Book by The book offers a critical evaluation of Qatar’s path from oil- and gas-based industries to a knowledge-based economy. This book gives basic information about the region and the country, including the geographic and demographic data, the culture, the politics and the economy, the health care conditions and the education system. It introduces the concepts of knowledge society and knowledge-based development and adds factual details about Qatar by interpreting indicators of the development status. Subsequently, the research methods that underlie the study are described, which offers information on the eGovernment study analyzing the government-citizen relationship, higher education institutions and systems, its students and the students’ way into the labor market. This book has an audience with economists, sociologists, political scientists, geographers, information scientists and other researchers on the knowledge society, but also all researchers and practitioners interested in the Arab Oil States and their future….(More)”.
Enhancing social impact through better monitoring, evaluation, and learning
Deloitte: “Social sector organizations tackle some of the world’s most difficult and complex challenges on a daily basis. And, just as in other industries, getting the right data and information at the right time is essential to understanding what an organization needs to achieve, whether it is doing what it set out to do, and what impact its efforts are actually having. Yet, despite marked advances in the tools and methods for monitoring, evaluation, and learning in the social sector, as well as a growing number of bright spots in practice emerging in the field, there is broad dissatisfaction across the sector about how data is—or is not—used….
Based on our interviews, the research team identified three characteristics that participants within and outside the social sector believe should be defining pillars of a better future for monitoring, evaluation, and learning. These three characteristics are purpose, perspective, and alignment with other actors….(More)”
Decoding Data Use: What evidence do world leaders want to achieve their goals?
Paper by Samantha Custer, Takaaki Masaki, and Carolyn Iwicki: “Information is “never the hero”, but it plays a supporting role in how leaders allocate scarce resources and accelerate development in their communities. Even in low- and middle-income countries, decision-makers have ample choices in sourcing evidence from a growing field of domestic and international data providers. However, more information is not necessarily better if it misses the mark for what leaders need to monitor their country’s progress. Claims that information is the “world’s most valuable resource” and calls for a “data revolution” will ring hollow if we can’t decode what leaders actually use — and why.
In a new report, Decoding Data Use: How leaders source data and use it to accelerate development, AidData reveals what 3500 leaders from 126 countries have to say about the types of data or analysis they use, from what sources, and for which purposes in the context of their work. We analyze responses to AidData’s 2017 Listening to Leaders (LTL) Survey to offer insights to help funders, producers, advocates, and infomediaries of development data understand how to position themselves for greater impact….(more)”.
Data for Development
The 2017 volume of the Development Co-operation Report by the OECD focuses on Data for Development: “Big Data” and “the Internet of Things” are more than buzzwords: the data revolution is transforming the way that economies and societies are functioning across the planet. The Sustainable Development Goals along with the data revolution are opportunities that should not be missed: more and better data can help boost inclusive growth, fight inequalities and combat climate change. These data are also essential to measure and monitor progress against the Sustainable Development Goals.
The value of data in enabling development is uncontested. Yet, there continue to be worrying gaps in basic data about people and the planet and weak capacity in developing countries to produce the data that policy makers need to deliver reforms and policies that achieve real, visible and long-lasting development results. At the same time, investing in building statistical capacity – which represented about 0.30% of ODA in 2015 – is not a priority for most providers of development assistance.
There is a need for stronger political leadership, greater investment and more collective action to bridge the data divide for development. With the unfolding data revolution, developing countries and donors have a unique chance to act now to boost data production and use for the benefit of citizens. This report sets out priority actions and good practices that will help policy makers and providers of development assistance to bridge the global data divide, notably by strengthening statistical systems in developing countries to produce better data for better policies and better lives…(More)”.
The social preferences of local citizens and spontaneous volunteerism during disaster relief operations
Paper by Samuel Roscoe et al: “Existing studies on disaster relief operations (DRO) pay limited attention to acts of spontaneous volunteerism by local citizens in the aftermath of disasters. The purpose of this paper is to explore how social preferences motivate citizens to help during post-disaster situations; above and beyond their own self-regarding interests. The paper begins by synthesizing the literature on social preferences from the field of behavioral economics and social psychology with the discourse surrounding behavioral operations management and humanitarian operations management (HOM). By doing so, we identify the motivators, enablers and barriers of local citizen response during disaster relief operations. These factors inform a theoretical framework of the social preferences motivating spontaneous volunteerism in post-disaster situations. We evidence facets of the framework using archival and unstructured data retrieved from Twitter feeds generated by local citizens during the floods that hit Chennai, India in 2015. Our model highlights the importance of individual level action during disaster relief operations and the enabling role of social media as a coordination mechanism for such efforts….(More)”.
