Data integration is a crucial element in mixed methods analysis and conceptualization. It has three principal purposes: illustration, convergent validation (triangulation), and the development of analytic density or ''richness.'' This article discusses such applications in relation to new technologies for social research, looking at three innovative forms of data integration that rely on computational support: (a) the integration of geo-referencing technologies with qualitative software, (b) the integration of multistream visual data in mixed methods research, and (c) the integration of data from qualitative and quantitative methods. Keywords data integration, new research technologies, computer support for mixed methods Combining different methods and kinds of data in the empirical study of social phenomena goes back to the beginnings of social science (see Hesse-Biber, 2010a, for the historical lineage of the triangulation concept and Plano Clark, 2010, for an account of the rise of mixed methods in U.S. government-funded research). Mixed methods potentially offer depth of qualitative understanding with the reach of quantitative techniques. Initially, it was the more quantitative researchers such as Paul Lazarsfeld who practiced mixed methods (Jahoda, Lazarsfeld, & Zeisl, 1976), but following Campbell's papers on ''triangulation'' as a means of convergent validation (Campbell & Fiske, 1959) and the emergence of grounded theory (Glaser & Strauss, 1967), whose ''constant comparative method'' involves comparing data from different sources, the triangulation metaphor also became established in qualitative research. Ivankova and Kawamura (2010) offer a comprehensive and extensive bibliometric survey of contemporary mixed methods practice. On the basis of searches of five databases (PubMed, ERIC, PsychInfo, Academic OneFile, Academic Search Premier) and two journals (Journal of Mixed Methods Research, International Journal of Multiple Research Approaches), Ivankova and Kawamura found a consistent growth in mixed methods research since 2000. Numbers rose increasingly sharply from the year 2000 (N = 10) to 2008 (N = 243). Some 689 studies were classed as full mixed
