"Spatially and temporally relevant ‘big data’ that does not require data collection in the field has the potential to provide insights into people’s economic, social, behavioural and political lives, and hence could be used in measuring key development outcomes. Big data consists of humangener
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ated data including online searches, social media, citizen reporting or crowdsourced data, process-mediated data such as mobile phone call record details (CRD), commercial transactions data and machine-generated data from satellites, sensors or drones. The primary value of big data is that it is possible to measure outcomes that could not previously be measured using household surveys at the required temporal and spatial scale. The potential of big data to answer causal attribution, however, is still not widely understood, especially in low- and middle-income countries (L&MICs). The report is based on a map of the studies using big data and its objective is to discuss methodological, ethical and practical constraints relating to the use of big data. The systematic map includes impact evaluations (IEs) that use big data to evaluate development outcomes, systematic reviews (SRs) of big data IEs and other measurement studies that innovatively use big data to measure and validate any development outcomes. This study also explores the sectoral and geographical spread of big data's use in international development. This map includes studies written in English and published between 2005 and 2019, regardless of the target country's income level or population's status. We provide detailed breakdowns on the map for different country income classifications, fragile contexts and population characteristics. From the initial list of 17,393 studies we arrived at a final list of 437 studies, which included 48 IEs, 381 measurement studies and 8 SRs." (Executive summary)
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"Gender equality and the empowerment of women and girls, one of the Sustainable Development Goals, is a highly complex and challenging undertaking. We must address multiple issues—discrimination, violence, education, employment, economic resources, and technology—and work across economic sectors
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, from agriculture to financial services. Achieving gender equality will require significant amounts of accurate data about the situations and struggles of women and girls. Globally, however, there is a major gap in data that is disaggregated by sex, and this gap often renders women’s societal, cultural, and economic contributions and obstacles practically invisible. It can also exacerbate existing gender divides, feeding and reinforcing biases in social programs, access to financial and other services, economic opportunities, and even development programs designed to address gender inequality. Part of the solution may be in the form of big data, which, if used effectively, can provide the volume of data needed to portray women and their situations accurately, which in turn can inform the creation of evidence-based solutions." (Page 1)
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"• Data impact assessments determine the potential benefits and risks associated with data management. They are a critical component of responsible data management, but are often overlooked.
• There are a wide variety of approaches to data impact assessments. Selecting the right assessment for a
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given data management activity can minimise the risk and maximise the benefit to affected people, humanitarians and other stakeholders.
• Applicable laws and regulations, internal policies, the context in which data management will take place and other factors determine which assessment(s) should be applied to a data management activity.
• Data impact assessments should be conducted before and during data management activities in order to inform project planning and design. Activities should be redesigned or cancelled if the foreseeable risks of data management outweigh the intended benefits." (Key takeaways)
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"El objetivo de esta investigación es el desarrollo de una guía de recolección de datos de migración con el fin entender mejor las características de la población migrante. Las recomendaciones de este trabajo surgen a partir de tres casos de estudio en ciudades/regiones fronterizas: Monterrey
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(México); Cúcuta (Colombia) y la Región Huetar Norte de Costa Rica. Este trabajo contribuye a identificar qué datos se producen sobre personas migrantes, quién los produce y cómo se manejan. A través de la investigación, se puede observar que los datos migratorios que se producen son principalmente de entradas/salidas, y hay una falta de recopilación y/o publicación de datos sobre las poblaciones migrantes en cada país. Debido a esto se realiza una serie de recomendaciones y una guía para la recopilación y manejo de datos de personas migrantes, para señalar los datos que pueden ser útiles para la creación de políticas públicas de integración y asentamiento." (Resumen ejecutivo)
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"Invisible Women shows us how, in a world largely built for and by men, we are systematically ignoring half the population. It exposes the gender data gap - a gap in our knowledge that is at the root of perpetual, systemic discrimination against women, and that has created a pervasive but invisible
