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This page provides the definitions of the terms we will use to describe the domain (qualitative analysis of interviews). Most of the definitions come from Basics of Qualitative Research, 3rd Edition by Juliet Corbin and Anselm Strauss and are annotated by [BQR].

The goal of this glossary is to ensure that we adopt a consistent terminology throughout the project (specs, design, implementation, user doc).

At the end of the glossary, there is a list of concepts that do not have a formal name yet.

Axial Coding

Crosscutting or relating concepts to each other. [BQR]


Higher-level concepts under which analysts group lower-level concepts according to shared properties. [BQR]

Also called themes. In my mind a category is often a concept that was not directly associated with any piece of data, but sometimes, a low-level code can be promoted to a category so I'm not sure the difference between categories and concepts matter in the context of Qualyzer --bart


Person who assigns a code (concept) to a piece of data.

A coder is not necessarily a researcher. For example, when using inter-coder agreement, the coders could be interns not part of the research team.


Deriving and developing concepts from data. [BQR]

Qualyzer should focus on supporting coding

Concepts (or Codes)

Words that stand for groups or classes of objects, events, and actions that share some major common property(ies), though the property(ies) can vary dimensionally. [BQR]

Constant Comparisons

The analytic process of comparing different pieces of data for similarities and differences. [BQR]

Ideally, Qualyzer should support this process by easing the comparison between interviews/quotes/codes


Structural conditions that shape the nature of situations... to which individuals respond by means of action... [BQR]

In my experience, context is developed through codes, categories, and memos. Do we want to explicitly support the modeling of context? --bart


Variations of a property along a range. [BQR]

When a code is associated with many pieces of data, the variety of the data represents the various dimensions.


A piece of raw data associated with a code.


Linking categories around a central or core category and refining the resulting theoretical formulation. [BQR]

Qualyzer should support integration by allowing the user to easily organize/group the various codes and categories. Qualyzer should also be able to detect codes that are not yet integrated.


A recorded conversation between two people (the interviewer and the interviewee) where questions are asked by the interviewer to obtain information from the interviewee.

An interview with one participant is the common case, but should Qualyzer supports any kind of Qualitative material like focus group transcriptions?


Person who participates to the data collection, analysis, and communication of the results. Could also be called investigator or analyst.

Researchers are the user of Qualyzer. Should we call them user or should we use a more precise term like researcher? --bart

In-Vivo Codes

Concepts using the actual words of research participants rather than being named by the analyst. [BQR]

It might be interesting to capture the fact that a code is in-vivo and trace its at least one quote.


Written records of analysis. [BQR] A researcher can write a memo to record a thought, to explain in more detail a concept, a relationship, a process, etc.

Memos are related to concepts, but should concepts be extracted from memos like they are from interviews? --bart

Negative Case

A piece of raw data that does not fit in the theoretical framework developed by the researcher. As Corbin put it "Often the negative case represents a dimensional extreme or variation on the conceptualization of data."

Also called contradiction or counter-example.

Qualyzer should help researchers keep track of these negative cases. In the end, all negative cases should be explainable so they are no longer negative, but just variations according to certain conditions.

Open Coding

Breaking data apart and delineating concepts to stand for blocks of raw data. [BQR]

Essentially, this means (1) generating concepts from raw data and (2) purposely breaking data into coherent blocks. This is as opposed to trying to assign a concept from a pre-defined list to a selected piece of raw data.

Should Qualyzer support other types of coding? --bart


The flow of actions... that occurs in response to events, situations, or problems. A change in structural conditions may call for adjustments in activities... Actions may be strategic, routine, random, automatic, etc.[BQR]

If we had lot of resources, we could devise a graphical editor that would enable users to draw a process and Qualyzer could infer the relationships between the various codes, based on the relationships in the process view... for now, I don't think this is a must-have feature --bart


Characteristics or components of an object, event, or action. The characteristics give specificity to and define an object, event, and/or action. [BQR]

The various properties of a code are represented by multiple parent categories. For example, Junk Food can be a "Cause of bad health" and also a "Temporary Solution to Stress".

Raw data

Information collected during a study, e.g., audio and video recording of interviews or tasks performed by participants. These recording are often transformed into a textual representation, the transcription.

A transcription is usually considered to be raw data, but there are various levels of transcriptions (e.g., non-verbal expressions are not always transcribed).

An interview summary is not considered to be raw data.

Should Qualyzer make a distinction between raw data and non-raw data? What about raw data (e.g., quotes) inside non-raw data? --bart

Research Participant

Person that participates in a research study, e.g., by accepting to share his/her experience through interviewing.

Will be called "Participant" in Qualyzer for simplicity


  • TBD