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Quality & Quantity

, Volume 50, Issue 4, pp 1449–1467 | Cite as

The rise of cross-national survey data harmonization in the social sciences: emergence of an interdisciplinary methodological field

  • Joshua Kjerulf Dubrow
  • Irina Tomescu-Dubrow
Article

Abstract

Cross-national survey data harmonization combines surveys conducted in multiple countries and across many time periods into a single, coherent dataset. Methodologically, ex post survey data harmonization is especially complex because it combines projects that were not specifically designed to be comparable. We examine the institutional and intellectual history of nine large scale ex post survey data harmonization (SDH) projects in the social sciences from the 1980s to the 2010s. An interdisciplinary methodological field of SDH slowly emerges, facilitated in part by a partnership between academia and government and from the coordinated contributions of social scientists, survey methodologists and computer scientists. While there has been a learning process, it is in terms of accumulated practicalities, and not with the coordination or institutional apparatus one would expect from a 30 year effort.

Keywords

Harmonization Surveys Methodology Cross-national Interdisciplinary 

Notes

Acknowledgements

This work is supported by the project “Democratic Values and Protest Behavior: Data Harmonization, Measurement Comparability, and Multi-Level Modeling in Cross-National Perspective”, funded by the National Science Centre, Poland, under the grant number 2012/06/M/HS6/00322. We thank Kazimierz M. Slomczynski and Marta Kolczynska for their comments on an earlier draft, and Dean Lillard for advice on the citation of harmonized data.

