Legislation Lab

Curated on Posted on by Stefaan Verhulst

“Legislation Lab is a platform for encouraging public awareness and discussion of upcoming legislation. We offer citizens easy access to legislation and provide a participatory model to collect their feedback,

  • Citizen can read through the different sections of the legislation, compare it to related international experiences.
  • Participants voice their opinions through voting, commenting and proposing changes.
  • Real-time, automated data analysis provides visibility into the opinions and demographics of participants.
  • Legislation Lab works on a transparent participation model, proving authenticity through transparency. All contributions are clearly identified with their source and aggregate demographics are provided clearly and openly.

All law documents in Legislation Lab are under the stewardship of a law facilitator. Law facilitators come from a variety of backgrounds including government, organizations, or even the general public. GovRight works with law facilitators to help them import legislation and to promote a meaningful discussion with citizens….

Legislation Lab is the product of years of experience by GovRight in the implementation of meaningful public discourse and participation in government.

Case Study: Reforme.ma

In early 2011 citizens of Morocco took to the streets to denounce social injustice, unemployment, and corruption and to call for a genuine constitutional monarchy. In March, King Mohammed VI announced the launch of constitutional reforms, but for the average citizen of Morocco there was little opportunity to voice their opinion on the content or direction of these reforms.

To address this, Tarik Nesh-Nash (GovRight co-founder & CEO) launched with a partner Reforme.ma, a participatory platform to collect the opinions of average Moroccan citizens on changes to the constitution. Within two months Reforme.ma was visited by more than 200,000 visitors and received more than 10,000 comments and proposals. Contributors were a broad demographic of Moroccan citizens ranging from all regions of the country…(More)”

How to use mobile phone data for good without invading anyone’s privacy

Curated on Posted on by Stefaan Verhulst

Leo Mirani in Quartz: “In 2014, when the West African Ebola outbreak was at its peak, some academics argued that the epidemic could have been slowed by using mobile phone data.

Their premise was simple: call-data records show the true nature of social networks and human movement. Understanding social networks and how people really move—as seen from phone movements and calls—could give health officials the ability to predict how a disease will move and where a disease will strike next, and prepare accordingly.

The problem is that call-data records are very hard to get a hold of. The files themselves are huge, there are enormous privacy risks, and the process of making the records safe for distribution is long.
First, the technical basics

Every time you make a phone call from your mobile phone to another mobile phone, the network records the following information (note: this is not a complete list):

  • The number from which the call originated
  • The number at which the call terminated
  • Start time of the call
  • Duration of the call
  • The ID number of the phone making the call
  • The ID number of the SIM card used to make the call
  • The code for the antenna used to make the call

On their own, these records are not creepy. Indeed, without them, networks would be unable to connect calls or bill customers. But it is easy to see why operators aren’t rushing to share this information. Even though the data includes none of the actual content of a phone call in the data, simply knowing which number is calling which, and from where and when, is usually more than enough to identify people.
So how can network operators use this valuable data for good while also protecting their own interests and those of their customers? A good example can be found in Africa, where Orange, a French mobile phone network with interests across several African countries, has for the second year run its “Data for Development” (D4D) program, which offers researchers a chance to mine call data for clues on development problems.

Steps to safe sharing

After a successful first year in Ivory Coast, Orange this year ran the D4D program in Senegal. The aim of the program is to give researchers and scientists at universities and other research labs access to data in order to find novel ways to aid development in health, agriculture, transport or urban planning, energy, and national statistics….(More)”

Enhancing Social Accountability Through ICT: Success Factors and Challenges

Curated on Posted on by Stefaan Verhulst

Wakabi, Wairagala and  Grönlund, Åke for the International Conference for E-Democracy and Open Government 2015: “This paper examines the state of citizen participation in public accountability processes via Information and Communication Technologies (ICT). It draws on three projects that use ICT to report public service delivery failures in Uganda, mainly in the education, public health and the roads sectors. While presenting common factors hampering meaningful use of ICT for citizens’ monitoring of public services and eParticipation in general, the paper studies the factors that enabled successful whistle blowing using toll free calling, blogging, radio talk shows, SMS texting, and e-mailing. The paper displays examples of the positive impacts of whistle-blowing mechanisms and draws up a list of success factors applicable to these projects. It also outlines common challenges and drawbacks to initiatives that use ICT to enable citizen participation in social accountability. The paper provides pathways that could give ICT-for-participation and for-accountability initiatives in countries with characteristics similar to Uganda a good chance of achieving success. While focusing on Uganda, the paper may be of practical value to policy makers, development practitioners and academics in countries with similar socio-economic standings….(More)”

