The NIC.br Annual Workshop on Survey Methodology was conceptualized with the objective of promoting capacity-building on quantitative and qualitative approaches used for the production and usage of ICT-related statistics, enhancing the importance of solid and rigorous methods for data collection and use among the ICT data community.
The IX edition of this 4-day workshop will address the “Data for public statistics: Data Science, Big Data & Artificial Intelligence”, considering the importance of new sources of data for producing public statistics.
Taking into account the current scenario where massive amounts of data are being produced at fast rates, the days 1 and 2 aims to address the following questions: how can we leverage the potential of big data to improve data production? How is the data ecosystem reconfigured? Which approaches can be used to generate value from this data? What is the role of Data Science in this context? How can big data and artificial intelligence be used for decision-making and which are the challenges and barriers associated with these?.
Days 3 and 4 will also deliver the Short Course: “Quantitative Survey Sampling and Qualitative Sampling” aimed at introducing participants to both survey sampling and qualitative sampling and looking at why good quality sampling is important and how to implement it.
The workshop is composed by lectures and short courses that include interactive activities, practical examples and case studies. No fees are charged and all the course material will be provided at the course.
The workshop is conducted in English and no simultaneous translation service is provided.
Jan van den Brakel (Statistics Netherlands/Maastricht University)
National statistical institutes are under increasing pressure to reduce administration costs and response burden for the production of official statistics. This could potentially be accomplished by using large data sets - so called big data. However, there are problems that must be addressed when using such data source for the production of official statistics. In these sessions, two different research lines will be presented on how big data sources can be used in the production of official statistics. They will be illustrated with research results from projects conducted at Statistics Netherlands. The first approach to be presented is to combine big data sources with sample data in a model-based inference approach. This implies that big-data sources are used as covariates in models used for small area estimation, for example in an area level model where cross-sectional correlation between areas are used to improve the effective sample size of the domains. The second approach is to use big data sources as a primary data source for the compilations of official statistics. This can be considered if a big data source covers the intended target population and not suffer to much from under- and over-coverage, e.g. the use of satellite and areal images for deriving statistical information on land use. In most cases, however, adjustments for selection bias are required.
Jan van den Brakel (Statistics Netherlands/Maastricht University)
National statistical institutes are under increasing pressure to reduce administration costs and response burden for the production of official statistics. This could potentially be accomplished by using large data sets - so called big data. However, there are problems that must be addressed when using such data source for the production of official statistics. In these sessions, two different research lines will be presented on how big data sources can be used in the production of official statistics. They will be illustrated with research results from projects conducted at Statistics Netherlands. The first approach to be presented is to combine big data sources with sample data in a model-based inference approach. This implies that big-data sources are used as covariates in models used for small area estimation, for example in an area level model where cross-sectional correlation between areas are used to improve the effective sample size of the domains. The second approach is to use big data sources as a primary data source for the compilations of official statistics. This can be considered if a big data source covers the intended target population and not suffer to much from under- and over-coverage, e.g. the use of satellite and areal images for deriving statistical information on land use. In most cases, however, adjustments for selection bias are required.
OECD Measuring the Digital Transformation and Going Digital Toolkit
Daniel Ker (Organisation for Economic Co-operation and Development)
"Measuring the Digital Transformation: A Roadmap for the Future" (https://oe.cd/mdt) was launched by the OECD at the Going Digital Summit in March 2019. It provides new insights into the state of the digital transformation by mapping indicators across a range of areas – from education and innovation, to trade and economic and social outcomes – against current digital policy issues, as presented in the accompanying publication "Going Digital: Shaping Policies, Improving Lives" (https://oe.cd/gdreport). In so doing, it identifies gaps in the current measurement framework, assesses progress made towards filling these gaps and sets-out a forward-looking measurement roadmap. The goal is to expand the evidence base, as a means to lay the ground for more robust policies for growth and well-being in the digital era.
