Open Innovation, Open Science, Open to the World


Speech by Carlos Moedas, EU Commissioner for Research, Science and Innovation: “On 25 April this year, an earthquake of magnitude 7.3 hit Nepal. To get real-time geographical information, the response teams used an online mapping tool called Open Street Map. Open Street Map has created an entire online map of the world using local knowledge, GPS tracks and donated sources, all provided on a voluntary basis. It is open license for any use.

Open Street Map was created by a 24 year-old computer science student at University College London in 2004, has today 2 million users and has been used for many digital humanitarian and commercial purposes: From the earthquakes in Haiti and Nepal to the Ebola outbreak in West Africa.

This story is one of many that demonstrate that we are moving into a world of open innovation and user innovation. A world where the digital and physical are coming together. A world where new knowledge is created through global collaborations involving thousands of people from across the world and from all walks of life.

Ladies and gentlemen, over the next two days I would like us to chart a new path for European research and innovation policy. A new strategy that is fit for purpose for a world that is open, digital and global. And I would like to set out at the start of this important conference my own ambitions for the coming years….

Open innovation is about involving far more actors in the innovation process, from researchers, to entrepreneurs, to users, to governments and civil society. We need open innovation to capitalise on the results of European research and innovation. This means creating the right ecosystems, increasing investment, and bringing more companies and regions into the knowledge economy. I would like to go further and faster towards open innovation….

I am convinced that excellent science is the foundation of future prosperity, and that openness is the key to excellence. We are often told that it takes many decades for scientific breakthroughs to find commercial application.

Let me tell you a story which shows the opposite. Graphene was first isolated in the laboratory by Profs. Geim and Novoselov at the University of Manchester in 2003 (Nobel Prizes 2010). The development of graphene has since benefitted from major EU support, including ERC grants for Profs. Geim and Novoselov. So I am proud to show you one of the new graphene products that will soon be available on the market.

This light bulb uses the unique thermal dissipation properties of graphene to achieve greater energy efficiencies and a longer lifetime that LED bulbs. It was developed by a spin out company from the University of Manchester, called Graphene Lighting, as is expected to go on sale by the end of the year.

But we must not be complacent. If we look at indicators of the most excellent science, we find that Europe is not top of the rankings in certain areas. Our ultimate goal should always be to promote excellence not only through ERC and Marie Skłodowska-Curie but throughout the entire H2020.

For such an objective we have to move forward on two fronts:

First, we are preparing a call for European Science Cloud Project in order to identify the possibility of creating a cloud for our scientists. We need more open access to research results and the underlying data. Open access publication is already a requirement under Horizon 2020, but we now need to look seriously at open data…

When innovators like LEGO start fusing real bricks with digital magic, when citizens conduct their own R&D through online community projects, when doctors start printing live tissues for patients … Policymakers must follow suit…(More)”

Rethinking Smart Cities From The Ground Up


New report byTom Saunders and Peter Baeck (NESTA): “This report tells the stories of cities around the world – from Beijing to Amsterdam, and from London to Jakarta – that are addressing urban challenges by using digital technologies to engage and enable citizens.

Key findings

  • Many ‘top down’ smart city ideas have failed to deliver on their promise, combining high costs and low returns.
  • ‘Collaborative technologies’ offer cities another way to make smarter use of resources, smarter ways of collecting data and smarter ways to make decisions.
  • Collaborative technologies can also help citizens themselves shape the future of their cities.
  • We have created five recommendations for city government who want to make their cities smarter.

As cities bring people together to live, work and play, they amplify their ability to create wealth and ideas. But scale and density also bring acute challenges: how to move around people and things; how to provide energy; how to keep people safe.

‘Smart cities’ offer sensors, ‘big data’ and advanced computing as answers to these challenges, but they have often faced criticism for being too concerned with hardware rather than with people.

In this report we argue that successful smart cities of the future will combine the best aspects of technology infrastructure while making the most of the growing potential of ‘collaborative technologies’, technologies that enable greater collaboration between urban communities and between citizens and city governments.

How will this work in practice? Drawing on examples from all around the world we investigate four emerging methods which are helping city governments engage and enable citizens: the collaborative economy, crowdsourcing data, collective intelligence and crowdfunding.

Policy recommendations

  1. Set up a civic innovation lab to drive innovation in collaborative technologies.
  2. Use open data and open platforms to mobilise collective knowledge.
  3. Take human behaviour as seriously as technology.
  4. Invest in smart people, not just smart technology.
  5. Spread the potential of collaborative technologies to all parts of society….(More)”

A computational algorithm for fact-checking


Kurzweil News: “Computers can now do fact-checking for any body of knowledge, according to Indiana University network scientists, writing in an open-access paper published June 17 in PLoS ONE.