A new approach to measuring the impact of open data

Curated on Posted on by Stefaan Verhulst

 at SunLight Foundation: “Strong evidence on the long-term impact of open data initiatives is incredibly scarce. The lack of compelling proof is partly due to the relative novelty of the open government field, but also to the inherent difficulties in measuring good governance and social change. We know that much of the impact of policy advocacy, for instance, occurs even before a new law or policy is introduced, and is thus incredibly difficult to evaluate. At the same time, it is also very hard to detect the causality between a direct change in the legal environment and the specific activities of a policy advocacy group. Attribution is equally challenging when it comes to assessing behavioral changes – who gets to take credit for increased political engagement and greater participation in democratic processes?

Open government projects tend to operate in an environment where the contribution of other stakeholders and initiatives is essential to achieving sustainable change, making it even more difficult to show the causality between a project’s activities and the impact it strives to achieve. Therefore, these initiatives cannot be described through simple “cause and effect” relationships, as they mostly achieve changes through their contribution to outcomes produced by a complex ecosystem of stakeholders — including journalists, think tanks, civil society organizations, public officials and many more — making it even more challenging to measure their direct impact.

We at the Sunlight Foundation wanted to tackle some of the methodological challenges of the field through building an evidence base that can empower further generalizations and advocacy efforts, as well as developing a methodological framework to unpack theories of change and to evaluate the impact of open data and digital transparency initiatives. A few weeks ago, we presented our research at the Cartagena Data Festival, and today we are happy to launch the first edition of our paper, which you can read below or on Scribd.

The outputs of this research include:

  • A searchable repository of more than 100 examples on the outputs, outcomes and impacts of open data and digital technology projects;
  • Three distinctive theories of change for open data and digital transparency initiatives from the Global South;
  • A methodological framework to help develop more robust indicators of social and political change for the ecosystem of open data initiatives, by applying and revising the Outcome Mapping approach of IDRC to the field…(You can read the study at :The Social Impact of Open Data by juliakeseru)

Five Headlines from a Big Month for the Data Revolution

Curated on Posted on by Stefaan Verhulst

Sarah T. Lucas at Post2015.org: “If the history of the data revolution were written today, it would include three major dates. May 2013, when theHigh Level Panel on the Post-2015 Development Agenda first coined the phrase “data revolution.” November 2014, when the UN Secretary-General’s Independent Expert Advisory Group (IEAG) set a vision for it. And April 2015, when five headliner stories pushed the data revolution from great idea to a concrete roadmap for action.

The April 2015 Data Revolution Headlines

1. The African Data Consensus puts Africa in the lead on bringing the data revolution to the regional level. TheAfrica Data Consensus (ADC) envisions “a profound shift in the way that data is harnessed to impact on development decision-making, with a particular emphasis on building a culture of usage.” The ADC finds consensus across 15 “data communities”—ranging from open data to official statistics to geospatial data, and is endorsed by Africa’s ministers of finance. The ADC gets top billing in my book, as the first contribution that truly reflects a large diversity of voices and creates a political hook for action. (Stay tuned for a blog from my colleague Rachel Quint on the ADC).

2. The Sustainable Development Solutions Network (SDSN) gets our minds (and wallets) around the data needed to measure the SDGs. The SDSN Needs Assessment for SDG Monitoring and Statistical Capacity Development maps the investments needed to improve official statistics. My favorite parts are the clear typology of data (see pg. 12), and that the authors are very open about the methods, assumptions, and leaps of faith they had to take in the costing exercise. They also start an important discussion about how advances in information and communications technology, satellite imagery, and other new technologies have the potential to expand coverage, increase analytic capacity, and reduce the cost of data systems.