Alongside these, the "Going Digital Toolkit" (https://www.oecd.org/going-digital-toolkit) helps countries assess their state of digital development and formulate policy strategies and approaches in response. Data exploration and visualisation are key features. The Going Digital Toolkit is structured along the 7 policy dimensions of the Going Digital Integrated Policy Framework, which cuts across policy areas to help ensure a whole-of-economy and society approach to realising the promises of digital transformation for all.
Make Measurement Matter: Leveraging Big Data and AI for Monitoring and Promoting Sustainable Human Development.
Emmanuel Letouzé (DataPop Alliance)
A decade into the “Data Revolution”, many questions remain about the real potential of ‘Big Data’, and increasingly AI, to meaningfully contribute to sustainable human development, including the monitoring and promotion of the SDGs. Many papers and pilots have showed how analysis of those ‘digital breadcrumbs’, most of which collected and controlled by private companies, could shed light on human processes and outcomes at very fine levels of temporal and geographic granularities. But to date there are no systems nor standards developed and even less deployed to unlock this potential at scale, safely, and ethically. In a ‘post-truth’ age there is also a need to reconsider commonly held assumptions about the role and limitations of measurement in shaping decisions; often data and facts do not seem to matter very much. And yet making measurement matter for development still seems like a simple and powerful way to foster progress. How can this be done, in the age of Big Data and AI? What does and will it take in the next decade and beyond for the ‘data generations’—these children and teenagers growing in a dataified world? Based on the experience and perspectives of Data-Pop Alliance, OPAL ("Open Algorithms"), and others, this presentation will seek to provide context, suggest options, and foster discussions on how Big Data and AI may help monitor and promote sustainable human development.
Make Measurement Matter: Leveraging Big Data and AI for Monitoring and Promoting Sustainable Human Development.
Emmanuel Letouzé (DataPop Alliance)
A decade into the “Data Revolution”, many questions remain about the real potential of ‘Big Data’, and increasingly AI, to meaningfully contribute to sustainable human development, including the monitoring and promotion of the SDGs. Many papers and pilots have showed how analysis of those ‘digital breadcrumbs’, most of which collected and controlled by private companies, could shed light on human processes and outcomes at very fine levels of temporal and geographic granularities. But to date there are no systems nor standards developed and even less deployed to unlock this potential at scale, safely, and ethically. In a ‘post-truth’ age there is also a need to reconsider commonly held assumptions about the role and limitations of measurement in shaping decisions; often data and facts do not seem to matter very much. And yet making measurement matter for development still seems like a simple and powerful way to foster progress. How can this be done, in the age of Big Data and AI? What does and will it take in the next decade and beyond for the ‘data generations’—these children and teenagers growing in a dataified world? Based on the experience and perspectives of Data-Pop Alliance, OPAL ("Open Algorithms"), and others, this presentation will seek to provide context, suggest options, and foster discussions on how Big Data and AI may help monitor and promote sustainable human development.
Use of Computational Tools to Support Planning and Policy
Johannes Bauer (Michigan State University)
The availability of rich and detailed data has greatly improved the ability of policy analysts and policy makers to develop better policy. Big data can also be utilized to improve the design and implementation of policies intended to advance fixed and wireless connectivity and to overcome second and third generation digital divides. One weakness of reliance on big data for purposes of policy design is that is inherently reflects past arrangements and relationships between players in the ICT industries. In as far as policy seeks to create a different future, it needs to augment the insights from big data analytics. One approach is computational modeling, which can help explore and evaluate different courses of action and their effects on social and economic outcomes. Examples that take advantage of increased data availability and computational power include scenario building, agent-based modeling, computer simulations. Designed for practitioners, the session will discuss these issues and illustrate the uses and limitations of computational methods for current policy issues (e.g., network neutrality, 5G deployment).
