge at Lough Erne, in Scotland, reaffirmed the commitment to the Busan open data standard as well as the specific undertaking that all G8 members would implement International Aid Transparency Index (IATI) standards by the end of 2015.
2013 was a particularly good year for the US Millenium Challenge Corporation (MCC) which topped the aid transparency index. While at the very top MCC and UK’s DfID were examples of best practice, there was still much room for improvement. “There is a really long tail of agencies who are not really taking transparency at all, yet. This includes important donors, the whole of France and the whole of Japan who are not doing anything credible,” says Hall-Matthews.
Yet given the increasing number of emerging and ‘frontier‘ markets whose growth is driven in large part by wealth derived from natural resources, 2013 saw a growing sense of urgency for transparency to be applied to revenues from oil, gas and mineral resources that may far outstrip aid. In May, the new Extractive Industries Transparency Initiative standard (EITI) was adopted, which is said to be far broader and deeper than its previous incarnation.
Several countries have done much to ensure that transparency leads to accountability in their extractive industries. In Nigeria, for example, EITI reports are playing an important role in the debate about how resources should be managed in the country. “In countries such as Nigeria they’re taking their commitment to transparency and EITI seriously, and are going beyond disclosing information but also ensuring that those findings are acted upon and lead to accountability. For example, the tax collection agency has started to collect more of the revenues that were previously missing,” says Jonas Moberg, head of the EITI International Secretariat.
But just the extent to which transparency and open data can actually deliver on its revolutionary potential has also been called into question. Governments and donors agencies can release data but if the power structures within which this data is consumed and acted upon do not shift is there really any chance of significant social change?
The complexity of the challenge is illustrated by the case of Mexico which, in 2014, will succeed Indonesia as chair of the Open Government Partnership. At this year’s London summit, Mexico’s acting civil service minister, spoke of the great strides his country has made in opening up the public procurement process, which accounts for around 10% of GDP and is a key area in which transparency and accountability can help tackle corruption.
There is, however, a certain paradox. As SOAS professor, Leandro Vergara Camus, who has written extensively on peasant movements in Mexico, explains: “The NGO sector in Mexico has more of a positive view of these kinds of processes than the working class or peasant organisations. The process of transparency and accountability have gone further in urban areas then they have in rural areas.”…
With increasing numbers of organisations likely to jump on the transparency bandwagon in the coming year the greatest challenge is using it effectively and adequately addressing the underlying issues of power and politics.
Top 2013 transparency publications
Open data, transparency and international development, The North South Institute
Data for development: The new conflict resource?, Privacy International
The fix-rate: a key metric for transparency and accountability, Integrity Action
Making UK aid more open and transparent, DfID
Getting a seat at the table: Civil Society advocacy for budget transparency in “untransparent” countries, International Budget Partnership
The dates that mattered
23-24 May: New Extractive Industries Transparency Index standard adopted
30 May: Post 2015 high level report calling for a ‘data revolution’ is published
17-18 June: UK premier, David Cameron, campaigns for tax, trade and transparency during the G8
24 October: US Millenium Challenge Corporation tops the aid transparency index”
30 October – 1 November: Open Government Partnership in London gathers civil society, governments and data experts
Are Smart Cities Empty Hype?
Irving Wladawsky-Berger in the Wall Street Journal: “A couple of weeks ago I participated in an online debate sponsored by The Economist around the question: Are Smart Cities Empty Hype? Defending the motion was Anthony Townsend, research director at the Institute for the Future and adjunct faculty member at NYU’s Wagner School of Public Service. I took the opposite side, arguing the case against the motion.
The debate consisted of three phases spread out over roughly 10 days. We each first stated our respective positions in our opening statements, followed a few days later by our rebuttals, and then finally our closing statements. It was moderated by Ludwig Siegele, online business and finance editor at The Economist. Throughout the process, people were invited to vote on the motion, as well as to post their own comments.
