international development

World’s biggest city database shines light on our increasingly urbanised planet

Curated on February 14, 2018August 3, 2018 by Stefaan Verhulst

EU Joint Research Centers: “The JRC has launched a new tool with data on all 10,000 urban centres scattered across the globe. It is the largest and most comprehensive database on cities ever published.

With data derived from the JRC’s Global Human Settlement Layer (GHSL), researchers have discovered that the world has become even more urbanised than previously thought.

Populations in urban areas doubled in Africa and grew by 1.1 billion in Asia between 1990 and 2015.

Globally, more than 400 cities have a population between 1 and 5 million. More than 40 cities have 5 to 10 million people, and there are 32 ‘megacities’ with above 10 million inhabitants.

There are some promising signs for the environment: Cities became 25% greener between 2000 and 2015. And although air pollution in urban centres was increasing from 1990, between 2000 and 2015 the trend was reversed.

With every high density area of at least 50,000 inhabitants covered, the city centres database shows growth in population and built-up areas over the past 40 years. Environmental factors tracked include:

‘Greenness’: the estimated amount of healthy vegetation in the city centre
Soil sealing: the covering of the soil surface with materials like concrete and stone, as a result of new buildings, roads and other public and private spaces
Air pollution: the level of polluting particles such as PM2.5 in the air
Vicinity to protected areas: the percentage of natural protected space within 30 km distance from the city centre’s border
Disaster risk-related exposure of population and buildings in low lying areas and on steep slopes.

The data is free to access and open to everyone. It applies big data analytics and a global, people-based definition of cities, providing support to monitor global urbanisation and the 2030 Sustainable Development Agenda.

The information gained from the GHSL is used to map out population density and settlement maps. Satellite, census and local geographic information are used to create the maps….(More)”.

Artificial Intelligence and Foreign Policy

Curated on February 8, 2018August 3, 2018 by Stefaan Verhulst

Paper by Ben Scott, Stefan Heumann and Philppe Lorenz: “The plot-lines of the development of Artificial Intelligence (AI) are debated and contested. But it is safe to predict that it will become one of the central technologies of the 21st century. It is fashionable these days to speak about data as the new oil. But if we want to “refine” the vast quantities of data we are collecting today and make sense of it, we will need potent AI. The consequences of the AI revolution could not be more far reaching. Value chains will be turned upside down, labor markets will get disrupted and economic power will shift to those who control this new technology. And as AI is deeply embedded in the connectivity of the Internet, the challenge of AI is global in nature. Therefore it is striking that AI is almost absent from the foreign policy agenda.

This paper seeks to provide a foundation for planning a foreign policy strategy that responds effectively to the emerging power of AI in international affairs. The developments in AI are so dynamic and the implications so wide-ranging that ministries need to begin engaging immediately. That means starting with the assets and resources at hand while planning for more significant changes in the future. Many of the tools of traditional diplomacy can be adapted to this new field. While the existing toolkit can get us started, this pragmatic approach does not preclude thinking about more drastic changes that the technological changes might require for our foreign policy institutions and instruments.

The paper approaches this challenge, drawing on the existing foreign policy toolbox and reflecting on the past lessons of adapting this toolbox to the Internet revolution. The paper goes on to make suggestions on how the tools could be applied to the international challenges that the AI revolution will bring about. The toolbox includes policy making, public diplomacy, bilateral and multilateral engagement, actions through international and treaty organizations, convenings and partnerships, grant-making and information-gathering and analysis. The analysis of the international challenges of the AI transformation are divided into three topical areas. Each of the three sections includes concrete suggestions how instruments from the tool box could be applied to address the challenges AI will bring about in international affairs….(More)“.

And Yet They Thrive!—Regaining the Relevance of a Transparency System

Curated on February 6, 2018August 3, 2018 by Stefaan Verhulst

Paper by Pontus Hedlin in Development Policy Review: “Over the past decade, a host of donor organizations implemented transparency systems to make international development aid more transparent to the public. These initiatives have met with little public interest, but their proliferation and development show no sign of diminishing. This article shows how internal importance to the political system, fueled by formal rankings and the exhibition of transparency systems as a flagship initiative, can replace relevance to the public as a driving force for sustainable development. The article concludes by discussing the possibility of a future development where transparency systems finally do connect with user groups, such as citizens of both donor and recipient countries, and gain a relevance even beyond original intentions….(More)”.