Quantitative Survey Sampling and Qualitative Sampling
Pamela Campanelli (The Survey Coach)
Do you have the right sampling design for your quantitative survey or for your qualitative focus groups or depth interviews? A poor sampling design can make or break a study. This course introduces participants to both survey sampling and qualitative sampling; looking at why good quality sampling is important and how to implement it. The course contains lots of practical advice and many workshops to put theory into practice. On the quantitative side, it does make use of mathematics and statistics, but it has been designed for all participants (those with little or no statistical background through to those who use statistics regularly). The topics covered include: types of samples (probability versus non-probability), how to construct a ‘sampling frame’, types of probability samples (e.g., simple random, systematic, stratified, multi-stage clustered, unequal probabilities of selection, probability proportional to size and flow sampling), what ‘sampling error’ is, the role of sampling error in confidence intervals, how to determine sample size, how a complex sampling design affects confidence intervals, issues with disproportionate designs and the impact on weighting and a brief introduction to weighting. On the qualitative side, the topics covered include: different types of samples (convenience, purposive, theoretical, heterogeneous and homogeneous), sampling units, sample size, and special tips for focus group samples.
10:45 - 11:00
Coffee-break
11:00 - 12:30
Quantitative Survey Sampling and Qualitative Sampling
Pamela Campanelli (The Survey Coach)
Do you have the right sampling design for your quantitative survey or for your qualitative focus groups or depth interviews? A poor sampling design can make or break a study. This course introduces participants to both survey sampling and qualitative sampling; looking at why good quality sampling is important and how to implement it. The course contains lots of practical advice and many workshops to put theory into practice. On the quantitative side, it does make use of mathematics and statistics, but it has been designed for all participants (those with little or no statistical background through to those who use statistics regularly). The topics covered include: types of samples (probability versus non-probability), how to construct a ‘sampling frame’, types of probability samples (e.g., simple random, systematic, stratified, multi-stage clustered, unequal probabilities of selection, probability proportional to size and flow sampling), what ‘sampling error’ is, the role of sampling error in confidence intervals, how to determine sample size, how a complex sampling design affects confidence intervals, issues with disproportionate designs and the impact on weighting and a brief introduction to weighting. On the qualitative side, the topics covered include: different types of samples (convenience, purposive, theoretical, heterogeneous and homogeneous), sampling units, sample size, and special tips for focus group samples.
12:30 - 13:30
Lunch
13:30 - 14:45
Quantitative Survey Sampling and Qualitative Sampling
Pamela Campanelli (The Survey Coach)
Do you have the right sampling design for your quantitative survey or for your qualitative focus groups or depth interviews? A poor sampling design can make or break a study. This course introduces participants to both survey sampling and qualitative sampling; looking at why good quality sampling is important and how to implement it. The course contains lots of practical advice and many workshops to put theory into practice. On the quantitative side, it does make use of mathematics and statistics, but it has been designed for all participants (those with little or no statistical background through to those who use statistics regularly). The topics covered include: types of samples (probability versus non-probability), how to construct a ‘sampling frame’, types of probability samples (e.g., simple random, systematic, stratified, multi-stage clustered, unequal probabilities of selection, probability proportional to size and flow sampling), what ‘sampling error’ is, the role of sampling error in confidence intervals, how to determine sample size, how a complex sampling design affects confidence intervals, issues with disproportionate designs and the impact on weighting and a brief introduction to weighting. On the qualitative side, the topics covered include: different types of samples (convenience, purposive, theoretical, heterogeneous and homogeneous), sampling units, sample size, and special tips for focus group samples.