The debate was inspired, I believe, by The Multiplexed Metropolis, an article Mr. Siegele published in the September 7 issue of The Economist which explored the impact of Big Data on cities. He wrote that the vast amounts of data generated by the many social interactions taking place in cities might lead to a kind of second electrification, transforming 21st century cities much as electricity did in the past. “Enthusiasts think that data services can change cities in this century as much as electricity did in the last one,” he noted. “They are a long way from proving their case.”
In my opening statement, I said that I strongly believe that digital technologies and the many data services they are enabling will make cities smarter and help transform them over time. My position is not surprising, given my affiliations with NYU’s Center for Urban Science and Progress (CUSP) and Imperial College’s Digital City Exchange, as well as my past involvements with IBM’s Smarter Cities and with Citigroup’s Citi for Cities initiatives. But, I totally understand why so many– almost half of those voting and quite a few who left comments–feel that smart cities are mostly hype. The case for smart cities is indeed far from proven.
Cities are the most complex social organisms created by humans. Just about every aspect of human endeavor is part of the mix of cities, and they all interact with each other leading to a highly dynamic system of systems. Moreover, each city has its own unique style and character. As is generally the case with transformative changes to highly complex systems, the evolution toward smart cities will likely take quite a bit longer than we anticipate, but the eventual impact will probably be more transformative than we can currently envision.
Electrification, for example, started in the U.S., Britain and other advanced nations around the 1880s and took decades to deploy and truly transform cities. The hype around smart cities that I worry the most about is underestimating their complexity and the amount of research, experimentation, and plain hard work that it will take to realize the promise. Smart cities projects are still in their very early stages. Some will work and some will fail. We have much to learn. Highly complex systems need time to evolve.
Commenting on the opening statements, Mr. Siegele noted: “Despite the motion being Are smart cities empty hype?, both sides have focused on whether these should be implemented top-down or bottom-up. Most will probably agree that digital technology can make cities smarter–meaning more liveable, more efficient, more sustainable and perhaps even more democratic. But the big question is how to get there and how smart cities will be governed.”…
Selected Readings on Data Visualization
The Living Library’s Selected Readings series seeks to build a knowledge base on innovative approaches for improving the effectiveness and legitimacy of governance. This curated and annotated collection of recommended works on the topic of data visualization was originally published in 2013.
Data visualization is a response to the ever-increasing amount of information in the world. With big data, informatics and predictive analytics, we have an unprecedented opportunity to revolutionize policy-making. Yet data by itself can be overwhelming. New tools and techniques for visualizing information can help policymakers clearly articulate insights drawn from data. Moreover, the rise of open data is enabling those outside of government to create informative and visually arresting representations of public information that can be used to support decision-making by those inside or outside governing institutions.
Selected Reading List (in alphabetical order)
- D.J. Duke, K.W. Brodlie, D.A. Duce and I. Herman — Do You See What I Mean? [Data Visualization] — a paper arguing for a systematic ontology for data visualization.
- Michael Friendly — A Brief History of Data Visualization – a brief overview of the history of data visualization that traces the path from early cartography and statistical graphics to modern visualization practices.
- Alvaro Graves and James Hendler — Visualization Tools for Open Government Data — a paper arguing for wider use of visualization tools to open government data achieve its full potential for impact.
- César A. Hidalgo — Graphical Statistical Methods for the Representation of the Human Development Index and Its Components — an argument for visualizing complex data to aid in human development initiatives.
- Genie Stowers — The Use of Data Visualization in Government — a report aimed at helping public sector managers make the most of data visualization tools and practices.
Annotated Selected Reading List (in alphabetical order)
Duke, D.J., K.W. Brodlie, D.A. Duce and I. Herman. “Do You See What I Mean? [Data Visualization].” IEEE Computer Graphics and Applications 25, no. 3 (2005): 6–9. http://bit.ly/1aeU6yA.
- In this paper, the authors argue that a more systematic ontology for data visualization to ensure the successful communication of meaning. “Visualization begins when someone has data that they wish to explore and interpret; the data are encoded as input to a visualization system, which may in its turn interact with other systems to produce a representation. This is communicated back to the user(s), who have to assess this against their goals and knowledge, possibly leading to further cycles of activity. Each phase of this process involves communication between two parties. For this to succeed, those parties must share a common language with an agreed meaning.”
