Quirkos - Doing Qualitative Research - Epistemology and Meta issues
Skip to main content

Doing Qualitative Research: Epistemology and Ontology; Meta issues in qualitative research

The qualitative research process, according to the model we are using for this course. Links are embedded in this graphic to take you to the different sections of the course.Design and planEpistemologyand MetaissuesGather dataManageand handledataAnalyse and transform dataWrite andreport

Doing Qualitative Research

Epistemology and Meta issues

↑ Back to top

Epistemology and Meta issues

Qualitative research projects will typically need to address the Meta issues of a project, even though they may never be detailed in published works. By Meta issues we mean the things that research needs to have, do, or be, in order to maintain public and academic trust in research. In this part of the course we will examine the philosophical basis of qualitative research first (including Epistemology) and meta issues such as:

  • Project rationale - the need for and purpose of the research
  • Design protocol - methods of data collection and analysis, stages of the research or decision points and timings
  • Ethical review and risk assessments
  • Data management plan - how and where your data will be stored and results made accessible for future researchers

There is a lot of material to cover here, so don’t worry if you need to take a break and look at some other sections. Just remember to come back often. That’s why our model shows Epistemology and Meta issues in the centre; it’s at the heart of qualitative research.

The research process and the philosophical basis of your research

Having thought about setting up your research, we need to take a step back in our process and consider how our design is related to our philosophical perspective and our beliefs about issues such as truth and validity.

Design issues

Rigorous and credible research is vital to ensure quality research. All research relies on clear procedures, justification of purpose and methods, reference to previous research, and justifiable conclusions.

Quantitative research relies on concepts such as objectivity, replicability of results, and statistical external validity to ensure rigour.

Qualitative research often has a different approach to rigour. Concepts that are valuable and appropriate to large-scale population based research are inappropriate for individuals and small groups, where the subjective experience may defy the norms of a general population. Rigour is demonstrated through:

  • Explication of method and methodology
  • Collection methods that would be reproducible, though the data collected would probably be different, even from the same participants and the same researcher.
  • Documented processes of analysis. Any codes, themes or arguments could be traced back to their origins in the data.
  • Understanding of the subjective positioning of the researcher throughout, and its effect on the analysis and findings.
  • Systematic use of representative data to present findings.

Triangulation (using different methods to examine the same issue) is sometimes used to demonstrate rigour. It is used in quantitative approaches to validate research findings, with the expectation that you will find the same thing using different methods. In qualitative research you might triangulate for a different reason, i.e. to demonstrate the thorough examination of an issue, you might use different methods to create perspective. These different perspectives may show different findings and add depth.

Methods and Methodologies

Before you look at some of the common language used in the philosophy of social research, take a moment to answer this question.

Question mark
Question mark
What's the difference between a method and a methodology?

  • Give your first response
  • Write it down
  • Discuss with colleagues
What's our answer?

Put very simply, Method is what you are doing: your tools or instruments; interviews, surveys, questionnaires, observations, artefacts, tests.

Methodology is why you are doing it that way: your reason for using that method and the approach you will take with the method.

For example, there are many approaches to an interview. Will you ask predetermined questions? Will they be in a set order? Will you accept deviations from your question list? Your epistimological beliefs will determine your answer. You may be using a qualitative tool, such as observation or focus group, but are you using a qualitative methodology? Just using these tools doesn't make your research ‘qualitative’. Perhaps you are just using a qualitative method, but applying quantitative analytical approaches. Don’t worry, it’s not wrong to use a different philosophical approach with qualitative tools, but you should know at least broadly what your epistemological approach is.

Ontology and Epistemology

Ontology and epistemology are terms that can understandably cause some confusion and anxiety as they deal with some difficult questions. Ontological questions include; What is knowable? Does God exist? What does it mean to be Human? Does knowledge pre-exist human knowing? Epistemological questions include, Does truth exist in an objective form, or is it dependent upon context and other constructs of knowledge? What can we know? How do we know?

Here is a simplified view that should help you when you read more complex texts.

What is ontology?

Ontology is the philosophical study of being or existence as well as the basic categories of those things. Ontology has strong implications for the conceptions of reality. Most forms of Science have a stable foundational ontology. This could be simplified as a single external reality that exists beyond the human experience. It can be reliably tested in isolation from the entire human experience. You are probably already deeply familiar with it (whether you know it or not), as this ontology is foundational in much of western education and systems of governance.

What is epistemology?

Epistemology - is the branch of philosophy that deals with the nature, origin and scope of knowledge. Epistemology is a position on the nature and variety of knowledge and how it relates to similar notions such as truth and belief. Much discussion in epistemology concerns the justification of knowledge claims.

What is the difference between the two?

Reduced to a terribly simplistic form, Ontology is what is knowable our world view and Epistemology is how do we go about knowing, or how do we find our methodology. A sound Epistemology is built on secure ontological foundations.

Research paradigms

A paradigm is a pattern of concepts that form the basis of legitimate research. Two major paradigms commonly referred to in social research are Quantitative research and Qualitative research. They are often placed in opposition to one another or as a false spectrum. What we usually call the quantitative paradigm can properly trace its roots to the philosophy of logical positivism, from the second half of the 19th Century and the 1st half of the 20th Century, (e.g. Compte, Wittgenstein, Russell). Qualitative research has a shorter modern history of academic debate, and the ontological foundation is constantly debated. This discussion is important, but when new to the debate can be intimidating rather than exciting.

Graph showing a continuum/dichotomy between quantitative and qualitative research

This is a false spectrum that places quantitative and qualitative research in opposition, but it is commonly used.

