The new issue of Harmonization: Newsletter on Survey Data Harmonization in the Social Sciences is now available. Harmonization is a product of the Harmonization team, and organized by Cross-national Studies: Interdisciplinary Research and Training program (CONSIRT.osu.edu). Working together, we share news and communicate with the growing community of scholars, institutions and government agencies who work on harmonizing social survey data and other projects with similar focus.

Articles in this issue:

Quality of Survey Data: How to Estimate It and Why It Matters by Melanie Revilla, Willem Saris and the Survey Quality Predictor (SQP) team

Estimation Bias due to Duplicated Observations: A Monte Carlo Simulation by Francesco Sarracino and Małgorzata Mikucka

Survey Weights as Indicators of Data Quality by Marta Kołczyńska, Marcin W. Zieliński, and Przemek Powałko

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by Marta Kołczyńska, The Ohio State University and Polish Academy of Sciences

Data, according to the United Nations Statistical Commission, are “the physical representation of information in a manner suitable for communication, interpretation, or processing by human beings or by automatic means” (UNSC 2000: 6). In other words, for information to qualify as data, it needs to be usable. Usable survey data depends on the availability and the high-quality of documentation.

Survey documentation refers to information on when, where, how and by whom the study was conducted, including information on the type of the sampling, size of the sample, response rate, preparation of the questionnaire and other instruments, as well as pretesting, and fieldwork control. In the Internet age, this information should accompany the survey data set in the form of one or more documents electronically available for viewing and downloading.

The main goal of any statistical analysis using survey data is to draw inferences about the target population. The precondition is that the survey sample is representative for the population. Representativeness can be approached in different ways and met to different degrees.

The researcher ultimately has to decide whether a given survey sample is sufficiently representative to solve their research problem. This decision requires knowledge about sampling, including the sampling scheme, the sampling frame and, if such is the case, details of stratified samples or other methods. For researchers, additional aspects of the survey process, such as response rates and control of fieldwork, are also important to review in order to assess survey data quality.

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by J. Craig Jenkins, Kazimierz M. Slomczynski, and Joshua Kjerulf Dubrow

An upsurge in popularity is not necessarily a revolution.

The wealth of quantitative data—including data from cross-national survey projects, official governmental and nongovernmental organization (NGO) statistics, newspapers and electronic newswires, and a variety of Internet-based websites, blogs, and social media sites—has generated a large and growing empirically based literature on political behavior.

Yet, social scientists have only begun to use this wealth to its fullest capacity, as advances in computing infrastructures, methods, and Internet communication technologies create new opportunities for developing and integrating diverse types of information into social science data. Social science faces the challenge of “big data,” a new era of the quantification and analysis of political behavior on an unprecedented scope and scale.

Will it rise to this challenge?

We guest edited a special issue of the International Journal of Sociology addresses recent uses of “big data,” its multiple meanings, and the potential that this may have in building a stronger understanding of political behavior. In our introduction, “Political Behavior and Big Data,” we address recent uses of “big data,” its multiple meanings, and the potential that this may have in building a stronger understanding of political behavior.

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by Irina Tomescu-Dubrow and Kazimierz M. Slomczynski, Polish Academy of Sciences and CONSIRT

The Democratic Values and Protest Behavior: Data Harmonization, Measurement Comparability, and Multi-Level Modeling study is financed by the (Polish) National Centre of Science and supported by The Ohio State University. CONSIRT hosts the project in Poland. While there are a number of survey data harmonization projects that have informed our own, each with their own acronyms (Dubrow and Tomescu-Dubrow 2014), we have come to call this large-scale research, simply, the Harmonization Project.

To test this model we need data at both the individual- and the country-level that vary over time and across space. The Harmonization Project sets out to create comparable measurements of political protest, social values, and demographics via ex-post harmonization of variables from international survey projects and append them with macro-level variables from external sources such as the World Bank, OSCE, UN agencies, Transparency International, and others.

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by Joshua Kjerulf Dubrow, Polish Academy of Sciences and CONSIRT

This article gives a brief overview of ex post cross-national survey data harmonization (SDH) projects in the social sciences from the 1980s to the 2010s (see also Burkhauser and Lillard 2005; Granda, Wolf, and Hadorn 2010; Dubrow and Tomescu-Dubrow 2014).

There are two major types of SDH projects. One are large scale projects designed to produce data on a range of research topics with open research questions. They involve multiple institutions – including governments, and especially their financing – and large numbers of researchers and assistants. These projects produce harmonized data and corresponding user manuals, as well as publications on the use of these data for addressing substantive issues. The second type are projects designed by small research teams to answer specific pre-determined research questions. Here, harmonization is limited to the variables needed to answer the research questions. This article focuses on large-scale projects.

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Welcome to the website for the project “Democratic Values and Protest Behavior: Data Harmonization, Measurement Comparability, and Multi-Level Modeling in Cross-National Perspective”.

This project is a joint endeavour of the Institute of Philosophy and Sociology, Polish Academy of Sciences, and the Mershon Center for International Security Studies, The Ohio State University, and is financed by the Polish National Science Centre in the framework of the Harmonia grant competition (2012/06/M/HS6/00322).

In this website you can find out more about the project and the data, as well as the conferences and workshops. Visit links for information on cross-national research and related topics.

The Harmonization Project is part of CONSIRT Labs (Cross-national Studies: Interdisciplinary Research and Training program, of OSU and PAN). See this website for a list of members of CONSIRT Lab: Methodology of Survey Data Harmonization and selected resources.