- That authors “believe that now is the right time to consider an ontology for visualization,” and “as visualization move from just a private enterprise involving data and tools owned by a research team into a public activity using shared data repositories, computational grids, and distributed collaboration…[m]eaning becomes a shared responsibility and resource. Through the Semantic Web, there is both the means and motivation to develop a shared picture of what we see when we turn and look within our own field.”
Friendly, Michael. “A Brief History of Data Visualization.” In Handbook of Data Visualization, 15–56. Springer Handbooks Comp.Statistics. Springer Berlin Heidelberg, 2008. http://bit.ly/17fM1e9.
- In this paper, Friendly explores the “deep roots” of modern data visualization. “These roots reach into the histories of the earliest map making and visual depiction, and later into thematic cartography, statistics and statistical graphics, medicine and other fields. Along the way, developments in technologies (printing, reproduction), mathematical theory and practice, and empirical observation and recording enabled the wider use of graphics and new advances in form and content.”
- Just as the general the visualization of data is far from a new practice, Friendly shows that the graphical representation of government information has a similarly long history. “The collection, organization and dissemination of official government statistics on population, trade and commerce, social, moral and political issues became widespread in most of the countries of Europe from about 1825 to 1870. Reports containing data graphics were published with some regularity in France, Germany, Hungary and Finland, and with tabular displays in Sweden, Holland, Italy and elsewhere.”
Graves, Alvaro and James Hendler. “Visualization Tools for Open Government Data.” In Proceedings of the 14th Annual International Conference on Digital Government Research, 136–145. Dg.o ’13. New York, NY, USA: ACM, 2013. http://bit.ly/1eNSoXQ.
- In this paper, the authors argue that, “there is a gap between current Open Data initiatives and an important part of the stakeholders of the Open Government Data Ecosystem.” As it stands, “there is an important portion of the population who could benefit from the use of OGD but who cannot do so because they cannot perform the essential operations needed to collect, process, merge, and make sense of the data. The reasons behind these problems are multiple, the most critical one being a fundamental lack of expertise and technical knowledge. We propose the use of visualizations to alleviate this situation. Visualizations provide a simple mechanism to understand and communicate large amounts of data.”
- The authors also describe a prototype of a tool to create visualizations based on OGD with the following capabilities:
- Facilitate visualization creation
- Exploratory mechanisms
- Viralization and sharing
- Repurpose of visualizations
Hidalgo, César A. “Graphical Statistical Methods for the Representation of the Human Development Index and Its Components.” United Nations Development Programme Human Development Reports, September 2010. http://bit.ly/166TKur.
- In this paper for the United Nations Human Development Programme, Hidalgo argues that “graphical statistical methods could be used to help communicate complex data and concepts through universal cognitive channels that are heretofore underused in the development literature.”
- To support his argument, representations are provided that “show how graphical methods can be used to (i) compare changes in the level of development experienced by countries (ii) make it easier to understand how these changes are tied to each one of the components of the Human Development Index (iii) understand the evolution of the distribution of countries according to HDI and its components and (iv) teach and create awareness about human development by using iconographic representations that can be used to graphically narrate the story of countries and regions.”
Stowers, Genie. “The Use of Data Visualization in Government.” IBM Center for The Business of Government, Using Technology Series, 2013. http://bit.ly/1aame9K.
- This report seeks “to help public sector managers understand one of the more important areas of data analysis today — data visualization. Data visualizations are more sophisticated, fuller graphic designs than the traditional spreadsheet charts, usually with more than two variables and, typically, incorporating interactive features.”
- Stowers also offers numerous examples of “visualizations that include geographical and health data, or population and time data, or financial data represented in both absolute and relative terms — and each communicates more than simply the data that underpin it. In addition to these many examples of visualizations, the report discusses the history of this technique, and describes tools that can be used to create visualizations from many different kinds of data sets.”
Ten thoughts for the future
The Economist: “CASSANDRA has decided to revisit her fellow forecasters Thomas Malnight and Tracey Keys to find out what their predictions are for 2014. Once again they have produced a collection of trends for the year ahead, in their “Global Trends Report”.