14:45 - 15:00
Coffee-break
15:00 - 16:30
Quantitative Survey Sampling and Qualitative Sampling
Pamela Campanelli (The Survey Coach)
Do you have the right sampling design for your quantitative survey or for your qualitative focus groups or depth interviews? A poor sampling design can make or break a study. This course introduces participants to both survey sampling and qualitative sampling; looking at why good quality sampling is important and how to implement it. The course contains lots of practical advice and many workshops to put theory into practice. On the quantitative side, it does make use of mathematics and statistics, but it has been designed for all participants (those with little or no statistical background through to those who use statistics regularly). The topics covered include: types of samples (probability versus non-probability), how to construct a ‘sampling frame’, types of probability samples (e.g., simple random, systematic, stratified, multi-stage clustered, unequal probabilities of selection, probability proportional to size and flow sampling), what ‘sampling error’ is, the role of sampling error in confidence intervals, how to determine sample size, how a complex sampling design affects confidence intervals, issues with disproportionate designs and the impact on weighting and a brief introduction to weighting. On the qualitative side, the topics covered include: different types of samples (convenience, purposive, theoretical, heterogeneous and homogeneous), sampling units, sample size, and special tips for focus group samples.
09:00 - 10:45
Quantitative Survey Sampling and Qualitative Sampling
Pamela Campanelli (The Survey Coach)
Do you have the right sampling design for your quantitative survey or for your qualitative focus groups or depth interviews? A poor sampling design can make or break a study. This course introduces participants to both survey sampling and qualitative sampling; looking at why good quality sampling is important and how to implement it. The course contains lots of practical advice and many workshops to put theory into practice. On the quantitative side, it does make use of mathematics and statistics, but it has been designed for all participants (those with little or no statistical background through to those who use statistics regularly). The topics covered include: types of samples (probability versus non-probability), how to construct a ‘sampling frame’, types of probability samples (e.g., simple random, systematic, stratified, multi-stage clustered, unequal probabilities of selection, probability proportional to size and flow sampling), what ‘sampling error’ is, the role of sampling error in confidence intervals, how to determine sample size, how a complex sampling design affects confidence intervals, issues with disproportionate designs and the impact on weighting and a brief introduction to weighting. On the qualitative side, the topics covered include: different types of samples (convenience, purposive, theoretical, heterogeneous and homogeneous), sampling units, sample size, and special tips for focus group samples.
10:45 - 11:00
Coffee-break
11:00 - 12:30
Quantitative Survey Sampling and Qualitative Sampling
Pamela Campanelli (The Survey Coach)
Do you have the right sampling design for your quantitative survey or for your qualitative focus groups or depth interviews? A poor sampling design can make or break a study. This course introduces participants to both survey sampling and qualitative sampling; looking at why good quality sampling is important and how to implement it. The course contains lots of practical advice and many workshops to put theory into practice. On the quantitative side, it does make use of mathematics and statistics, but it has been designed for all participants (those with little or no statistical background through to those who use statistics regularly). The topics covered include: types of samples (probability versus non-probability), how to construct a ‘sampling frame’, types of probability samples (e.g., simple random, systematic, stratified, multi-stage clustered, unequal probabilities of selection, probability proportional to size and flow sampling), what ‘sampling error’ is, the role of sampling error in confidence intervals, how to determine sample size, how a complex sampling design affects confidence intervals, issues with disproportionate designs and the impact on weighting and a brief introduction to weighting. On the qualitative side, the topics covered include: different types of samples (convenience, purposive, theoretical, heterogeneous and homogeneous), sampling units, sample size, and special tips for focus group samples.
12:30 - 13:30
Lunch
13:30 - 14:45
Quantitative Survey Sampling and Qualitative Sampling
Pamela Campanelli (The Survey Coach)
Do you have the right sampling design for your quantitative survey or for your qualitative focus groups or depth interviews? A poor sampling design can make or break a study. This course introduces participants to both survey sampling and qualitative sampling; looking at why good quality sampling is important and how to implement it. The course contains lots of practical advice and many workshops to put theory into practice. On the quantitative side, it does make use of mathematics and statistics, but it has been designed for all participants (those with little or no statistical background through to those who use statistics regularly). The topics covered include: types of samples (probability versus non-probability), how to construct a ‘sampling frame’, types of probability samples (e.g., simple random, systematic, stratified, multi-stage clustered, unequal probabilities of selection, probability proportional to size and flow sampling), what ‘sampling error’ is, the role of sampling error in confidence intervals, how to determine sample size, how a complex sampling design affects confidence intervals, issues with disproportionate designs and the impact on weighting and a brief introduction to weighting. On the qualitative side, the topics covered include: different types of samples (convenience, purposive, theoretical, heterogeneous and homogeneous), sampling units, sample size, and special tips for focus group samples.
