The Ultimate Guide to Qualitative Research - Part 2: Handling Qualitative Data

% complete
Get hands-on guidance for working with qualitative data: discover how to transcribe, organize, code, and analyze.
Jörg Hecker
Neringa Kalpokas
Director, Training & Partnership Development
  1. Handling qualitative data
  2. Transcripts
  3. Field notes
  4. Memos
  5. Survey data and responses
  6. Visual and audio data
  7. Data organization
  8. Data coding
  9. Coding frame
  10. Auto and smart coding
  11. Organizing codes
  12. Qualitative data analysis
  13. Content analysis
  14. Thematic analysis
  15. Thematic analysis vs. content analysis
  16. Narrative research
  17. Phenomenological research
    1. Introduction
    2. Knowledge
    3. Phenomenology
    4. Phenomenology in qualitative research
    5. Considerations for phenomenological inquiry
    6. ATLAS.ti tools for phenomenological research
  18. Discourse analysis
  19. Grounded theory
  20. Deductive reasoning
  21. Inductive reasoning
  22. Inductive vs. deductive reasoning
  23. Qualitative data interpretation
  24. Qualitative analysis software

Phenomenological research

Knowledge is a subjective experience. Yes, all knowledge! If you are taking a qualitative research approach, you can benefit from having a firm grasp of phenomenology and its value to qualitative research methods.

Phenomenology is about examining the world through individuals' lived experiences and knowledge.

Let's examine what phenomenology is, what that means to our ability to understand phenomena and generate knowledge, and how ATLAS.ti can help you make qualitative research more concrete and compelling to your research audiences.


One of the most challenging notions to acknowledge in qualitative research is that people perceive the world around them differently from other people. Because everyone's circumstances, life experiences, value systems, and biological factors are different, it is challenging, if not impossible, to achieve an objective understanding of all but the most basic concepts.

In scholarly research, the most objective knowledge can be found in the physical and natural sciences. For example, the molecular weight of a given element is always the same regardless of where or how much of it is found. The acceleration of a falling object within Earth's gravity is always constant. At sea level and at a defined pressure level, water always freezes at the same temperature.

Research approaches in the social sciences, on the other hand, deal with concepts that are subjectively constructed. For example, what does it mean when people have a dialogue with each other? Is it simply the act of multiple people talking, or do ideas need to be exchanged and developed among those people? And is such an exchange contentious, harmonious, or something in between? That social scientists can disagree on which of the many possible versions of dialogue is the most pertinent conceptualization affirms the challenge of viewing social phenomena as objective concepts with absolute truths. As such, phenomenological research methods make up an essential aspect of human science to contribute to scientific theories. Understanding and acknowledging phenomenology is less about determining the "true value" or objective meaning of a particular concept or phenomenon and more about situating social phenomena in the context of individuals and cultures.


If you are employing a phenomenological research design to gain insights, then it's important to get a sense of the philosophical underpinnings of phenomenology. While this can be a long, protracted discussion, two important concepts to keep in mind are epistemology and ontology.

Epistemology and ontology

When we say that qualitative methodologies employed in phenomenological research involve perception, we mean to say that it examines what people think in addition to what they see and sense. After all, while things like water and light are objectively defined in science, they are only defined by human beings who use their senses to understand such things.

Epistemology refers to considering the origin, nature, or scope of knowledge. A purely phenomenological study can focus on the way that people perceive the world around them to provide a deeper understanding of the epistemologies informed by cultures and societies. Ultimately, this is useful in fields such as anthropology and sociology, where the discussion of cultures identifies the different ways that people see the world. Still, phenomenological researchers can think about epistemology to also facilitate market research in understanding how customers look at products and services and how they behave in the consumer market. Moreover, fields like phenomenological psychology are especially interested in epistemology because of the need to explore how individuals experience the world through their senses.

If epistemology relates to the way of thinking, ontology deals with the questions of what exists in the world or the nature of reality. Broadly, research inquiries can analyze human experiences to gain insights into the reality of the world around people. If “reality” is viewed as something that exists independent of human experience, researchers can aim to identify the “truth” that exists. Conversely, if “reality” is understood as dependent on people’s interpretations, researchers can develop an understanding of participants’ constructed “truths” that are contextually embedded.