Views on Open Data Business from Software Development Companies

Curated on February 6, 2018August 3, 2018 by Stefaan Verhulst

Antti Herala, Jussi Kasurinen, and Erno Vanhala in the Journal of Theoretical and Applied Electronic Commerce Research: “The main concept of open data and its application is simple; access to the publicly-funded data provides greater returns from the public investment and can generate wealth through the downstream use of outputs, such as traffic information or weather forecast services. However, even though open data and data sharing as concepts are forty years old with the open data initiative reaching ten, the practical actions and applications have tended to stay on the superficial level, and significant progress or success stories are hard to find. The current trend is that the governments and municipalities are opening their data, but the impact and usefulness of raw open data repositories to citizens – and even to businesses – can be questioned Besides the governments, a handful of private organizations are opening their data in an attempt to unlock the economic value of open data, but even they have difficulties finding innovative usage, let alone generate additional profit.

In a previous study it was found that companies are interested in open data and that this mindset spans over different industries, from both publicly available data to the private business-to-business data access. Open data is not only a resource for software companies, but also for traditional engineering industries and even for small, nonfranchised local markets and shops. In our previous study, it was established that there is evidence on recognizing the applicability of open data, and opening the data to the clients by private organizations leads to business opportunities, creating new value.

However, while there is interest towards open data in a wide variety of businesses, the question still remains whether or not open data is actually used to generate income or are there some other sharing methods in use that are more efficient and more profitable.

For this study, four research questions were formulated. The first three are concentrating on the usage of open data as well as the interest towards opening or sharing data and the fourth research question revolves around the different types of openness:

How do new clients express interest towards open data?
What kind of open data-based solutions is the existing clientele expecting?
How does the product portfolio of a software company respond to open data?
What are the current trends of open initiatives?…(More)”.

The Modern Research Data Portal: a design pattern for networked, data-intensive science

Curated on January 30, 2018August 20, 2018 by Stefaan Verhulst

Kyle Chard et al in PeerJ Computer Science: “We describe best practices for providing convenient, high-speed, secure access to large data via research data portals. We capture these best practices in a new design pattern, the Modern Research Data Portal, that disaggregates the traditional monolithic web-based data portal to achieve orders-of-magnitude increases in data transfer performance, support new deployment architectures that decouple control logic from data storage, and reduce development and operations costs.

We introduce the design pattern; explain how it leverages high-performance data enclaves and cloud-based data management services; review representative examples at research laboratories and universities, including both experimental facilities and supercomputer sites; describe how to leverage Python APIs for authentication, authorization, data transfer, and data sharing; and use coding examples to demonstrate how these APIs can be used to implement a range of research data portal capabilities. Sample code at a companion web site, https://docs.globus.org/mrdp, provides application skeletons that readers can adapt to realize their own research data portals….(More)”.

Rights-Based and Tech-Driven: Open Data, Freedom of Information, and the Future of Government Transparency

Curated on January 30, 2018August 3, 2018 by Stefaan Verhulst

Beth Noveck at the Yale Human Rights and Development Journal: “Open data policy mandates that government proactively publish its data online for the public to reuse. It is a radically different approach to transparency than traditional right-to-know strategies as embodied in Freedom of Information Act (FOIA) legislation in that it involves ex ante rather than ex post disclosure of whole datasets. Although both open data and FOIA deal with information sharing, the normative essence of open data is participation rather than litigation. By fostering public engagement, open data shifts the relationship between state and citizen from a monitorial to a collaborative one, centered around using information to solve problems together. This Essay explores the theory and practice of open data in comparison to FOIA and highlights its uses as a tool for advancing human rights, saving lives, and strengthening democracy. Although open data undoubtedly builds upon the fifty-year legal tradition of the right to know about the workings of one’s government, open data does more than advance government accountability. Rather, it is a distinctly twenty-first century governing practice borne out of the potential of big data to help solve society’s biggest problems. Thus, this Essay charts a thoughtful path toward a twenty-first century transparency regime that takes advantage of and blends the strengths of open data’s collaborative and innovation-centric approach and the adversarial and monitorial tactics of freedom of information regimes….(More)”.