Using factual information from summary infoboxes from Wikipedia* as a source, they built a “knowledge graph” with 3 million concepts and 23 million links between them. A link between two concepts in the graph can be read as a simple factual statement, such as “Socrates is a person” or “Paris is the capital of France.”

In the first use of this method, IU scientists created a simple computational fact-checker that assigns “truth scores” to statements concerning history, geography and entertainment, as well as random statements drawn from the text of Wikipedia. In multiple experiments, the automated system consistently matched the assessment of human fact-checkers in terms of the humans’ certitude about the accuracy of these statements.

Dealing with misinformation and disinformation

In what the IU scientists describe as an “automatic game of trivia,” the team applied their algorithm to answer simple questions related to geography, history, and entertainment, including statements that matched states or nations with their capitals, presidents with their spouses, and Oscar-winning film directors with the movie for which they won the Best Picture awards. The majority of tests returned highly accurate truth scores.

Lastly, the scientists used the algorithm to fact-check excerpts from the main text of Wikipedia, which were previously labeled by human fact-checkers as true or false, and found a positive correlation between the truth scores produced by the algorithm and the answers provided by the fact-checkers.

Significantly, the IU team found their computational method could even assess the truthfulness of statements about information not directly contained in the infoboxes. For example, the fact that Steve Tesich — the Serbian-American screenwriter of the classic Hoosier film “Breaking Away” — graduated from IU, despite the information not being specifically addressed in the infobox about him.

Using multiple sources to improve accuracy and richness of data

“The measurement of the truthfulness of statements appears to rely strongly on indirect connections, or ‘paths,’ between concepts,” said Giovanni Luca Ciampaglia, a postdoctoral fellow at the Center for Complex Networks and Systems Research in the IU Bloomington School of Informatics and Computing, who led the study….

“These results are encouraging and exciting. We live in an age of information overload, including abundant misinformation, unsubstantiated rumors and conspiracy theories whose volume threatens to overwhelm journalists and the public. Our experiments point to methods to abstract the vital and complex human task of fact-checking into a network analysis problem, which is easy to solve computationally.”

Expanding the knowledge base

Although the experiments were conducted using Wikipedia, the IU team’s method does not assume any particular source of knowledge. The scientists aim to conduct additional experiments using knowledge graphs built from other sources of human knowledge, such as Freebase, the open-knowledge base built by Google, and note that multiple information sources could be used together to account for different belief systems….(More)”

Beating the news’ with EMBERS: Forecasting Civil Unrest using Open Source Indicators


Paper by Naren Ramakrishnan et al: “We describe the design, implementation, and evaluation of EMBERS, an automated, 24×7 continuous system for forecasting civil unrest across 10 countries of Latin America using open source indicators such as tweets, news sources, blogs, economic indicators, and other data sources. Unlike retrospective studies, EMBERS has been making forecasts into the future since Nov 2012 which have been (and continue to be) evaluated by an independent T&E team (MITRE). Of note, EMBERS has successfully forecast the uptick and downtick of incidents during the June 2013 protests in Brazil. We outline the system architecture of EMBERS, individual models that leverage specific data sources, and a fusion and suppression engine that supports trading off specific evaluation criteria. EMBERS also provides an audit trail interface that enables the investigation of why specific predictions were made along with the data utilized for forecasting. Through numerous evaluations, we demonstrate the superiority of EMBERS over baserate methods and its capability to forecast significant societal happenings….(More)”

Civic open data at a crossroads: Dominant models and current challenges


Renee E. Sieber and Peter A. Johnson in Government Information Quarterly: “As open data becomes more widely provided by government, it is important to ask questions about the future possibilities and forms that government open data may take. We present four models of open data as they relate to changing relations between citizens and government. These models include; a status quo ‘data over the wall’ form of government data publishing, a form of ‘code exchange’, with government acting as an open data activist, open data as a civic issue tracker, and participatory open data. These models represent multiple end points that can be currently viewed from the unfolding landscape of government open data. We position open data at a crossroads, with significant concerns of the conflicting motivations driving open data, the shifting role of government as a service provider, and the fragile nature of open data within the government space. We emphasize that the future of open data will be driven by the negotiation of the ethical-economic tension that exists between provisioning governments, citizens, and private sector data users….(More)”

 

The Climatologist’s Almanac


Clara Chaisson at onEarth: “Forget your weather app with its five- or even ten-day forecasts—a supercomputer at NASA has just provided us with high-resolution climate projections through the end of the century. The massive new 11-terabyte data set combines historical daily temperatures and precipitation measurements with climate simulations under two greenhouse gas emissions scenarios. The project spans from 1950 to 2100, but users can easily zero in on daily timescales for their own locales—which is precisely the point.

