This paper describes recent issues and developments in Qualitative Data Analysis Software (QDAS) as presented in the opening plenary at the KWALON 2016 conference. From a user perspective, it reflects current features and functionality, including the use of artificial intelligence and machine learning; implications of the cloud; user friendliness; the role of digital archives; and the development of a common exchange format. This user perspective is complemented with the views of software developers who took part in the “Rotterdam Exchange Format Initiative,” an outcome of the conference.
Qualitative Data Analysis Software, QDAS, Artificial Intelligence, Machine Learning, ATLAS.ti, Cassandre, Dedoose, f4analyse, MAXQDA, NVivo, QDA Miner, Quirkos, Transana, Exchange format, Interoperability, Qualitative Data Analysis, Learning Curve QDAS, Textual Data Mining, Cloud services.
I am indebted to Anne Kuckartz, Thomas Muhr and Thorsten Pehl for their openness to the idea for the Conference at the Berliner Methoden Treffen 2015, which encouraged me to proceed it further. Last but certainly not least, I would like to thank Harry van den Berg and Richard Staring for their comments on an earlier version of this article and Christina Silver for her comments on a part of the earlier version.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.
Recommended APA Citation
Evers, J. C. (2018). Current Issues in Qualitative Data Analysis Software (QDAS): A User and Developer Perspective. The Qualitative Report, 23(13), 61-73. Retrieved from https://nsuworks.nova.edu/tqr/vol23/iss13/5