3. The Overseas Development Institute (ODI) calls on us to find the “missing millions.” ODI’s The Data Revolution: Finding the Missing Millions presents the stark reality of data gaps and what they mean for understanding and addressing development challenges. The authors highlight that even that most fundamental of measures—of poverty levels—could be understated by as much as a quarter. And that’s just the beginning. The report also pushes us to think beyond the costs of data, and focus on how much good data can save. With examples of data lowering the cost of doing government business, the authors remind us to think about data as an investment with real economic and social returns.

4. Paris21 offers a roadmap for putting national statistic offices (NSOs) at the heart of the data revolution.Paris21’s Roadmap for a Country-Led Data Revolution does not mince words. It calls on the data revolution to “turn a vicious cycle of [NSO] underperformance and inadequate resources into a virtuous one where increased demand leads to improved performance and an increase in resources and capacity.” It makes the case for why NSOs are central and need more support, while also pushing them to modernize, innovate, and open up. The roadmap gets my vote for best design. This ain’t your grandfather’s statistics report!

5. The Cartagena Data Festival features real-live data heroes and fosters new partnerships. The Festival featured data innovators (such as terra-i using satellite data to track deforestation), NSOs on the leading edge of modernization and reform (such as Colombia and the Philippines), traditional actors using old data in new ways (such as the Inter-American Development Bank’s fantastic energy database), groups focused on citizen-generated data (such as The Data Shift and UN My World), private firms working with big data for social good (such asTelefónica), and many others—all reminding us that the data revolution is well underway and will not be stopped. Most importantly, it brought these actors together in one place. You could see the sparks flying as folks learned from each other and hatched plans together. The Festival gets my vote for best conference of a lifetime, with the perfect blend of substantive sessions, intense debate, learning, inspiration, new connections, and a lot of fun. (Stay tuned for a post from my colleague Kristen Stelljes and me for more on Cartagena).

This month full of headlines leaves no room for doubt—momentum is building fast on the data revolution. And just in time.

With the Financing for Development (FFD) conference in Addis Ababa in July, the agreement of Sustainable Development Goals in New York in September, and the Climate Summit in Paris in December, this is a big political year for global development. Data revolutionaries must seize this moment to push past vision, past roadmaps, to actual action and results…..(More)”

How Data Mining could have prevented Tunisia’s Terror attack in Bardo Museum

Curated on Posted on by Stefaan Verhulst

Wassim Zoghlami at Medium: “…Data mining is the process of posing queries and extracting useful patterns or trends often previously unknown from large amounts of data using various techniques such as those from pattern recognition and machine learning. Latelely there has been a big interest on leveraging the use of data mining for counter-terrorism applications

Using the data on more than 50.000+ ISIS connected twitter accounts , I was able to establish an understanding of some factors determined how often ISIS attacks occur , what different types of terror strikes are used in which geopolitical situations, and many other criteria through graphs about the frequency of hashtags usages and the frequency of a particular group of the words used in the tweets.

A simple data mining project of some of the repetitive hashtags and sequences of words used typically by ISIS militants in their tweets yielded surprising results. The results show a rise of some keywords on the tweets that started from Marsh 15, three days before Bardo museum attacks.

Some of the common frequent keywords and hashtags that had a unusual peak since marsh 15 , three days before the attack :

#طواغيت تونس : Tyrants of Tunisia = a reference to the military

بشرى تونس : Good news for Tunisia.

قريبا تونس : Soon in Tunisia.

#إفريقية_للإعلام : The head of social media of Afriqiyah

#غزوة_تونس : The foray of Tunis…

Big Data and Data Mining should be used for national security intelligence

The Tunisian national security has to leverage big data to predict such attacks and to achieve objectives as the volume of digital data. Some of the challenges facing the Data mining techniques are that to carry out effective data mining and extract useful information for counterterrorism and national security, we need to gather all kinds of information about individuals. However, this information could be a threat to the individuals’ privacy and civil liberties…(More)”

Wicked Opportunities

Curated on Posted on by Stefaan Verhulst

Essay by William D. Eggers & Anna Muoio: “Wicked problems”—ranging from malaria to dwindling water supplies—are being reframed as “wicked opportunities” and tackled by networks of nongovernmental organizations, social entrepreneurs, governments, and big businesses.