The projections can be found on Amazon for free for all to see and plan by. The space agency hopes that developing nations and poorer communities that may not have any spare supercomputers lying around will use the info to predict and prepare for climate change. …(More)”

Why open data should be central to Fifa reform


Gavin Starks in The Guardian: “Over the past two weeks, Fifa has faced mounting pressure to radically improve its transparency and governance in the wake of corruption allegations. David Cameron has called for reforms including expanding the use of open data.

Open data is information made available by governments, businesses and other groups for anyone to read, use and share. Data.gov.uk was launched as the home of UK open government data in January 2010 and now has almost 21,000 published datasets, including on government spending.

Allowing citizens to freely access data related to the institutions that govern them is essential to a well-functioning democratic society. It is the first step towards holding leaders to account for failures and wrongdoing.

Fifa has a responsibility for the shared interests of millions of fans around the world. Football’s popularity means that Fifa’s governance has wide-ranging implications for society, too. This is particularly true of decisions about hosting the World Cup, which is often tied to large-scale government investment in infrastructure and even extends to law-making. Brazil spent up to £10bn hosting the 2014 World Cup and had to legalise the sale of beer at matches.

Following Sepp Blatter’s resignation, Fifa will gather its executive committee in July to plan for a presidential election, expected to take place in mid-December. Open data should form the cornerstone of any prospective candidate’s manifesto. It can help Fifa make better spending decisions and ensure partners deliver value for money, restore the trust of the international football community.

Fifa’s lengthy annual financial report gives summaries of financial expenditure,budgeted at £184m for operations and governance alone in 2016, but individual transactions are not published. Publishing spending data incentivises better spending decisions. If all Fifa’s outgoings – which totalled around £3.5bn between 2011 and 2014 – were made open, it would encourage much more efficiency….(more)”

Exploring Open Energy Data in Urban Areas


The Worldbank: “…Energy efficiency – using less energy input to deliver the same level of service – has been described by many as the ‘first fuel’ of our societies. However, lack of adequate data to accurately predict and measure energy efficiency savings, particularly at the city level, has limited the realization of its promise over the past two decades.
Why Open Energy Data?
Open Data can be a powerful tool to reduce information asymmetry in markets, increase transparency and help achieve local economic development goals. Several sectors like transport, public sector management and agriculture have started to benefit from Open Data practices. Energy markets are often characterized by less-than-optimal conditions with high system inefficiencies, misaligned incentives and low levels of transparency. As such, the sector has a lot to potentially gain from embracing Open Data principles.
The United States is a leader in this field with its ‘Energy Data’ initiative. This initiative makes data easy to find, understand and apply, helping to fuel a clean energy economy. For example, the Energy Information Administration’s (EIA) open application programming interface (API) has more than 1.2 million time series of data and is frequently visited by users from the private sector, civil society and media. In addition, the Green Button  initiative is empowering American citizens to have access to their own energy usage data, and OpenEI.org is an Open Energy Information platform to help people find energy information, share their knowledge and connect to other energy stakeholders.
Introducing the Open Energy Data Assessment
To address this data gap in emerging and developing countries, the World Bank is conducting a series of Open Energy Data Assessments in urban areas. The objective is to identify important energy-related data, raise awareness of the benefits of Open Data principles and improve the flow of data between traditional energy stakeholders and others interested in the sector.
The first cities we assessed were Accra, Ghana and Nairobi, Kenya. Both are among the fastest-growing cities in the world, with dynamic entrepreneurial and technology sectors, and both are capitals of countries with an ongoing National Open Data Initiative., The two cities have also been selected to be part of the Negawatt Challenge, a World Bank international competition supporting technology innovation to solve local energy challenges.
The ecosystem approach
The starting point for the exercise was to consider the urban energy sector as an ecosystem, comprised of data suppliers, data users, key datasets, a legal framework, funding mechanisms, and ICT infrastructure. The methodology that we used adapted the established World Bank Open Data Readiness Assessment (ODRA), which highlights valuable connections between data suppliers and data demand.  The assessment showcases how to match pressing urban challenges with the opportunity to release and use data to address them, creating a longer-term commitment to the process. Mobilizing key stakeholders to provide quick, tangible results is also key to this approach….(More) …See also World Bank Open Government Data Toolkit.”

The death of data science – and rise of the citizen scientist


Ben Rossi at Information Age: “The notion of data science was born from the recent idea that if you have enough data, you don’t need much (if any) science to divine the truth and foretell the future – as opposed to the long-established rigours of statistical or actuarial science, which most times require painstaking efforts and substantial time to produce their version of ‘the truth’. …. Rather than embracing this untested and, perhaps, doomed form of science, and aimlessly searching for unicorns (also known as data scientists) to pay vast sums to, many organisations are now embracing the idea of making everyone data and analytics literate.