References

  1. Balsiger, P.W.: Supradisciplinary research practices: history, objectives and rationale. Futures 36, 407–421 (2004)CrossRefGoogle Scholar
  2. Börsch-Supan, A., Martina, B., Hunkler, C., Kneip, T., Korbmacher, J., Malter, F., Schaan, B., Stuck, S., Zuber, S., On Behalf of the SHARE Central Coordination Team: Data resource profile: the survey of health, ageing and retirement in Europe (SHARE). Int. J. Epidemiol. (2013). doi: 10.1093/ije/dyt088 Google Scholar
  3. Burkhauser, R.V., Lillard, D.R.: The contribution and potential of data harmonization for cross-national comparative research, DIW Diskussionspapiere, No. 486. http://www.econstor.eu/bitstream/10419/18337/1/dp486.pdf (2005). Accessed 12 Feb 2014
  4. CEPS/INSTEAD: http://www.ceps.lu/?type=module&id=53 (2014). Accessed 13 Feb 2014
  5. CHINTEX: Final conference: harmonisation of surveys and data quality. https://www.destatis.de/DE/Methoden/Methodenpapiere/Chintex/ResearchResults/FinalConference/Einfuehrung.html (2003). Accessed 14 Feb 2014
  6. Classifications Newsletter: United Nations Statistics Division (UNSD) Number 27 (August). http://www.uis.unesco.org/Education/Documents/UNSD_newsletter_27e_ISCED.pdf (2011). Accessed 7 Feb 2014
  7. Cornell University User Package for the Cross-National Equivalent File (CNEF): http://www.human.cornell.edu/pam/research/centers-programs/german-panel/cnef.cfm (1970–2009). Accessed 11 Feb 2014
  8. Cross-National Equivalent File (CNEF): http://cnef.ehe.osu.edu/ (2014). Accessed 22 Feb 2014
  9. ČSDA: Program of Workshop on Harmonisation of Social Survey Data for Cross-National Comparison will be held in Prague on Tuesday 19th October http://archiv.soc.cas.cz/articles/cz/84/workshop.html (2010). Accessed 22 Feb 2014
  10. Doiron, D., Raina, P., Ferretti, V., L’Heureux, F., Fortier, I.: Facilitating collaborative research—implementing a platform supporting data harmonization and pooling. Norsk Epidemiologi 21(2), 221–224 (2012)CrossRefGoogle Scholar
  11. Dubrow, J.K.: Sociology and American Studies: A Case Study in the Limits of Interdisciplinarity. Am. Sociol. 42(4), 303–315 (2011)Google Scholar
  12. Dubrow, J.K., Kolczynska, M.: A quem pertence o estudo da democracia? Sociologia, ciência política e a promessa da interdisciplinaridade na Sociologia política desde 1945 (Who Owns the Study of Democracy? Sociology, Political Science, and the Interdisciplinary Promise of Political Sociology since 1945). Sociologias 17(38), 92–120 (2015)Google Scholar
  13. Ehling, M., Rendtel, U., et al.: Synopsis. Researh Results of Chintex - Summary and Conclusions. http://destatis.de/DE/Methoden/Methodenpapiere/Chintex/ResearchResults/Downloads/Synopsis.html (2006). Retrieved 15 Feb 2015
  14. Elias, P.: ‘Big Data’ and the social sciences—a perspective from the ESRC. http://www2.warwick.ac.uk/fac/soc/economics/research/centres/cage/events/conferences/peuk/peter_elias_big_data_and_the_social_sciences_pe_final.pdf (2014). Accessed 6 Feb 2014
  15. EPUNET: http://epunet.essex.ac.uk/view_news.php%3FID=36.html (2014). Accessed 13 Feb 2014
  16. EuroPanel Users Network: http://epunet.essex.ac.uk/echp.php.html (2014). Accessed 13 Feb 2014
  17. European Commission website: Consortium of household panels for European socio-economic research (CHER) http://ec.europa.eu/research/social-sciences/projects/010_en.html (2014). Accessed 13 Feb 2014
  18. European Community Household Panel (ECHP): http://epp.eurostat.ec.europa.eu/portal/page/portal/microdata/echp (2011). Accessed 18 Aug 2011
  19. European Union Statistics on Income and Living Conditions (EU-SILC): http://epp.eurostat.ec.europa.eu/portal/page/portal/microdata/eu_silc (2014). Accessed 13 Feb 2014
  20. EUROSTAT: Harmonised European time use surveys. Methodologies and working papers. http://epp.eurostat.ec.europa.eu/portal/page/portal/product_details/publication?p_product_code=KS-RA-08-014 (2009). Accessed 22 Feb 2014
  21. Fisher, K., Gershuny. J.: Multinational time use study. User’s guide and documentation. Version 6, 16 July (2013)Google Scholar