Democracy in the digital age: digital agora or dystopia
Paper by Peter Parycek, Bettina Rinnerbauer, and Judith Schossböck in the International Journal of Electronic Governance: “Information and communication technologies (ICTs) affect democracy and the rule of law. Digitalisation has been perceived as a stimulus towards a more participative society or as support to decision making, but not without criticism. Authors draw on a legal review, case studies and quantitative survey data about citizens’ view on transparency and participation in the German-speaking region to summarise selected discourses of democratisation via ICTs and the dominant critique. The paper concludes with an outlook on contemporary questions of digital democracy between the dialectic of protecting citizens’ rights and citizen control. It is proposed that prospective e-participation projects will concentrate on processes of innovation and creativity as opposed to participation rates. Future investigations should evaluate the contexts in which a more data-driven, automated form of decision making could be supported and collect indicators for where to draw the line between the protection and control of citizens, including research on specific tools…(More).
‘Big Data’ Tells Thailand More About Jobs Than Low Unemployment
Suttinee Yuvejwattana at Bloomberg: “Thailand has one of the lowest unemployment rates in the world, which doesn’t always fit the picture of an emerging-market economy that’s struggling to get growth going.
To get a fuller picture of what’s happening in the labor market — as well as in other under-reported industries in the economy, like the property market — the central bank is increasingly turning to “big data” sources drawn from social media and online stores to supplement official figures.
The Bank of Thailand is building its own employment index based on data from online jobs-search portals and is also creating a property indicator to give it a better sense of supply and demand in the housing market.
“We want to do evidence-based policy so big data is useful,” Jaturong Jantarangs, an assistant governor at the Bank of Thailand, said in an interview in Bangkok. “It’s not only a benefit to monetary policy but financial policy as well.”…
“Official data can’t capture the whole picture of the economy,” said Somprawin Manprasert, Bangkok-based head of research at Bank of Ayudhya Pcl. “We have a big informal sector. Many people are self-employed. This leads to a low unemployment rate.”
“The big data can show all aspects, so it can help us to solve the problems where they are,” he said…
Thailand’s military administration is also trying to harness big data to improve policy decisions, Digital Economy and Society Minister Pichet Durongkaveroj said in an interview last month. Pichet said he’s been tasked to look into digitizing, integrating and analyzing information across more than 200 government departments.
Santitarn Sathirathai, head of emerging Asia economics at Credit Suisse Group AG in Singapore, said big data analytics can be used to better target policy responses as well as allow timely evaluation of past programs. At the same time, he called on authorities to make their data more readily available to the public.
“The government should not just view big data analytics as being solely about it using richer data but also about creating a more open data environment,” he said. That’s to ensure “people can have better access to many government non-sensitive datasets and help conduct analysis that could complement the policy makers,” he said….(More)”.
What Are Data? A Categorization of the Data Sensitivity Spectrum
Paper by John M.M. Rumbold and Barbara K. Pierscionek in Big Data Research: “The definition of data might at first glance seem prosaic, but formulating a definitive and useful definition is surprisingly difficult. This question is important because of the protection given to data in law and ethics. Healthcare data are universally considered sensitive (and confidential), so it might seem that the categorisation of less sensitive data is relatively unimportant for medical data research. This paper will explore the arguments that this is not necessarily the case and the relevance of recognizing this.
The categorization of data and information requires re-evaluation in the age of Big Data in order to ensure that the appropriate protections are given to different types of data. The aggregation of large amounts of data requires an assessment of the harms and benefits that pertain to large datasets linked together, rather than simply assessing each datum or dataset in isolation. Big Data produce new data via inferences, and this must be recognized in ethical assessments. We propose a schema for a granular assessment of data categories. The use of schemata such as this will assist decision-making by providing research ethics committees and information governance bodies with guidance about the relative sensitivities of data. This will ensure that appropriate and proportionate safeguards are provided for data research subjects and reduce inconsistency in decision making…(More)”.
Evidence-Based Policy Mistakes
Kaushik Basu at Project Syndicate: “… it is important to recognize that data alone are not enough to determine future expectations or policies. While there is certainly value in collecting data (via, for example, randomized control trials), there is also a need for deductive and inductive reasoning, guided by common sense – and not just on the part of experts. By dismissing the views and opinions of ordinary people, economists may miss out on crucial insights.