14:45 - 15:00
Coffee-break
15:00 - 16:30
Quantitative Survey Sampling and Qualitative Sampling
Pamela Campanelli (The Survey Coach)
Do you have the right sampling design for your quantitative survey or for your qualitative focus groups or depth interviews? A poor sampling design can make or break a study. This course introduces participants to both survey sampling and qualitative sampling; looking at why good quality sampling is important and how to implement it. The course contains lots of practical advice and many workshops to put theory into practice. On the quantitative side, it does make use of mathematics and statistics, but it has been designed for all participants (those with little or no statistical background through to those who use statistics regularly). The topics covered include: types of samples (probability versus non-probability), how to construct a ‘sampling frame’, types of probability samples (e.g., simple random, systematic, stratified, multi-stage clustered, unequal probabilities of selection, probability proportional to size and flow sampling), what ‘sampling error’ is, the role of sampling error in confidence intervals, how to determine sample size, how a complex sampling design affects confidence intervals, issues with disproportionate designs and the impact on weighting and a brief introduction to weighting. On the qualitative side, the topics covered include: different types of samples (convenience, purposive, theoretical, heterogeneous and homogeneous), sampling units, sample size, and special tips for focus group samples.
Regional Center for Studies on the Development of the Information Society under the auspices of UNESCO (Cetic.br)
Alexandre Barbosa
Alexandre Fernandes Barbosa leads several information and communication technologies (ICT) surveys and research projects on the socioeconomic implications of ICT in Brazil. He is responsible for conducting nationwide ICT surveys for the production of ICT-related statistics on the access to and use of ICTs in different segments of society and capacity building in survey methodologies in Latin América and lusophone countries of Africa. Mr Barbosa is also the Chair of the Expert Group on ICT Households indicators from the International Telecommunications Union (ITU). Mr Barbosa holds a PhD degree in Business Administration from Getulio Vargas Foundation (Brazil), a Master Degree in Business Administration from Bradford University (UK), an MSc Degree in Computer Science from Federal University of Minas Gerais (Brazil) and a BSc Degree in Electrical Engineering from Catholic University (Brazil). He has also conducted postdoctoral research at HEC Montreal (Canada).
Instituto Brasileiro de Opinião Pública - Inteligência
Bernardo Canedo
Bernardo Canedo Graduated in Economics, Bernardo has a solid background in CRM programs as founder of IBOPE DTM, established in 2004 and acquired by IBOPE Group in 2013. Before that, spent over 10 years as an executive at major retail banks. His last position was Relationship Marketing Director at Banco Santander.
Caitlin Sampaio Mulholland has a PhD and MSc degree in Civil Law at the Rio de Janeiro State University - UERJ. She is an associate professor at the Pontifical Catholic University of Rio de Janeiro (PUC-Rio) Law Department . She is the Dean of Students at PUC-Rio Law Department. She is professor of the post-graduation program in Constitutional Law and Political Theory at PUC-Rio. She is a researcher at the Legalite Center, with emphasis in the areas of Artificial Intelligence and Law, Data Protection and Privacy Law. The most frequent themes of her scientific production are: technology, right of privacy, fundamental rights, civil liability and contracts. She is the author of the books "Civil liability and causality presumption" and "Internet and Contracts: a panorama on consumer electronic contractual relations". She is a member of the Civil Law Commission of the Brazilian Bar Association, Rio de Janeiro Branch. Associated with the Brazilian Institute of Civil Law - IBDCivil and the Association Henri Capitant des Amis de la Culture Juridique Française. Associate Founder of the Brazilian Institute of Civil Liability Studies (IBERC). Researcher at INCT Proprietas.