The possibilities of mind control seem alarming ( point 6) as do the implications of growing income inequality (point 10). Cassandra also hopes that “unemployability” and “unemployerability”, as discussed in point 9, are contested next year (on both linguistic and social fronts).
Nevertheless, the forecasts make for intriguing reading and highlights appear below.
1. From social everything to being smart socially
Social technologies are everywhere, but these vast repositories of digital “stuff” bury the exceptional among the unimportant. It’s time to get socially smart. Users are moving to niche networks to bring back the community feel and intelligence to social interactions. Businesses need to get smarter about extracting and delivering value from big data including challenging business models. For social networks, mobile is the great leveller. Competition for attention with other apps will intensify the battle to own key assets from identity to news sharing, demanding radical reinvention.
2. Information security: The genie is out of the bottle
Thought your information was safe? Think again. The information security genie is out of the bottle as cyber-surveillance and data mining by public and private organizations increases – and don’t forget criminal networks and whistleblowers. It will be increasingly hard to tell friend from foe in cyberspace as networks build artificial intelligence to decipher your emotions and smart cities track your every move. Big brother is here: Protecting identity, information and societies will be a priority for all.
3. Who needs shops anyway?
Retailers are facing a digitally driven perfect storm. Connectivity, rising consumer influence, time scarcity, mobile payments, and the internet of things, are changing where, when and how we shop – if smart machines have not already done the job. Add the sharing economy, driven by younger generations where experience and sustainable consumption are more important than ownership, and traditional retail models break down. The future of shops will be increasingly defined by experiential spaces offering personalized service, integrated online and offline value propositions, and pop-up stores to satisfy demands for immediacy and surprise.
4. Redistributing the industrial revolution
Complex, global value chains are being redistributed by new technologies, labour market shifts and connectivity. Small-scale manufacturing, including 3D and soon 4D printing, and shifting production economics are moving production closer to markets and enabling mass customization – not just by companies but by the tech-enabled maker movement which is going mainstream. Rising labour costs in developing markets, high unemployment in developed markets, global access to online talent and knowledge, plus advances in robotics mean reshoring of production to developed markets will increase. Mobility, flexibility and networks will define the future industrial landscape.
5. Hubonomics: The new face of globalization
As production and consumption become more distributed, hubs will characterize the next wave of “globalization.” They will specialize to support the needs of growing regional trade, emerging city states, on-line communities of choice, and the next generation of flexible workers and entrepreneurs. Underpinning these hubs will be global knowledge networks and new business and governance models based on hubonomics™, that leverage global assets and hub strengths to deliver local value.
6. Sci-Fi is here: Making the impossible possible
Cross-disciplinary approaches and visionary entrepreneurs are driving scientific breakthroughs that could change not just our lives and work but our bodies and intelligence. Labs worldwide are opening up the vast possibilities of mind control and artificial intelligence, shape-shifting materials and self-organizing nanobots, cyborgs and enhanced humans, space exploration, and high-speed, intelligent transportation. Expect great debate around the ethics, financing, and distribution of public and private benefits of these advances – and the challenge of translating breakthroughs into replicable benefits.
7. Growing pains: Transforming markets and generations
The BRICS are succumbing to Newton’s law of gravitation: Brazil’s lost it, India’s losing it, China’s paying the price for growth, Russia’s failing to make a superpower come-back, and South Africa’s economy is in disarray. In other developing markets currencies have tumbled, Arab Spring governments are still in turmoil and social unrest is increasing along with the number of failing states. But the BRICS & Beyond growth engine is far from dead. Rather it is experiencing growing pains which demand significant shifts in governance, financial systems, education and economic policies to catch up. The likely transformers will be younger generations who aspire to greater freedom and quality of life than their parents.