  22. Frick, J.R., Jenkins, S.P., Lillard, D.R., Lipps, O., Wooden, M.: The cross-national equivalent file (CNEF) and its member country household panel studies In: Schmollers Jahrbuch 127(4), 627–654. http://www.diw.de/documents/dokumentenarchiv/17/diw_01.c.77260.de/schmoller_frick_etal_2007.pdf (2007). Accessed 22 Feb 2014
  23. Friendly, M., Denis, D.: The early origins and development of the scatterplot. J. Hist. Behav. Sci. 41(2), 103–130 (2005)CrossRefGoogle Scholar
  24. Ganzeboom, H.B.G., Treiman, D.J.: Ascription and achievement after career entry. Paper presented at the 2000 meeting of the RC28 (2000)Google Scholar
  25. Ganzeboom, H.B.G., Treiman, D.J.: Three internationally standardised measures for comparative research on occupational status. In: Hoffmeyer-Zlotnik, J.H.P., Wolf, C. (eds.) Advances in cross-national comparison. A European working book for demographic and socio-economic variables, pp. 159–193. Kluwer Academic Press, New York (2003)CrossRefGoogle Scholar
  26. Gartner: Definition of big data. http://www.gartner.com/it-glossary/big-data/ (2014). Accessed 22 Feb 2014
  27. GESIS: An illustrated user guide to the CharmCats database for classifications and conversions. http://www.cessda.org/project/doc/D12.2c_An_illustrated_short_Usermanual_CharmCats_0.5.pdf (2009). Accessed 22 Feb 2014
  28. Granda, P., Blasczyk, E.: Data harmonization. In: Cross-cultural survey guidelines. http://ccsg.isr.umich.edu/pdf/13DataHarmonizationNov2010.pdf (2010). Accessed 7 Feb 2014
  29. Granda, P., Wolf, C., Hadorn, R.: Harmonizing survey data. In: Harkness, J.A., Braun, M., Edwards, B., Johnson, T.P., Lyberg, L., Mohler, P.P., Pennell, B.-E., Smith, T.W. (eds.) Survey Methods in Multinational, Multiregional, and Multicultural Contexts, pp. 315–334. Wiley, New York (2010)CrossRefGoogle Scholar
  30. Harmonised European time use surveys (HETUS): Introduction. https://www.h2.scb.se/tus/tus/introduction1.html (2014). Accessed 14 Feb 2014
  31. Harmonization of Cognitive Measures in Individual Participant Data and Aggregate Data Meta-Analysis. http://www.ncbi.nlm.nih.gov/books/NBK132553/pdf/TOC.pdf (2014). Accessed 22 Feb 2014
  32. Hoffmeyer-Zlotnik, J.H.P., Wolf, C.: Comparing demographic and socio-economic variables across nations: synthesis and recommendations. In: Hoffmeyer-Zlotnik, J.H.P., Wolf, C. (eds.) Advances in Cross-national Comparison: A European Working Book for Demographic and Socio-Economic Variables, pp. 389–406. Springer, New York (2003)CrossRefGoogle Scholar
  33. Hout, M., DiPrete, T.A.: What we have learned: RC28’s contributions to knowledge about social stratification. Res. Soc. Stratif. Mobil. 24(2006), 1–20 (2006)CrossRefGoogle Scholar
  34. International Stratification and Mobility File (ISMF): http://www.harryganzeboom.nl/ISMF/index.htm (2014). Accessed 22 Feb 2014
  35. Jacobs, J.A.: In Defense of Disciplines: Interdisciplinarity and Specialization in the Research University. University of Chicago Press, Chicago (2014)Google Scholar
  36. Lee, R.M.: The secret life of focus groups: Robert Merton and the diffusion of a research method. Am. Sociol. 41, 115–141 (2010)CrossRefGoogle Scholar
  37. Nissen, Sylke: The eurobarometer and the process of european integration: methodological foundations and weaknesses of the largest european survey. Qual. Quant. 48, 713–727 (2014)CrossRefGoogle Scholar
  38. LIS standardisation routines for highest level of completed education. Undated. http://www.lisdatacenter.org/wp-content/uploads/standardisation-of-education-levels.pdf. Accessed 7 Feb 2014
  39. Marcum, J.A.: Instituting science: discovery or construction of scientific knowledge? Int. Stud. Phil. Sci. 22(2), 185–210 (2008)CrossRefGoogle Scholar
  40. Minkel, H.: Report on data conversion methodology of the change from input harmonization to ex-post harmonization in national samples of the European Community Household Panel—Implications on data quality. CHINTEX Working Paper 20. https://www.destatis.de/DE/Methoden/Methodenpapiere/Chintex/ResearchResults/Downloads/WorkingPaper20.pdf?__blob=publicationFile (2004). Retrieved 15 Feb 2015
  41. National Academies.: Facilitating Interdisciplinary Research. National Academies Press, Washington (2004)Google Scholar
