Qualitative Data Analysis Software (nVivo, Atlas.TI, and more)

Overview and resource links for Qualitative Data Analysis Software (QDAS), uses and how to choose, focusing on QDAS supported by JHU Data Services: nVivo and Atlas.TI, with resource and training links to these and other QDA Software

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JHU Data Services

Contact us, JHU Data Services for assistance with access to nVivo and ATLAS.ti at the Data Services offices on A level, JHU Eisenhower Library.

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Qualitative Data Analysis Software (QDAS) overview

Qualitative research, particularly that involving multimedia digital data, has benefited over the last decade or so by the development and advances in software tools that facilitate most of the primary qualitative methodological techniques.

These guides start with resources for the two major QDAS products, nVivo and Atlas.ti.  Both programs can be found on the workstations at Data Services offices on A-level, Eisenhower library. This guide also lists other QDA software and linked resources.

Many university libraries have produced comprehensive guides on nVivo, Atlas.ti, and other QDA software, to which we will provide links with our gratitude

Schmider, Christian. n.d. What Qualitative Data Analysis Software Can and Can’t Do for You – an Intro Video. MERIT Library at the School of Education: School of Education, University of Wisconsin-Madison. Accessed January 7, 2020. https://www.youtube.com/watch?v=tLKfaCiHVic.

Choosing QDA Software

Qualitative Data Analysis (QDA) Software supports a variety of qualitative techniques and methodologies

Qualitative techniques supported by QDAS

  • Coding and Classifying
  • Writing: analysis, description, memos
  • Relating: finding and annotating connections, relationships, patterns
  • Audio/Visual analysis: marking, clipping, transcribing, annotating
  • Text mining: computer-aided discovery in large amounts of unstructured text
  • Visualization: diagramming, relationship and network patterns, quantitative summary 

QDAS supported methodologies

  • Ethnography
  • Case studies
  • Grounded theory/ phenomenology
  • Discourse/narrative analysis
  • Sociolinguistic analysis
  • Collaborative qualitative research
  • Text analysis & text mining

Overview of qualitative methods from ATLAS.ti: https://atlasti.com/qualitative-research-methods/

Decision factors for your research

  • Methods to feature facilitation (in disciplinary context): How many features directly support your methodology?
  • Interface for collection, analysis, reports: Do features accommodate most phases of your research workflow?
  • Visualization and outputs: Does it produce and successfully export needed visualization without extensive modification?
  • Cost and access to software: Is it worth the investment cost as well as in learning to use it? Look for education discounts.

Core QDAS functions

Basic functions common to most QDA programs, and to NVivo and ATLAS.ti in particular:

  • Coding
    • Application of a maintained set of terms and short phrases linked to segments of text or audio/video that can be queried and gathered for comparative analysis. 
  • Annotation
    • Longer narrative notes attached to text or a/v segments, or to codes
  • Navigation / queries
    • Quick access to codes and segments that can be brought together in panel views for comparison, advanced Boolean search options, and flexible interlinking of segments, codes, and annotation
  • Transcription
    • Most QDAS facilitates transcribing audio and video, ideally maintaining the links between transcript and A/V segments. 
  • Relationships/patterns
    • Gathering codes, segments, and annotations facilitates pattern discovery and further description of relationships. Some QDAS support social network analysis techniques and visualization
  • Reporting / collating
    • A range of reports using queries and filters to assemble data and annotations facilitates analysis and writing results.
  • Visualization
    • Typically includes code tables, social network graphs, and annotated A/V clips.
  • Collaboration
    • Shared access to data & analysis, facilitating comments and discussion, and tracking contributor actions and changes.