Reflecting the inter-connected reality of today's world, contemporary education is striving to keep up with the exponentially rapid changes that individuals around the globe are facing. Innovative educational proposals carry labels such as connective learning (Downes, 2006), e-learning 2.0 (Downes, 2005), education 2.0 (Carr et al., 2008), or social learning 2.0 (Dron & Anderson, 2007). This chapter defines multimodality and discusses processes involved in multimodal data collection and analysis, as well as their bearing on scientifically sound qualitative research, endeavoring to embody a holistic approach. The term multimodality is used in this chapter to describe research in which interaction takes place entirely or partially online. To tackle the practicalities involved in multimodal data collection and analysis, this chapter describes software packages for efficiently managing multimodal data. Readers of this chapter will find a description of Computer-Assisted Qualitative Data Analysis Software (CAQDAS), namely the Transana, Atlas.ti, and NVIVO software packages, their main features, and ways in which they can support efficient storage, management and analysis of vast multimodal datasets. The chapter finishes with some recommendations to guide young researchers in choosing the right software package for their research purposes. Sources recommended for additional reading, and websites with resources are also provided. [A Spanish version of this chapter is also included in the book. For the complete volume, "Qualitative Approaches to Research on Plurilingual Education," see ED573580.]