As a killer disease, malaria is the world’s third biggest, after only HIV/AIDS and tuberculosis. In 2013, an estimated 584,000 people died of it—90 percent of these deaths in Africa, mostly among children under five years of age.1 And because 3.2 billion people—almost half the world’s population—live in regions where malaria spreads easily, it is very hard to fight.2 Scores of organizations are embroiled in the complex search for solutions, sometimes pursuing conflicting priorities, always competing for scarce resources. Despite the daunting challenges, here’s how Bill Gates, who has already spent more than $2 billion of Gates Foundation money on the problem, characterizes the situation: “This is one of the greatest opportunities the global health world has ever had.”3

Opportunity? It’s a surprising word even for an optimistic mega-philanthropist to describe a scourge that people have been trying to eliminate, unsuccessfully, for hundreds of years. It’s also, however, a fair statement about what is possible in the 21st century. We’re seeing a trend by which many kinds of “wicked problems”—complex, dynamic, and seemingly intractable social challenges—are being reframed and attacked with renewed vigor through solution ecosystems. Unprecedented networks of non-governmental organizations (NGOs), social entrepreneurs, health professionals, governments, and international development institutions—and yes, businesses—are coalescing around them, and recasting them as wicked opportunities….(More)”

The road to better data

Curated on Posted on by Stefaan Verhulst

Johannes Jütting at OECDInsights: Tradition tells us that more than 3,000 years ago, Moses went to the top of Mount Sinai and came back down with 10 commandments. When the world’s presidents and prime ministers go to the top of the Sustainable Development Goals (SDGs) mountain in New York late this summer they will come down with not 10 commandments but 169. Too many?

Some people certainly think so. “Stupid development goals,” The Economist said recently. It argued that the 17 SDGs and roughly 169 targets should “honour Moses and be pruned to ten goals”. Others disagree. In a report for the Overseas Development Institute, May Miller-Dawkins, warned of the dangers of letting practicality “blunt ambition”. She backed SDGs with “high ambition”.

The debate over the “right” number of goals and targets is interesting, important even. But it misses a key point: No matter how many goals and targets are finally agreed, if we can’t measure their real impact on people’s lives, on our societies and on the environment, then they risk becoming irrelevant.

Unfortunately, we already know that many developing countries have problems compiling even basic social and economic statistics, never mind the complex web of data that will be needed to monitor the SDGs. A few examples: In 2013, about 35% of all live births were not officially registered worldwide, rising to two-thirds in developing countries. In Africa, just seven countries have data on their total number of landholders and women landholders, and none have data from before 2004. Last but not least, fast-changing economies and associated measurement challenges mean we are not sure today if we have worldwide a billion people living in extreme poverty, half a billion or more than a billion.

Why does this matter? Without adequate data, we cannot identify the problems that planning and policymaking need to address. We also cannot judge if governments and others are meeting their commitments. As a report from the Centre for Global Development notes, “Data […] serve as a ‘currency’ for accountability among and within governments, citizens, and civil society at large, and they can be used to hold development agencies accountable.”…(More)”

Data Science and Ebola

Curated on Posted on by Stefaan Verhulst

Inaugural Lecture by Aske Plaat on the acceptance of the position of professor of Data Science at the Universiteit Leiden: “…Today, everybody and everything produces data. People produce large amounts of data in social networks and in commercial transactions. Medical, corporate, and government databases continue to grow. Ten years ago there were a billion Internet users. Now there are more than three billion, most of whom are mobile.1 Sensors continue to get cheaper and are increasingly connected, creating an Internet of Things. The next three billion users of the Internet will not all be human, and will generate a large amount of data. In every discipline, large, diverse, and rich data sets are emerging, from astrophysics, to the life sciences, to medicine, to the behavioral sciences, to finance and commerce, to the humanities and to the arts. In every discipline people want to organize, analyze, optimize and understand their data to answer questions and to deepen insights. The availability of so much data and the ability to interpret it are changing the way the world operates. The number of sciences using this approach is increasing. The science that is transforming this ocean of data into a sea of knowledge is called data science. In many sciences the impact on the research methodology is profound—some even call it a paradigm shift.