Organisation for Economic Co-operation and Development
Daniel Ker
Daniel Ker is co-author of “Measuring the Digital Transformation: a Roadmap for the future”, which the OECD launched, along with an accompanying online Toolkit, at its “Going Digital” Summit in March 2019. Together, these enable a holistic assessment of the digital transformation across OECD and BRIICS countries, as well as identifying areas for further development and setting out a roadmap for addressing measurement needs. Prior to this, Daniel lead the team responsible for the R&D statistics and survey framework at the OECD, having previously been responsible for work to capitalise R&D in the UK National Accounts and co-deputy director of Public Sector statistics at the UK Office for National Statistics.
Danny Pfeffermann is the National Statistician and Head of the Central Bureau of Statistics of Israel. He is Professor Emeritus of Statistics at the Hebrew University of Jerusalem, Israel, and Professor of Statistics at Southampton University, UK. His main research areas are analytic inference from complex sample surveys, small area estimation, seasonal adjustment and trend estimation and more recently, observational studies and non-ignorable nonresponse. Danny published over than 70 articles in refereed journals and co-edited the two-volume handbook “Sample Surveys”, published by North-Holland. He was President of the Israel Statistical Society and of the International Association of Survey Statisticians (IASS); he is a Fellow of the American Statistical Association and an elected member of the International Statistical Institute. He is the recipient of the 2011 Waksberg award for “outstanding contributions to survey methodology”, the 2014 recipient of the Hansen Lecture award, the 2015 recipient of the S.N. Roy Memorial Lecture award, the 2017 recipient of the West medal, awarded by the UK Royal Statistical Society and the 2018 recipient of the Julius Shiskin Award for unusually original and important contributions in the development of economic statistics, sponsored by the Washington Statistical Society and the American Statistical Association.
Demi Getschko holds BSc, MSc, and PhD, degrees in Electronic Engineering from the University of Sao Paulo in Brazil. He is an advisor to the Brazilian Internet Steering Committee (CGI.br), CEO of the Brazilian Network Information Center (NIC.br) and an Associate Professor at the Pontifical Catholic University of São Paulo (PUC-SP). He was a member of the Board of Directors of the Internet Corporation for Assigned Names and Numbers (ICANN) by the Country Code Names Supporting Organization (ccNSO). In April 2014 he was an inductee at the Internet Hall of Fame under the category "Global Connectors", in a ceremony held in Hong Kong. In July of the same year, he was awarded with the “Cristina Tavares" prize of the Brazilian Computer Society. In December, on the day of the Engineer, he received from the Engineers' Union, in the State of São Paulo, the "Personality of Technology 2014" award, under the category "Internet." In May 2016 he was admitted to the Order of Merit of Communications, at the "Officer's Degree" as a form of recognition of his services to Communications.
Escola Nacional de Ciências Estatísticas / Instituto Brasileiro de Geografia e Estatística
Denise Britz do Nascimento Silva
Denise Britz do N. Silva is Principal Researcher and former director of the National School of Statistical Sciences (ENCE) from the Brazilian Institute of Geography and Statistics (IBGE). Has also worked as a Principal Methodologist for the Office for National Statistics (ONS-UK) and as a lecturer at the University of Southampton. She completed her PhD in Statistics at the University of Southampton and has an MSc and a BSc in Statistics. She has extensive experience in teaching at graduate and undergraduate levels as well as professional development courses, and has been working as a survey statistician at IBGE for more than 30 years. Her main areas of interest are survey methods, statistical modelling for the social sciences, small area estimation and time series analysis. She is president-elect of the International Association of Survey Statisticians (IASS) and is an elected member of the International Statistical Institute (ISI).
