What is Open Coding in Qualitative Research?

Introduction

Qualitative coding aims to bring order to unstructured data. Whether it's a blog post, an interview transcript, or notes from a set of striking observations, qualitative researchers rely on codes in order to identify relationships between and provide an explanation for social phenomena. That said, there are countless approaches to coding; the best approach depends on your research inquiry.

Among approaches to coding data in qualitative research, open coding is perhaps one of the least prescriptive approaches. When employing open coding, the researcher codes the data based on what they see in the data and how they interpret what is going on. This is a good first step in the data analysis process if your research project is focused on the development of new themes, concepts, or theories. If that is the case for your study, let's look a little more closely at the open coding process.

What is meant by open coding?

Open coding is an integral part of the qualitative analysis process where exploratory inquiries are involved. Qualitative data almost always undergoes some sort of coding process to help researchers conduct analysis on and draw meaning from the data. When qualitative data is coded, it greatly facilitates analysis and the proposal of new theories and concepts based on the produced codes. Open coding is one of many strategies used to code data. While other approaches may be deductive in nature (i.e., reliant on existing theories), open coding adopts an inductive approach, requiring researchers to examine the data with as few preconceived notions as possible. In a sense, the researcher remains "open" to the various possibilities of meaning in the data so that the representations of meaning contained in a research project's codes are as close to the data as possible.

Uses for open coding

Open coding is often applied to the analytic process in grounded theory methodology, thematic analysis, and any other inductive approach to qualitative research. Essentially, any research project involving an exploratory research question (i.e., an inquiry that develops or proposes a new theory rather than tests existing theory) will often employ open coding as a part of its research methods.

Method of open coding

A code is a word or short phrase that describes something that is going on in the data -- you can also think of codes as tags that you attach to segments of data. Open codes are created when the researcher examines qualitative data (such as text, images, videos, etc.), selects a relevant segment of data, and attaches a code (or codes) that capture the meaning or the aspects that are relevant to the research question within that data segment. As mentioned previously, the researcher should look at the data with as open a mind as possible, avoiding the temptation of applying existing theories to the coding process. This approach allows for new theory developed directly from the data.

When should I use open coding, axial coding, and selective coding?

Open coding is only one strategy that can be complemented by other methods of coding. In a grounded theory approach, open, axial, and selective coding make up the steps of a larger process that aims to contribute new theory or propose new concepts. The researcher conducts open coding to apply short and descriptive phrases to larger segments of data. Think of these codes as keywords used to condense and organize the data for subsequent stages of analysis.

At the axial coding stage, the researcher draws connections between discrete parts of their study represented by open codes. Axial coding consists of grouping codes and placing them in a new category that embodies a broader meaning. As a result, if the codes produced in open coding are discrete elements of meaning, axial codes thus represent broader categories that group those open codes together. It is up to the researcher to determine how open codes should be categorized and how those categories place discrete codes within the broader context of their study.

Finally, selective coding narrows the analysis process to a single core category or categories related to the codes in your project. At this stage, the researcher acknowledges that certain categories are more consequential to the research question and warrant a more central role in the emerging theory. Ultimately, selective coding connects the discrete meaning represented in the codes and categories with the broader theory development in an exploratory study.

Keep in mind that the grounded theory approach is an iterative process. As categories and themes develop, the researcher develops an understanding of the collected data that can be employed in subsequent iterations of data collection and coding. At this stage of the analysis process, the researcher continues to avoid applying existing theories to the data but, instead, uses their understanding of the codes and categories they produce to engage in a more nuanced iteration of open coding as they continue to develop a coherent theory.