8. Panic versus denial: The resource gap grows, the global risks rise – but who is listening?
The complex nexus of food, water, energy and climate change presents huge global economic, environmental and societal challenges – heating up the battle to access new resources from the Arctic to fracking. Risks are growing, even as multilateral action stalls. It’s a crisis of morals, governance, and above all marketing and media, pitting crisis deniers against those who recognize the threats but are communicating panic versus reasoned solutions. Expect more debate and calls for responsible capitalism – those that are listening will be taking action at multiple levels in society and business.
9. Fighting unemployability and unemployerability
Companies are desperate for talented workers – yet unemployment rates remain high. Polarization towards higher and lower skill levels is squeezing mid-level jobs, even as employers complain that education systems are not preparing students for the jobs of the future. Fighting unemployability is driving new government-business partnerships worldwide, and will remain a critical issue given massive youth unemployment. Employers must also focus on organizational unemployerability – not being able to attract and retain desired talent – as new generations demand exciting and meaningful work where they can make an impact. If they can’t find it, they will quickly move on or swell the growing ranks of young entrepreneurs.
10. Surviving in a bipolar world: From expecting consistency to embracing ambiguity
Life is not fair, nor is it predictable. Income inequality is growing. Intolerance and nationalism are rising but interdependence is the currency of a connected world. Pressure on leaders to deliver results today is intense but so too is the need for fundamental change to succeed in the long term. The contradictions of leadership and life are increasing faster than our ability to reconcile the often polarized perspectives and values each embodies. Increasingly, they are driving irrational acts of leadership (think the US debt ceiling), geopolitical, social and religious tensions, and individual acts of violence. Surviving in this world will demand stronger, responsible leadership comfortable with and capable of embracing ambiguity and uncertainty, as opposed to expecting consistency and predictability.”
Digital Passivity
Jaron Lanier in the New York Times: “I fear that 2013 will be remembered as a tragic and dark year in the digital universe, despite the fact that a lot of wonderful advances took place.
It was the year in which tablets became ubiquitous and advanced gadgets like 3-D printers and wearable interfaces emerged as pop phenomena; all great fun. Our gadgets have widened access to our world. We now regularly communicate with people we would not have been aware of before the networked age. We can find information about almost anything, any time.
But 2013 was also the year in which we became aware of the corner we’ve backed ourselves into. We learned — through the leaks of Edward J. Snowden, the former U.S. National Security Agency contractor, and the work of investigative journalists — how much our gadgets and our digital networks are being used to spy on us by ultra-powerful, remote organizations. We are being dissected more than we dissect.
I wish I could separate the two big trends of the year in computing — the cool gadgets and the revelations of digital spying — but I cannot.
Back at the dawn of personal computing, the idealistic notion that drove most of us was that computers were tools for leveraging human intelligence to ever-greater achievement and fulfillment. This was the idea that burned in the hearts of pioneers like Alan Kay, who a half-century ago was already drawing illustrations of how children would someday use tablets.
But tablets do something unforeseen: They enforce a new power structure. Unlike a personal computer, a tablet runs only programs and applications approved by a central commercial authority. You control the data you enter into a PC, while data entered into a tablet is often managed by someone else.
Steve Jobs, who oversaw the introduction of the spectacularly successful iPad at Apple, declared that personal computers were now ‘‘trucks’’ — tools for working-class guys in T-shirts and visors, but not for upwardly mobile cool people. The implication was that upscale consumers would prefer status and leisure to influence or self-determination.
I am not sure who is to blame for our digital passivity. Did we give up on ourselves too easily?
This would be bleak enough even without the concurrent rise of the surveillance economy. Not only have consumers prioritized flash and laziness over empowerment; we have also acquiesced to being spied on all the time.
The two trends are actually one. The only way to persuade people to voluntarily accept the loss of freedom is by making it look like a great bargain at first.
Consumers were offered free stuff (like search and social networking) in exchange for agreeing to be watched. Vast fortunes can be made by those who best use the personal data you voluntarily hand them. Instagram, introduced in 2010, had only 13 employees and no business plan when it was bought by Facebook less than two years later for $1 billion.
One can argue that network technology enhances democracy because it makes it possible, for example, to tweet your protests. But complaining is not yet success. Social media didn’t create jobs for young people in Cairo during the Arab Spring…”