Web Technology Study Center (Ceweb.br)/ Pontifical Catholic University of São Paulo
Diogo Cortiz
Diogo Cortiz is Researcher at Web Technology Study Center (Ceweb.br) and Professor at Pontifical Catholic University of São Paulo. He holds a PhD in Technologies of Intelligence and Digital Design from Pontifical Catholic University of São Paulo with PhD Fellowship form Universite Paris I – Pantheon-Sorbonne. He completed a postdoctoral research on Virtual Reality and Creative Technologies in the Laboratory of Artificial Intelligence and Creative Computing at the University of Salamanca, Spain. He has research in the fields of design and emerging technologies.
Dr Emmanuel Letouzé is the Director of Data-Pop Alliance, a global coalition on Big Data, Artificial Intelligence and development created in 2013 by the Harvard Humanitarian Initiative (HHI), MIT Media Lab and Overseas Development Institute (ODI), joined by Flowminder in 2016. He is a co-founder and serves as Program Director of the Open Algorithms (OPAL) project and is a Visiting Scholar at MIT Media Lab and a Connection Science Fellow at MIT, as well as a Research Associate at ODI. He wrote UN Global Pulse's White Paper "Big Data for Development” in 2011, where he worked as Senior Development Economist, and has since then focused on data and technology’s applications and implications for development, governance, poverty, inequality, social cohesion, as well as ethics and privacy. He worked as a Development Economist for UNDP in New York (2006-09) on fiscal policy, post-conflict recovery and migration, and in Hanoi, Vietnam, for the French Ministry of Finance as a technical assistant in public finance and official statistics (2000-04). He received a BA in Political Science and an MA in Applied Economics-Economic Demography from Sciences Po Paris, an MA in International Affairs-Economic Development from Columbia University, where he was a Fulbright Fellow, and a PhD in Demography from the University of California, Berkeley, where his dissertation focused on the use of Big Data for demo-economic research. He is also a political cartoonist for various media.
Fernanda Campagnucci is member of the public management career at São Paulo City Hall and, since 2013, has been implementing policies related to transparency, innovation, open government and digital transformation in the city. She served as Head of Integrity at the Comptroller General’s Office and coordinated the Open Government and Digital Transformation Initiative at the Education Department – Pátio Digital.
She has a postgraduate certificate in Transparency and Accountability by the University of Chile. Prior to that, she graduated in Communication Studies (Journalism) at the University of São Paulo, where she also obtained a Master’s Degree in Sociology of Education. She is pursuing a PhD student in Public Administration and Government at Fundação Getúlio Vargas (EAESP-FGV).
Fernanda is a former Open Government fellow at the Organization of American States (2015), Open Data Leader at the Open Data Institute (2016), and Government Fellow at the United Nations University Operating Unit on Policy-Driven Electronic Governance - UNU-EGOV (2018).
Iñigo Herguera is an Associate Professor in Economics at the Universidad Complutense de Madrid (Spain). His recent research and advisory activities relate to ICT/Telecommunications development and regulatory issues. Iñigo has been Director at the Spanish Telecom Regulatory Authority (CNMC) and has been for a number of years Chair of Expert Group of ICT/Telecom Indicators in the International Telecommunications Union (ITU) as well as Chair of the Benchmarking Expert Group in the Board of European Regulators for Electronic Communications (BEREC) where he focused on the design of indicators on ICT/telecom for monitoring regulation and the development of ICT worldwide. He participates regularly in international expert groups regarding telecommunications, regulation and indicators. Prof. Herguera has advised numerous public and private organizations on issues related on competition policy: abuse of dominance and damages after collusion agreements and M&A; telecom regulation and design of forward markets. As ITU consultant he has advised several telecom regulatory authorities on the design and implementation of data collection and exploitation systems (Jamaica, Israel, Mexico and Oman). He has published in international journals on imperfect competition and quality provision, trade policy, analysis of different aspects of the regulation of the telecom industry as well as on adoption models of digital services. Iñigo Herguera received the Licenciado Degree in Economics by the Universidad Autonoma de Madrid (Spain), Diplom in European Studies by the Univeristaet Saarlandes (Germany) and PhD in Economics by the European University Institute (Italy). He is a visiting Professor on Regulation at the Barcelona Graduate School of Economics and has lectured in the Universidad Pompeu Fabra (Spain), Universidad Carlos III de Madrid and Universidad de Baja California (Mexico).