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bias with a profound effect on women's lives. Award-winning campaigner and writer Caroline Criado Perez brings together for the first time an impressive range of case studies, stories and new research from across the world that illustrate the hidden ways in which women are forgotten, and the impact this has on their health and well-being. From government policy and medical research, to technology, workplaces, urban planning and the media, Invisible Women reveals the biased data that excludes women. In making the case for change, this powerful and provocative book will make you see the world anew." (Back cover)
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"This report shows how governments in developing countries can enhance their use of data to provide better services to citizens. It also shows how the business sector is starting to capitalize on data for competitive advantage. For citizens, the report argues that new tools can allow them to take mo
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re control of personal data and benefit more directly from its value. For the World Bank Group and its development partners, the report contains plentiful examples of how big data and open data can be harnessed for better development outcomes. But challenges loom. The growth of data platforms is changing the profile of competitive markets and business models, away from subscriber-funded networks to advertising-funded services. This has important implications for how infrastructure is financed. In this evolving context, we must ensure that data is used for inclusion, not exclusion, and for enhanced privacy, not greater threats to security. The final chapter of the report looks at data policies for the digital economy and how conflicting demands can be reconciled. At a time when governments around the world are reviewing existing data policies, and writing new ones, such as the European Union’s General Data Protection Regulation, this report seeks to contribute to the debate." (Foreword)
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"This guide categorises data-driven campaigning methods to loosely reflect how value is created along the data pipeline, from acquisition (asset), to analysis (intelligence) to application (influence)." (Page 3)
"Data has become a social and political issue because of its capacity to reconfigure relationships between states, subjects, and citizens. This book explores how data has acquired such an important capacity and examines how critical interventions in its uses in both theory and practice are possible.
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Data and politics are now inseparable: data is not only shaping our social relations, preferences and life chances but our very democracies. Expert international contributors consider political questions about data and the ways it provokes subjects to govern themselves by making rights claims. Concerned with the things (infrastructures of servers, devices, and cables) and language (code, programming, and algorithms) that make up cyberspace, this book demonstrates that without understanding these conditions of possibility it is impossible to intervene in or to shape data politics." (Publisher description)
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"A decade ago, open data was more or less just an idea, emerging as a rough point of consensus for action among pro-democracy practitioners, internet entrepreneurs, open source advocates, civic technology developers, and open knowledge campaigners. Calls for “open data now” offered a powerful cr
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itique of the way in which governments and other institutions were hoarding valuable data paid for by taxpayers – data that if made accessible, could be reused in a myriad of different ways to bring social and economic benefits and democratic change. Ten years on, open data is much more than just an idea. First, it was a movement, and then a label applied to vast quantities of data from genomics and geospatial data to land registers, contracting, and parliamentary voting. Today, it’s a term found on government portals, in global policy documents, and in job descriptions. Thousands of businesses around the world owe their existence or their growth to the release of open government data, and hundreds of civil society organisations have embraced open data as a key element of their social change toolkit. For a while, it may have been possible to identify a cohesive open data movement united by shared interests, working simply to gain access to more data and establishing the principle that government data should be open. However, as the movement has evolved, stakeholders have turned their focus to linking data use to specific needs and to questions of how to quantify the return on investment in advancing open data. Within this fast growing and organic open data movement, an ever-increasing number of networks and communities of practice have become more diverse, fluid, and cross-sectoral. So what is the open data movement today? What has it achieved over the last decade? Answering these questions is at the core of this publication. It is a collective effort to explore what we can learn from the past, to identify how to build on the investments made to date, and to look at how open data policy and practice have started to address challenges such as mainstreaming and sectorisation. Exploring these questions is not just important for historical purposes. It can yield important insights on how best to move forward. This publication is also an invitation to identify the issues that may sustain this broad coalition into the future." (Introduction)
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"This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data vis
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ualization in an honest and effective way. Data Visualization builds the reader's expertise in ggplot, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective "small multiple" plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible." (Publisher description)
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