For those new to qualitative research, this is the #1 book we recommend to familiarise yourself with the concept of coding, with clear tips and hints to get started, and to continue exploring different aspects of your data. This book is not discipline specific and is suitable for anyone attempting qualitative research either for the first time, or as a refresher.
In Saldana's words (p1) , the purpose of the book is:
to discuss the functions of codes, coding, and analytic memo writing during the qualitative data collection and analytic processes;
to profile a selected yet diverse repertoire of coding methods generally applied in qualitative data analysis; and
to provide readers with sources, descriptions, recommended applications, examples, and exercises for coding and further analyzing qualitative data.
"Coding is primarily an interpretive act; it is not an exact science" (p.4). Coding involves identifying patterns in the data with a pattern being "repetitive, regular, or consistent occurrences of action/data".
Saldana argues that this pattern needs to appear more than twice; on this point we don't entirely agree as sometimes the pattern is what is not being said, or something that is coded only once, which we consider significant. We agree it is not an exact science and the interpretation depends on the researcher’s philosophical beliefs, research training, methodological use etc.
Coding of qualitative data is generally done in two ways: using inductive and deductive techniques. Induction starts with recording a specific instance (e.g. a comment in an interview) and coding it to a relevant category or "code" that you create . This is a technique often associated with grounded theory and interpretive research; however we find it has relevance in most projects. Deduction starts with ‘a priori’ codes, categories you have set up before you start coding, often developed from the literature or from a theoretical framework. Both techniques can be used in combination.
Saldana argues that "coding is neither a philosophy nor a way of viewing the world; it is simply a heuristic for achieving some sense of clarity about the world from your data and your deep reflections on them". As such, this book helps with 30+ techniques for what to look for in your data. It's a great place to start, and a great go-to guide when we get stuck.
It also provides reassurance for the new researcher, reminding them that everyone experiences the ‘overwhelming fear’ when first confronted with the vast range of coding methods.