Extracting crowd intelligence from pervasive and social big data

Curated on January 20, 2018August 3, 2018 by Stefaan Verhulst

Introduction by Leye Wang, Vincent Gauthier, Guanling Chen and Luis Moreira-Matias of Special Issue of the Journal of Ambient Intelligence and Humanized Computing: “With the prevalence of ubiquitous computing devices (smartphones, wearable devices, etc.) and social network services (Facebook, Twitter, etc.), humans are generating massive digital traces continuously in their daily life. Considering the invaluable crowd intelligence residing in these pervasive and social big data, a spectrum of opportunities is emerging to enable promising smart applications for easing individual life, increasing company profit, as well as facilitating city development. However, the nature of big data also poses fundamental challenges on the techniques and applications relying on the pervasive and social big data from multiple perspectives such as algorithm effectiveness, computation speed, energy efficiency, user privacy, server security, data heterogeneity and system scalability. This special issue presents the state-of-the-art research achievements in addressing these challenges. After the rigorous review process of reviewers and guest editors, eight papers were accepted as follows.

The first paper “Automated recognition of hypertension through overnight continuous HRV monitoring” by Ni et al. proposes a non-invasive way to differentiate hypertension patients from healthy people with the pervasive sensors such as a waist belt. To this end, the authors train a machine learning model based on the heart rate data sensed from waists worn by a crowd of people, and the experiments show that the detection accuracy is around 93%.

The second paper “The workforce analyzer: group discovery among LinkedIn public profiles” by Dai et al. describes two users’ group discovery methods among LinkedIn public profiles. One is based on K-means and another is based on SVM. The authors contrast results of both methods and provide insights about the trending professional orientations of the workforce from an online perspective.

The third paper “Tweet and followee personalized recommendations based on knowledge graphs” by Pla Karidi et al. present an efficient semantic recommendation method that helps users filter the Twitter stream for interesting content. The foundation of this method is a knowledge graph that can represent all user topics of interest as a variety of concepts, objects, events, persons, entities, locations and the relations between them. An important advantage of the authors’ method is that it reduces the effects of problems such as over-recommendation and over-specialization.

The fourth paper “CrowdTravel: scenic spot profiling by using heterogeneous crowdsourced data” by Guo et al. proposes CrowdTravel, a multi-source social media data fusion approach for multi-aspect tourism information perception, which can provide travelling assistance for tourists by crowd intelligence mining. Experiments over a dataset of several popular scenic spots in Beijing and Xi’an, China, indicate that the authors’ approach attains fine-grained characterization for the scenic spots and delivers excellent performance.

The fifth paper “Internet of Things based activity surveillance of defence personnel” by Bhatia et al. presents a comprehensive IoT-based framework for analyzing national integrity of defence personnel with consideration to his/her daily activities. Specifically, Integrity Index Value is defined for every defence personnel based on different social engagements, and activities for detecting the vulnerability to national security. In addition to this, a probabilistic decision tree based automated decision making is presented to aid defence officials in analyzing various activities of a defence personnel for his/her integrity assessment.

The sixth paper “Recommending property with short days-on-market for estate agency” by Mou et al. proposes an estate with short days-on-market appraisal framework to automatically recommend those estates using transaction data and profile information crawled from websites. Both the spatial and temporal characteristics of an estate are integrated into the framework. The results show that the proposed framework can estimate accurately about 78% estates.

The seventh paper “An anonymous data reporting strategy with ensuring incentives for mobile crowd-sensing” by Li et al. proposes a system and a strategy to ensure anonymous data reporting while ensuring incentives simultaneously. The proposed protocol is arranged in five stages that mainly leverage three concepts: (1) slot reservation based on shuffle, (2) data submission based on bulk transfer and multi-player dc-nets, and (3) incentive mechanism based on blind signature.

The last paper “Semantic place prediction from crowd-sensed mobile phone data” by Celik et al. semantically classifes places visited by smart phone users utilizing the data collected from sensors and wireless interfaces available on the phones as well as phone usage patterns, such as battery level, and time-related information, with machine learning algorithms. For this study, the authors collect data from 15 participants at Galatasaray University for 1 month, and try different classification algorithms such as decision tree, random forest, k-nearest neighbour, naive Bayes, and multi-layer perceptron….(More)”.