  42. Olenski, J.: SSDIS. Global Standard for Harmonization of Social Statistics with special reference to transition and globalization processes. United Nations Statistics Division. ESA/STAT/AC.88/10 (April 7, 2003). http://unstats.un.org/unsd/demographic/meetings/egm/Socialstat_0503/docs/no_10.pdf (2003). Accessed 22 Feb 2014
  43. Platt, J.: The development of the ‘Participant Observation’ method in sociology: origin myth and history. J. Hist. Behav. Sci. 19, 379–393 (1983)CrossRefGoogle Scholar
  44. Portal on Collaboration in Research and Methodology for Official Statistics (CROS): http://www.cros-portal.eu/page/legal-notice (2014). Accessed 14 Feb 2014
  45. Quandt, M.: Data harmonisation as a cumulative effort a platform designed to foster the cumulation of knowledge. Paper presented at the workshop on harmonisation of social survey data for cross-national comparison. Prague, 19th October. http://archiv.soc.cas.cz/download/860/06_Quandt.pdf (2010). Accessed 22 Feb 2014
  46. Rainwater, L., Smeeding, T.: The luxembourg income study: The use of telecommunications in the social sciences. Luxembourg income study working paper series. Working paper No. 12 (May). http://www.lisdatacenter.org/wps/liswps/12.pdf (1987). Accessed 7 Feb 2014
  47. Schröder, H., Ganzeboom, H.B.G.: Measuring and modeling levels of education in european societies. Eur Sociol Rev 30, 119–136 (2013)CrossRefGoogle Scholar
  48. Slomczynski, K.M., Tomescu-Dubrow, I.: Survey data recycling: towards a formalized approach to ex-post harmonization of international projects. In: Harmonization: newsletter on survey data harmonization in the social sciences, vol. 1, pp. 10–13 (2015)Google Scholar
  49. Smeeding, T.M.., Schmaus, G., Allegrezza, S.: An introduction to LIS. Luxembourg income study working paper series. Working Paper No. 1 (June). http://www.lisdatacenter.org/wps/liswps/1.pdf (1985). Accessed 7 Feb 2014
  50. Smith, T.W.: Refining the total survey error perspective. Int. J. Pub. Opin. Res. 23(4), 464–484 (2011)CrossRefGoogle Scholar
  51. Thomas, E.A.: Herbert Blumer’s critique of the polish peasant: a post mortem on the life history approach in sociology. J. Hist. Behav. Sci. 14, 124–131 (1978)CrossRefGoogle Scholar
  52. Treiman, D.J., Ganzeboom, H.B.G.: Cross-National comparative status attainment research. Res. Soc. Stratif. Mobil. (9), 105–127 (1990)Google Scholar
  53. Treiman, D.J., Ganzeboom, H.B.G.: The fourth generation of comparative stratification research. In: Quah, S.R., Sales, A. (eds.) The International Handbook of Sociology, pp. 122–150. Sage, London (2000)Google Scholar
  54. Tomescu-Dubrow, I., Slomczynski, K.M.: Democratic Values and Protest Behavior: Data Harmonization, Measurement Comparability, and Multi-Leve Modeling in Cross-National Perspective. Ask. Res. Methods. 23(1), 103–114 (2014)Google Scholar
  55. UK’s Economic and Social Research Council: http://www.esrc.ac.uk/ (2014). Accessed 22 Feb 2014
  56. Van de Vijver, F.J.R., Matsumoto, D.: Introduction to the methodological issues associated with cross-cultural research. In Matsumoto, D., van de Vijver, F.J.R. (eds.) Cross-cultural research methods in psychology, pp. 1–16. Cambridge University Press, New York (2011)Google Scholar
  57. Wagner, C.S., Roessner, J.D., Bobb, K., Klein, J.T., Boyack, K.W., Keyton, J., Rafols, I., Börner, K.: Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature. J. Infometrics. 165, 14–26 (2011)Google Scholar
  58. Workshop “Harmonization Strategies for Behavioral, Social Science, and Genetic Research” organized by the US Department of Health and Human Services, National Institutes of Health, National Institute on Aging and Division of Behavioral and Social Research, Bethesda (MD), November 29–30, 2011. http://www.nia.nih.gov/sites/default/files/nia_bssg_harmonization_summary_version_2-5-20122.pdf (2014). Accessed 22 Feb 2014

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Joshua Kjerulf Dubrow
    • 1
    • 2
  • Irina Tomescu-Dubrow
    • 1
    • 2
  1. 1.Cross-national Studies: Interdisciplinary Research and Training program (CONSIRT)The Ohio State UniversityColumbusUSA
  2. 2.Institute of Philosophy and SociologyPolish Academy of SciencesWarsawPoland

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