Jan van den Brakel is a Senior Statistician at the Methodology Department of Statistics Netherlands and external professor of Survey Methodology at Maastricht University, Department of Quantitative Economics. He studied Biometrics at Wageningen University. His PhD; Design and analysis of experiments in embedded in complex sample designs, is based on research and consultancy work at Statistics Netherlands and Rotterdam University. His research interests are sampling theory, design and analysis of experiments, inference methods for mixed-mode surveys, small area estimation, and time series methods. He is particularly interested in applying these methods in the context of measuring effects of survey process redesigns, model-based inference for official statistics and the use of non-probability data for official statistics.
Johannes M. Bauer is the Quello Chair for Media and Information Policy and the Chairperson of the Department of Media and Information at Michigan State University (MSU). He is trained as an engineer and social scientist with MA and PhD degrees from the Vienna University of Economics, Austria. His research focuses on current issues of media and information policy, such as network neutrality, overcoming digital divides, innovation in 5G wireless services, and generally the design of public interest technology. He uses qualitative and quantitative methods in his work, including computational approaches to policy analysis. His work has been funded by the U.S. National Science Foundation (NSF) and international organizations. Dr. Bauer has served as an advisor to public and private sector organizations in North and South America, Europe, and Asia. His most recent book, the Handbook on the Economics of the Internet (co-edited with Professor Michael Latzer at the University of Zurich), was published in 2016 by Edward Elgar. Dr. Bauer has held visiting professorships at the Technical University of Delft, Netherlands (2000-2001), the University of Konstanz, Germany (Summer 2010), and the University of Zurich, Switzerland (2012).
Dr Pamela Campanelli is a Survey Methods Consultant, Chartered Statistician, Chartered Scientist, and Fellow of the Academy of Social Sciences. She received her Ph.D. in statistics from the London School of Economics, and an M.A. in survey research methods and B.A. in psychology from the University of Michigan. Prior to becoming an independent consultant, she was a Research Associate at the University of Michigan, a Survey Statistician at the U.S. Bureau of the Census, Chief Research Officer at the UK Institute for Social and Economic Research at the University of Essex, and a Research Director at the Survey Methods Centre at the National Centre for Social Research, London. Her main interests and publications are in the study of survey error and survey data quality issues, with special emphasis on questionnaire design, question testing strategies, survey sampling and survey analysis. She regularly teaches short courses on various survey topics for universities, government departments, as well as various other institutions and businesses. She is based in the UK, but regularly teaches courses around the world and is so pleased to be teaching again for NIC.br.
Escola Nacional de Ciências Estatísticas / Instituto Brasileiro de Geografia e Estatística
Pedro Luis Nascimento Silva
Pedro Luis do Nascimento Silva was the President of the International Statistical Institute 2015-2017, and is Principal Researcher at the National School of Statistical Sciences (ENCE) of the Brazilian Institute of Geography and Statistics (IBGE). PhD. in Social Statistics (University of Southampton, 1996), Pedro’s main research interests are survey and sampling methodology applied to household and business surveys, as well as the analysis of survey data.
Useful Information
TRAVEL RECOMMENDATIONS
Vaccination against yellow fever is recommended for international travellers visiting any area in the state of São Paulo. Please check your country’s legislation before travelling. Additionally, please refer to: https://www.who.int/countries/bra/en/.