Potential questions exploring the ontology of the social world include some of the following:

  • What is an individual's role in greater society?
  • How are the material and spiritual worlds linked?
  • How does language inform our reality and vice versa?

Phenomenology in qualitative research

Phenomenology has origins in discussions of philosophy, but its principles have significant utility in qualitative research precisely because it can inform how we should approach data collection and data analysis in the social sciences. That said, phenomenology provides multiple approaches for researchers to choose from.

Transcendental phenomenology and hermeneutic phenomenology

Edmund Husserl's approach to phenomenology is largely concerned with finding the essence of consciousness. Any transcendental approach holds the assumption that phenomenological research can get at the very core of what it means to see and experience the world, irrespective of language barriers, cultural differences, or personal preferences. The objective of this approach to phenomenology is nothing short of getting at what it means for us to be human beings. A transcendental phenomenological method engages in a process called bracketing. When collecting data, the researcher is supposed to suspend intuitions or assumptions that might be informed by prior experience (in effect, "bracketing" or isolating those assumptions from perception or analysis). Instead, under Husserl's phenomenology, new theories should be generated without researcher bias.

Unlike Husserl, Martin Heidegger was more interested in an approach to phenomenology that relies on interpretation. Within hermeneutic phenomenology is the assumption that meaning is interpreted and reinterpreted through the lived experiences and perspectives of people. In other words, how a person sees the world is shaped by their knowledge, beliefs, values, and experiences. Hermeneutic phenomenology tends to focus on the interpretation of texts, like books or personal narratives. Think about how children's stories are reinterpreted and how each new author or storyteller changes the finer points of those stories. Such changes are informed by each storyteller's personal characteristics and other factors like societal circumstances or influences by personal acquaintances.

Interpretive phenomenology

While interpretive and hermeneutic phenomenology shares similar roots, interpretive phenomenology has a broader focus on the interpretation of the lived experiences themselves. Imagine how differently people feel about riding a roller coaster, particularly when one is a thrill-seeker while another is more averse to risk or danger. While the objective experience of a roller coaster ride is essentially the same for the two people, how they experience it and retell their experience to others will depend on how they ultimately feel about it.

Practical concerns

Regardless of the approach, the philosophical underpinnings of interpretative phenomenological analysis require qualitative researchers to critically evaluate their data collection methods and data analysis when they acknowledge that, as human beings, they are incapable of producing a purely objective representation of the world around them. When gathering data involves perception, how that perception is colored requires a full accounting, whether to inform data analysis or to bracket any potential biases from the analysis. In particular, a phenomenological research design that relies on hermeneutics calls for a detailed description of who the researcher is relative to their research participants. This gives the research audience a clear guide that they can use to understand the data and apply the research to their own inquiry. On the side of data analysis, an acknowledgment of phenomenology requires researchers to take a critical look at what their research participants say and do. Put another way, it could be a mistake to take participants' experiences and utterances at face value.

Considerations for phenomenological inquiry

Among other concerns, those involved in conducting phenomenological research through qualitative methods should look at three distinct factors: what they want to research, how their view of the world and the research affects their methods for collecting data, and how their research participants see the world. Addressing these considerations is essential for any phenomenological research as they color how the data is collected and interpreted by both the researcher and their audience.

Crafting research questions for phenomenological research

The research question in a phenomenological research study determines the theoretical underpinnings that guide the way you collect and analyze data. Highly structured questions aim to provide structure and conceptual clarity to your study. Palliative health research questions, for example, might explore how patients deal with death and dying. As a result, researchers engaged in such inquiries might direct their focus to observing patients in terms of what they say and do.


Health research and psychological research often involve researchers who have vastly different backgrounds than those of their research participants. For example, researchers in palliative medicine often work with dying patients to get a perspective that is relatively unfamiliar to them. The difference in perspective requires accounting by way of positionality. In qualitative research, researchers describe who they are and what their background is to allow their research audience to compare the researcher with their research participants. The distinctions that are made explicit provide clarity to the data that is collected. Moreover, explicitly declaring positionality is also a good form of self-reflection that keeps researchers aware of where they are relative to their research participants.

