Qualitative data analysis is a MethodSpace focus for April. One topic is the use of software to aid the process. See a post on Qual Data Analysis with Software, and the entire series of posts about qualitative data analysis.
You found, downloaded, or collected qualitative data… now what? NVivo and Atlas ti are popular software options for analyzing diverse types of data for qualitative research. Two important books that guide researchers who want to use these CAQDAS are newly updated. In this post Susanne Friese discusses the new edition of Qualitative Data Analysis with ATLAS.ti. In a previous post Kristi Jackson, co-author with Pat Bazeley, discussed Qualitative Data Analysis with NVivo.
JS. The new edition of your book, Qualitative Data Analysis with ATLAS.ti, is now available. Can you tell us briefly what you’ve updated in the third edition?
SF. The book has been updated for version 8 Windows and Mac. Mac users will find instructions for all skills trainings on the companion website. The changes are quite extensive, as version 8 of ATLAS.ti is a completely new software. In addition, 9 years have passed since the writing of the first edition and I have developed my thinking about computer-assisted qualitative data analysis further. This is also reflected in the book.
JS. What features of ATLAS.ti are difficult to learn and use, and how will your book help researchers to move forward with their data analysis?
SF. It starts with setting up a project. Knowing what you can do with coded data, already helps making the right decisions when creating a project. If you are unfamiliar with the software, you don’t know this yet. Here I give the reader first guidance so that they don’t run into problems later.
The next step is learning how to code. Technically, that’s easy. The construction of a meaningful code system, however, is less self-explanatory. Chapter 5 therefore deals exclusively with the methodological aspects of building a coding system. I show typical mistakes and how to avoid them, such as the “code swamp”.
Teamwork and Intercoder Agreement (ICA), more use cases than functions, are two further topics that need a bit more explanation. I describe different scenarios, explain the methodical prerequisite for ICA and guide the reader step by step through the individual work phases.
JS. There are a number of CAQDAS options on the market. What do you feel is the benefit for choosing ATLAS.ti? What types of qualitative research are best served by analysis with ATLAS.ti?
SF. To give a sales pitch is not really my cup of tea. There are several features that all programs have, but each of these packages also has unique features. Those familiar with ATLAS.it know that these are the quotation level and the networks. Although other packages have something similar that they call a model or map, ATLAS.ti’s networking capability has never been surpassed. In terms of analytical approaches, ATLAS.ti supports interpretive approaches better than others due to the quotation level. However, at the other end of the spectrum, ATLAS.ti also gives numbers like absolute and relative frequencies, allows for data normalization and export to statistics programs, etc. that serve those working with a mix-method approach.
Another aspect I like about ATLAS.ti is that the development of software is driven by an innovative team focused on the needs of qualitative researchers. An example of this is that ATLAS.ti has always offered a non-proprietary XML-based project export format that other software companies used to provide an import function without offering anything of equal value in return. See this article written by Thomas Muhr already published in the year 2000.
Thanks to the initiative and relentless efforts of Jeanine Evers, this vision of Thomas Muhr has become true. ATLAS.ti is one of the founding members of the Rotterdam Exchange Format Initiative (REFI), the consortium that governs and designs the interoperability standard QDPX, and was amongst the first who released this new export format that allows projects to be exchanged between different CAQDAS packages when it was launched on March 18th this year.
JS. Can ATLAS.ti help qualitative researchers who are using Big Data? What about visual data, media, physical artifacts?
SF. If someone claims that one of the CAQDAS packages is suitable for analyzing Big Data, it would be wrong and misleading. ATLAS.ti and other CAQDAS can not handle millions of records. Some are better than others, but most are very slow or crash if you want to work with 2000 or more documents. This does not mean that the AI functions developed in connection with Big Data in recent years, such as sentiment analysis or entity recognition, could not be useful. I think such methods are a good and useful addition to manual coding but will not replace it. As CAQDAS software offers more cloud connectivity, larger online data archives can be accessed as a benchmark. This will significantly improve the results of AI applications, even for smaller data sets.
ATLAS.ti was already able to process visual data (pictures and videos) in 1996 with the first version of Windows. This was one of the reasons why I chose ATLAS.ti. Social media data is an important data source today, and I am sure that ATLAS.ti will offer more social media import options in the future.
Physical artifacts would need to be digitized as either image or video. Then you can also analyze them with ATLAS.ti.
JS. What research experience prepared you to develop this comprehensive guide?
SF. My not so straightforward career path I would say 😊. This is how “my points” connect:
I met John Seidel, the developer of the CAQDAS software The Ethnograph in 1992 while studying at Oregon State University and worked as a research associate for him for two years after completing my master’s degree. He is a trained sociologist and not a software developer. I learned a lot from him and am grateful that I had him as a mentor. For example, the N-C-T model that I present in the book is based on his ideas and I have developed it further over the years. After returning to Europe and starting a post as a research fellow at the University of Sussex in 1994, John put me in touch with Nigel Fielding, Ray Lee and Ann Lewins at the nearby University of Surrey at the launch of the CAQDAS project. As part of the project, I started teaching CAQDAS programs such as The Ethnograph and Nud*ist. In 1996 I returned to Germany and it was John who encouraged me to start my own company Qualitative Research & Consulting, QuaRC for short. He also came up with the name. If you want to know more about it, here is the story on my website.
When someone asks me about my discipline, I say, I’m a social scientist. I have never studied a classical subject such as sociology, psychology or economics. I started with nutrition and home economics in Bonn, Gemany. At Oregon State University, I studied Family Research Management and Marketing (Consumer Behavior). Then as I mentioned, I worked for John, my entry into computer-aided qualitative data analysis. The research project in the UK was anchored at the Institute of Social Psychology and Experimental Psychology. My dissertation was in the field of consumer economics and this resulted in a position as assistant professor at the Copenhagen Business School, not a match made in heaven. Between 2006 and 20011, I headed a Methodology and Media Center in the Department of Sociology at the University of Hanover. Most recently, I was a researcher at the Max Planck Institute as part of a larger research network in Digital Humanities. The all-connecting topic since my master’s degree was computer-aided qualitative data analysis. This is my area of expertise and this has prepared me over the years to write this book.
JS. You offer lots of “skills training” exercises in your book. How do you suggest readers use them?
SF. Readers should click through the individual exercises 😊. You cannot learn software just by reading something about it. The book is a hands-on book. I know from the readers of previous editions that they have the book on their desks next to them and work through the chapters in parallel with the advances they are making in their research projects.
Workshop participants can use the book to re-read what they learned and heard in the workshop. Teachers can use the book as a textbook and perform the exercises in seminars. There are several sample projects on the companion website that can be used in combination with the skill trainings.
JS. Is there anything else you would like to add about ATLAS.ti or the new edition of your book?
SF. I think this issue is the best version I’ve written so far. With each issue you learn something new. The feedback that I got from the reviewers in designing the 3rd edition and during the writing process was tremendously useful. Regarding ATLAS.ti, I would like to thank the wonderful, multi-faceted team. It’s great to work with you.
Related MethodSpace Posts
- Using Visuals to Present and Explain Qualitative Data
- A Data Visualization Sampler
- Visual Data Collection meets Data Visualization
- May Focus: Visualize Data & Findings
- ICYMI: Qual Data Analysis Series at a Glance
Also see: Learn from Cases: Using ATLAS.ti