People’s everyday experiences provide huge amounts of potentially useful information. While a common-sense approach based on individual experience is not the most “scientific,” it should not be dismissed out of hand. A meteorologist might detect a coming storm by plugging data from myriad sources – atmospheric sensors, weather balloons, radar, and satellites – into complex computer models. But that doesn’t mean that the sight of gathering clouds in the sky is not also a legitimate sign that one might need an umbrella – even if the weather forecast promises sunshine.
Intuition and common sense have been critical to our evolution. After all, had humans not been able to draw reasonably accurate conclusions about the world through experience or observation, we wouldn’t have survived as a species.
The development of more systematic approaches to scientific inquiry has not diminished the need for such intuitive reasoning. In fact, there are important and not obvious truths that are best deduced using pure reason.
Consider the Pythagorean Theorem, which establishes the relation among the three sides of a right triangle. If all conclusions had to be reached by combing through large data sets, Pythagoras, who is believed to have devised the theorem’s first proof, would have had to measure a huge number of right triangles. In any case, critics would likely argue that he had looked at a biased sample, because all of the triangles examined were collected from the Mediterranean region.
Inductive reasoning, too, is vital to reach certain kinds of knowledge. We “know” that an apple will not remain suspended in mid-air, because we have seen so many objects fall. But such reasoning is not foolproof. As Bertrand Russell pointed out, “The man who has fed the chicken every day throughout its life at last wrings its neck instead, showing that more refined views as to the uniformity of nature would have been useful to the chicken.”
Of course, many policymakers – not just the likes of Erdoğan and Trump – make bad decisions not because of a misunderstanding of the evidence, but because they prefer to pursue politically expedient measures that benefit their benefactors or themselves. In such cases, exposing the inappropriateness of their supposed evidence may be the only option.
But, for the rest, the imperative must be to advocate for a more comprehensive approach, in which leaders use “reasoned intuition” to draw effective conclusions based on hard data. Only then will the age of effective evidence-based policymaking really begin….(More)”.
Influenzanet: Citizens Among 10 Countries Collaborating to Monitor Influenza in Europe
Paper by Carl E Koppeschaar et al in the Special Issue of JMIR Public Health and Surveillance on Participatory Disease Surveillance: “The wide availability of the Internet and the growth of digital communication technologies have become an important tool for epidemiological studies and health surveillance. Influenzanet is a participatory surveillance system monitoring the incidence of influenza-like illness (ILI) in Europe since 2003. It is based on data provided by volunteers who self-report their symptoms via the Internet throughout the influenza season and currently involves 10 countries.
Objective: In this paper, we describe the Influenzanet system and provide an overview of results from several analyses that have been performed with the collected data, which include participant representativeness analyses, data validation (comparing ILI incidence rates between Influenzanet and sentinel medical practice networks), identification of ILI risk factors, and influenza vaccine effectiveness (VE) studies previously published. Additionally, we present new VE analyses for the Netherlands, stratified by age and chronic illness and offer suggestions for further work and considerations on the continuity and sustainability of the participatory system.
Methods: Influenzanet comprises country-specific websites where residents can register to become volunteers to support influenza surveillance and have access to influenza-related information. Participants are recruited through different communication channels. Following registration, volunteers submit an intake questionnaire with their postal code and sociodemographic and medical characteristics, after which they are invited to report their symptoms via a weekly electronic newsletter reminder. Several thousands of participants have been engaged yearly in Influenzanet, with over 36,000 volunteers in the 2015-16 season alone.
Results: In summary, for some traits and in some countries (eg, influenza vaccination rates in the Netherlands), Influenzanet participants were representative of the general population. However, for other traits, they were not (eg, participants underrepresent the youngest and oldest age groups in 7 countries). The incidence of ILI in Influenzanet was found to be closely correlated although quantitatively higher than that obtained by the sentinel medical practice networks. Various risk factors for acquiring an ILI infection were identified. The VE studies performed with Influenzanet data suggest that this surveillance system could develop into a complementary tool to measure the effectiveness of the influenza vaccine, eventually in real time.
Conclusions: Results from these analyses illustrate that Influenzanet has developed into a fast and flexible monitoring system that can complement the traditional influenza surveillance performed by sentinel medical practices. The uniformity of Influenzanet allows for direct comparison of ILI rates between countries. It also has the important advantage of yielding individual data, which can be used to identify risk factors. The way in which the Influenzanet system is constructed allows the collection of data that could be extended beyond those of ILI cases to monitor pandemic influenza and other common or emerging diseases….(More)”. (see also https://www.influenzanet.eu/)