Member checking

When you record field notes during observations or create transcripts from interviews, you are really only collecting data as you see it, not necessarily how the research participants see it. Think about a male researcher trying to document women's experiences and actions. Without the researcher trying to explore what their research participants are thinking during those experiences, it is a challenge to present a truly detailed study of the human experience.

Oftentimes, a rigorous phenomenological study depends on a process called member checking, which involves the researcher following up with their research participants about the collected data and analysis. For example, a researcher may observe someone going about their everyday life and record their actions in field notes. Afterward, a responsible researcher checks with the person who was observed to confirm the details of their actions and the thinking behind the decisions they made.

ATLAS.ti tools for phenomenological research

Organizing the data in a phenomenological study may be little different from that of other qualitative studies. That said, some tools in ATLAS.ti are especially relevant to phenomenological research.

Focus Group Coding

Individual interviews and focus groups are useful sources of data for capturing how human beings see the world differently from those around them. Once we acknowledge that our research participants' experiences and knowledge make each person's worldview unique, then we can identify the utility of sorting data by participant.

The challenge for interviews and focus groups is that transcripts make it difficult to isolate one speaker's utterances from another's. The Focus Group Coding tool in ATLAS.ti can help with this task by applying distinct codes to each speaker. The Focus Group Coding tool can parse a consistently formatted transcript to identify a speaker and their utterances. For example, ATLAS.ti can parse out part of a movie script to create codes based on the names of the speakers in the scene and apply those codes to the utterances of each speaker. With these codes and quotations in place, you can refine the scope of ATLAS.ti's search and analysis tools to the data relevant to a single speaker.

Code Groups

As you develop your phenomenological research, you may want to group individuals together if you find they share a similar worldview or other factors that can be used to form groups of people like cultures or other identity groups. Tools like Focus Group Coding create codes for individual speakers. Still, codes in a qualitative study should be organized into broader categories to allow for a more efficient analysis of your data.

In ATLAS.ti, codes can be nested in hierarchies in the Code Manager for a clearer organization of your coding structure. However, phenomenological research often looks at phenomena regarding individuals and their affiliation with multiple groups (e.g., groups based on age, gender, ethnicity, or even personal interests). In this case, you should consider using code groups to organize your codes representing individual research participants in multiple categories. Researchers can categorize each speaker code (e.g., Charlie and Darlene) into different code groups such as "male" or "female," "young speaker" or "elderly speaker." These groupings will serve as the descriptive elements of your phenomenological research and will be complemented by codes and groups that are more interpretive in nature (e.g., "happy," "excited") when you conduct your analysis later on.

Sentiment Analysis

With codes and groups for your speakers already in place throughout your project, you will also need to apply interpretive codes to employ tools such as Code Co-Occurrence to identify potential relationships between research participants and social phenomena. The challenge is that applying these codes manually is a time-consuming process, especially if you have large data sets.

While the coding process can never be fully automated, Sentiment Analysis in ATLAS.ti can help you speed up some of the creation and application of codes in your project. Sentiment Analysis is an AI-powered tool that examines the text in your documents for sentiments that can be positive, negative, or neutral in nature. As a result, you can analyze a speaker's utterances in interviews for their attitudes about particular concepts or phenomena.

Code Co-Occurrence Analysis

When your descriptive codes and interpretive codes overlap with each other, there is a correlation or a co-occurrence that can be analyzed for important insights. Identifying these co-occurrences can help you generate a rich analysis for generating new theories. In Code Co-Occurrence Analysis, you can search for correlations between descriptive codes and interpretive codes to see which combinations of codes appear the most often with each other. The resulting table not only identifies those frequencies but also lets you narrow your view of the data to a specific group of people addressing a particular social phenomenon.


At a core level, memos in ATLAS.ti are just another form of document in your project. Methodologically, however, they serve a number of important purposes in any qualitative research approach. First, they provide a written record of our reflections that we would otherwise forget. These reflections might be consequential in refining your analysis, reorganizing your data, or even adjusting your research methods or questions. Above all, memos are useful especially as phenomenological research requires an accounting of who the researcher is and how they approach the research and their research participants. You may also have multiple members working together in a research team, in which case the research relies on the consensus of all team members regarding the elements and direction of the research.