Appropriating technology for accountability

Curated on January 18, 2018August 3, 2018 by Stefaan Verhulst

Research report by Rosie McGee with Duncan Edwards, Colin Anderson, Hannah Hudson and Francesca Feruglio: “Making All Voices Count was a programme designed to solve the ‘grand challenge’ of creating more effective democratic governance and accountability around the world. Conceived in an era of optimism about the use of tech to open up government and allow more fluid communication between citizens and governments, it used funding from four donors to support the development and spread of innovative ideas for solving governance problems – many of them involving tools and platforms based on mobile phone and web technologies. Between 2013 and 2017, the programme made grants for innovation and scaling projects that aimed to amplify the voices of citizens and enable governments to listen and respond. It also conducted research and issued research grants to explore the roles that technology can play in securing responsive, accountable government.

This synthesis report reviews the Making All Voices Count’s four-and-a-half years of operational experience and learning. In doing so, it revisits and assesses the key working assumptions and expectations about the roles that technologies can play in governance, which underpinned the programme at the outset. The report draws on a synthesis of evidence from Making All Voices Count’s 120+ research, evidence and learning-focused publications, and the insights and knowledge that arose from the innovation, scaling and research projects funded through the programme, and the related grant accompaniment activities.

It shares 14 key messages on the roles technologies can play in enabling citizen voice and accountable and responsive governance. These messages are presented in four sections:

Applying technologies as technical fixes to solve service delivery problems
Applying technologies to broader, systemic governance challenges
Applying technologies to build the foundations of democratic and accountable governance systems
Applying technologies for the public ‘bad’.

The research concludes that the tech optimism of the era in which the programme was conceived can now be reappraised from the better-informed vantage point of hindsight. Making All Voices Count’s wealth of diverse and grounded experience and documentation provides an evidence base that should enable a more sober and mature position of tech realism as the field of tech for accountable governance continues to evolve….(More)”.

The Future Computed: Artificial Intelligence and its role in society

Curated on January 17, 2018August 20, 2018 by Stefaan Verhulst

Brad Smith at the Microsoft Blog: “Today Microsoft is releasing a new book, The Future Computed: Artificial Intelligence and its role in society. The two of us have written the foreword for the book, and our teams collaborated to write its contents. As the title suggests, the book provides our perspective on where AI technology is going and the new societal issues it has raised.

On a personal level, our work on the foreword provided an opportunity to step back and think about how much technology has changed our lives over the past two decades and to consider the changes that are likely to come over the next 20 years. In 1998, we both worked at Microsoft, but on opposite sides of the globe. While we lived on separate continents and in quite different cultures, we shared similar experiences and daily routines which were managed by manual planning and movement. Twenty years later, we take for granted the digital world that was once the stuff of science fiction.

Technology – including mobile devices and cloud computing – has fundamentally changed the way we consume news, plan our day, communicate, shop and interact with our family, friends and colleagues. Two decades from now, what will our world look like? At Microsoft, we imagine that artificial intelligence will help us do more with one of our most precious commodities: time. By 2038, personal digital assistants will be trained to anticipate our needs, help manage our schedule, prepare us for meetings, assist as we plan our social lives, reply to and route communications, and drive cars.

Beyond our personal lives, AI will enable breakthrough advances in areas like healthcare, agriculture, education and transportation. It’s already happening in impressive ways.

But as we’ve witnessed over the past 20 years, new technology also inevitably raises complex questions and broad societal concerns. As we look to a future powered by a partnership between computers and humans, it’s important that we address these challenges head on.

How do we ensure that AI is designed and used responsibly? How do we establish ethical principles to protect people? How should we govern its use? And how will AI impact employment and jobs?

To answer these tough questions, technologists will need to work closely with government, academia, business, civil society and other stakeholders. At Microsoft, we’ve identified six ethical principles – fairness, reliability and safety, privacy and security, inclusivity, transparency, and accountability – to guide the cross-disciplinary development and use of artificial intelligence. The better we understand these or similar issues — and the more technology developers and users can share best practices to address them — the better served the world will be as we contemplate societal rules to govern AI.

We must also pay attention to AI’s impact on workers. What jobs will AI eliminate? What jobs will it create? If there has been one constant over 250 years of technological change, it has been the ongoing impact of technology on jobs — the creation of new jobs, the elimination of existing jobs and the evolution of job tasks and content. This too is certain to continue.

Some key conclusions are emerging….

The Future Computed is available here and additional content related to the book can be found here.”