…I will address the question of why there is so much interest in data. I will answer this question by discussing one of the most visible recent challenges to public health of the moment, the 2014 Ebola outbreak in West Africa…(More)”

New surveys reveal dynamism, challenges of open data-driven businesses in developing countries

Curated on Posted on by Stefaan Verhulst

Alla Morrison at World Bank Open Data blog: “Was there a class of entrepreneurs emerging to take advantage of the economic possibilities offered by open data, were investors keen to back such companies, were governments tuned to and responsive to the demands of such companies, and what were some of the key financing challenges and opportunities in emerging markets? As we began our work on the concept of an Open Fund, we partnered with Ennovent (India), MDIF (East Asia and Latin America) and Digital Data Divide (Africa) to conduct short market surveys to answer these questions, with a focus on trying to understand whether a financing gap truly existed in these markets. The studies were fairly quick (4-6 weeks) and reached only a small number of companies (193 in India, 70 in Latin America, 63 in South East Asia, and 41 in Africa – and not everybody responded) but the findings were fairly consistent.

  • Open data is still a very nascent concept in emerging markets. and there’s only a small class of entrepreneurs/investors that is aware of the economic possibilities; there’s a lot of work to do in the ‘enabling environment’
    • In many regions the distinction between open data, big data, and private sector generated/scraped/collected data was blurry at best among entrepreneurs and investors (some of our findings consequently are better indicators of  data-driven rather than open data-driven businesses)
  • There’s a small but growing number of open data-driven companies in all the markets we surveyed and these companies target a wide range of consumers/users and are active in multiple sectors
    • A large percentage of identified companies operate in sectors with high social impact – health and wellness, environment, agriculture, transport. For instance, in India, after excluding business analytics companies, a third of data companies seeking financing are in healthcare and a fifth in food and agriculture, and some of them have the low-income population or the rural segment of India as an intended beneficiary segment. In Latin America, the number of companies in business services, research and analytics was closely followed by health, environment and agriculture. In Southeast Asia, business, consumer services, and transport came out in the lead.
    • We found the highest number of companies in Latin America and Asia with the following countries leading the way – Mexico, Chile, and Brazil, with Colombia and Argentina closely behind in Latin America; and India, Indonesia, Philippines, and Malaysia in Asia
  • An actionable pipeline of data-driven companies exists in Latin America and in Asia
    • We heard demand for different kinds of financing (equity, debt, working capital) but the majority of the need was for equity and quasi-equity in amounts ranging from $100,000 to $5 million USD, with averages of between $2 and $3 million USD depending on the region.
  • There’s a significant financing gap in all the markets
    • The investment sizes required, while they range up to several million dollars, are generally small. Analysis of more than 300 data companies in Latin America and Asia indicates a total estimated need for financing of more than $400 million
  • Venture capitals generally don’t recognize data as a separate sector and club data-driven companies with their standard information communication technology (ICT) investments
    • Interviews with founders suggest that moving beyond seed stage is particularly difficult for data-driven startups. While many companies are able to cobble together an initial seed round augmented by bootstrapping to get their idea off the ground, they face a great deal of difficulty when trying to raise a second, larger seed round or Series A investment.
    • From the perspective of startups, investors favor banal e-commerce (e.g., according toTech in Asia, out of the $645 million in technology investments made public across the region in 2013, 92% were related to fashion and online retail) or consumer service startups and ignore open data-focused startups even if they have a strong business model and solid key performance indicators. The space is ripe for a long-term investor with a generous risk appetite and multiple bottom line goals.
  • Poor data quality was the number one issue these companies reported.
    • Companies reported significant waste and inefficiency in accessing/scraping/cleaning data.

The analysis below borrows heavily from the work done by the partners. We should of course mention that the findings are provisional and should not be considered authoritative (please see the section on methodology for more details)….(More).”