This leads me to what my column is really meant to focus on: the rise of the citizen scientist. 

The citizen scientist is not a new idea, having seen action in the space and earth sciences world for decades now, and has really come into its own as we enter the age of open data.

Cometh the hour

Given the exponential growth of open data initiatives across the world – the UK remains the leader, but has growing competition from all locations – the need for citizen scientists is now paramount. 

As governments open up vast repositories of new data of every type, the opportunity for these same governments (and commercial interests) to leverage the passion, skills and collective know-how of citizen scientists to help garner deeper insights into the scientific and civic challenges of the day is substantial. 

They can then take this knowledge and the collective energy of the citizen scientist community to develop common solution sets and applications to meet the needs of all their constituencies without expending much in terms of financial resources or suffering substantial development time lags. 

This can be a windfall of benefits for every level or type of government found around the world. The use of citizen scientists to tackle so-called ‘grand challenge’ problems has been a driving force behind many governments’ commitment to and investment in open data to date. 

There are so many challenges in governing today that it would be foolish not to employ these very capable resources to help tackle them. 

The benefits manifested from this approach are substantial and well proven. Many are well articulated in the open data success stories to date. 

Additionally, you only need to attend a local ‘hack fest’ to see how engaged citizen scientists can be of any age, gender and race, and feel the sense of community that these events foster as everyone focuses on the challenges at hand and works diligently to surmount them using very creative approaches. 

As open data becomes pervasive in use and matures in respect to the breadth and richness of the data sets being curated, the benefits returned to both government and its constituents will be manifold. 

The catalyst to realising these benefits and achieving return on investment will be the role of citizen scientists, which are not going to be statisticians, actuaries or so-called data gurus, but ordinary people with a passion for science and learning and a desire to contribute to solving the many grand challenges facing society at large….(More)

In The Information Debate, Openness and Privacy Are The Same Thing


 at TechCrunch: “We’ve been framing the debate between openness and privacy the wrong way.

Rather than positioning privacy and openness as opposing forces, the fact is they’re different sides of the same coin – and equally important. This might seem simple, but it might also be the key to moving things forward around this crucial debate.

Open data advocates often suggest that openness should be the default for all human knowledge. We should share, re-use and compare data freely and in doing so reap the benefits of innovation, cost savings and increased citizen participation — to name a just a few gains.

And although it might sound a little utopian, the promise is being realized in many corners of the world….But as we all know, even if we accept all the possible benefits of open data, concerns about privacy, especially personal information, still exist as a counter weight to the open data evangelists. People worry that the path of openness could lead to an Orwellian world where all our information is shared with everyone, permanently.

There is a way to turn the conversation from the face-value clash between openness and privacy to how they can be complementary forces. Gus Hosein, CEO of Privacy International, has explained that privacy is “the governing framework to control access to, collection and usage of information.” Basically, privacy laws enable knowledge and control of data about citizens and their surroundings.

Even if we accept all the possible benefits of open data, concerns about privacy, especially personal information, still exist as a counter weight to the open data evangelists.

This is strikingly similar to the argument that open data increases service delivery efficiency and personalization. Openness and privacy both share the same impulse: I want to be in control of my life, I want to know and choose whether a hospital or school is a good hospital or school and be in control of my choice of services.

Another strong thread in conversations around open data is that transparency should be proportionate to power. This makes sense on one level and seems simple enough: Politicians should be held accountable which means a heightened level of transparency.

But who is ‘powerful’, how do you define ‘power’ and who is in charge of defining this?

Politicians have chosen to run for public office and submit themselves to public scrutiny, but what about the CEO of a listed company, the leader of a charity, the anonymous owner of a Cayman-islands’ registered corporation? In practice, it is very difficult to apply the ‘transparency is proportionate to power’ rule outside democratic politics.

We need to stop making a binary distinction between freedom of information laws and data protection; between open data policies and privacy policies. We need one single policy framework that controls as well as encourages the use ‘open’ data.

The closest we get is with so-called PEPs (politically exposed persons) databases: Individuals who are the close family and kin, and close business associates of politicians. But even that defines power as derivative from political power, and not commercial, social or other forms of power.

 And what about personal data?  Should personal data ever be open?

Omidyar Network asked this question to 200 guests at a convention on openness and privacy last year. The audience was split down the middle: 50% thought personal data could never be open data. 50% thought that it should, and that foregoing the opportunity to release it would block the promise of economic gains, better services and other benefits. Open data experts, including the 1,000 who attended a recent meeting in Ottawa, ultimately disagree on this fundamental issue.

Herein lies the challenge. Many of us, including the general public, are uncomfortable with open personal data, even despite the gains it can bring….(More)”