Regimes of truth and constructions of power

Graph showing a continuum/dichotomy between positivism and qualitative research

As we saw earlier, truth can be seen differently depending upon our particular paradigm. In qualitative paradigms, where truth is considered a construct, we can go further than this. It is argued that notions of validity, reliability and replicability, which are central to notions of robustness in scientific (positivitic) research, are (at best) inappropriate regimes for evaluating qualitative research. They are (at worst) damaging paternalistic structures used to limit power, thought, and maintain the status quo, along with other positivistic regimes of truth (i.e. central tenets that are held to be true and go unquestioned).

Examples of regimes of truth in positivistic research:
  • If something is not statistically provable then it is not true
  • Large samples are always better than small ones
  • Personal testimony has no value because people can lie
  • Normal science can and does achieve objectivity
  • Bias can and should be isolated and removed

A central tenet of Qualitative research (epistemologically speaking) is that Research is NOT objective. You, the researcher, affect the field. Even in physical sciences there is recognition of uncertainty principles, such as Heisenberg's Uncertainty Principle which relates to how we affect a particle we're attempting to measure. Facts are not universal truths, they are social constructs.

Research does not take place in a social vacuum and it may be difficult for you to embrace and make the most of your subjectivity. Peers in your discipline may be looking at your research and looking for the same indicators of robustness as for numerical research i.e. external statistical validity and replicability. This can be frustrating. Nonetheless we should be creating processes that show credible, reflexive and transparent justification for your claims.

Understanding your personal ontology and epistemology

The tools that we use and the way we use them in research will be guided both consciously and unconsciously by our training and our worldviews. So we need to be conscious and explicit about what we think we know and believe, especially as this changes over time. In the previous section ✏️ Design and plan, you were invited to consider a simple set of Socratic questions:

Who will be your research participants?

Why are you undertaking the research?

Where will you get your sample?

When will you begin and end?

How will you collect, analyse and report the data?

What aspect of the issue you will explore?

This simple list of Socratic questions becomes more complex as the subjective is acknowledged and accepted. For example…

Who will be your research participants?

What is the power relationship? Who are the gate-keepers? Are you an appropriate person to do this research?

Why are you undertaking the research?

What is the purpose, and for whose benefit are you asking the question?

Where will you get your sample?

Where will you do your field work? Is that feasible?

When will you begin and end?

When (and how) will you leave the field?

How will you collect, analyse and report the data?

To whom will you report? How will your participants be involved or consulted about their data?

What aspect of the issue you will explore?

What happens if your participants or context doesn’t conform to your expectations? How are you representing participants?

… and the list is not exhaustive.

Photo of a pen on top of handwritten plans
Qualitative research design (and planning)
[9 min read]

The thinking and reading that you did in ✏️ Design and plan would have prepared you for some of this kind of thinking.

  • Revisit and reflect on the blog or the notes you made, before moving on to your own worldview
  • Discuss with colleagues

Discuss and reflect on your own world view

Framing everything you do is your methodology. (For now we will treat methodology and epistemology as the same thing). Without a methodological framework you are applying tools bluntly to your problem.

Exclamation point
Exclamation point
Organise these broad statements to match these paradigms.

Where would you position your own world view? Does it even fit in anywhere on this grid? Drag and drop responses to complete the table. Make notes and discuss with colleagues.

Positivist/Critical rationalist (Normative science)

What is happening here? Why do you act this way?
Discover the underlying meaning of events and activities in the context of power relations. Reconstruct to create new insight and empowerment
If it works then it must be true.
Null hypothesis
Who has power here and how is it exercised? How can the situation be changed?
Which action will lead to the desired outcome?
Hypotheses can be tested from which knowledge can be deduced.
Knowledge cannot be verified only falsified.
Discover the underlying meaning of events and activities in context. Reconstruct to create new insight
Whatever works or provides solutions to problems is ‘best’
Rules exist for governing all things - some of which are hidden from the senses, but the truth is out there.
Power is key in the construction and control of reality. Those with power control truth.
Reality is constructed by individuals within groups. Truth is a construct.
Ideological review, Civil/participant-based actions
Mixed methods
View an answer to compare with your own
Positivist/Critical rationalist (Normative science)
Rules exist for governing all things - some of which are hidden from the senses, but the truth is out there.
Hypotheses can be tested from which knowledge can be deduced.
Knowledge cannot be verified only falsified.
Null hypothesis

Reality is constructed by individuals within groups. Truth is a construct.
Discover the underlying meaning of events and activities in context. Reconstruct to create new insight
What is happening here? Why do you act this way?
Power is key in the construction and control of reality. Those with power control truth.
Discover the underlying meaning of events and activities in the context of power relations. Reconstruct to create new insight and empowerment
Who has power here and how is it exercised? How can the situation be changed?
Ideological review, Civil/participant-based actions
If it works then it must be true.
Whatever works or provides solutions to problems is ‘best’
Which action will lead to the desired outcome?
Mixed methods

As you learn and develop your thinking, your position will change, perhaps finding yourself swinging quite wildly at times as you read and understand new things. As you learn more, you will likely become more secure with your own views and how they fit, or change, with any particular context, purpose or time.

Key common features of qualitative research

Qualitative research seeks to find out how people and things interact in the environment (without isolating variables); it is considered real world research, where variables are not isolated or controlled.

Qualitative researchers seek to explore, explain and describe the experiences and meaning of people’s behaviour, experience and events. Qualitative research aims to generate insight, often in order to challenge received knowledge and accepted ‘facts’, and look beyond the statistical norm to improve people’s lives.

Take the concept of fatherhood, for example:[1]
A father holding his young child
Quality, not quantity

Meaning not measurement. What does it mean to be a good father?

Another father holding his young child
Generate hypotheses

Not test hypotheses. In what ways does sexuality shape views of fatherhood?

A Naval officer holding his child for the first time
Understand the subjective experience and create insight

Rather than objectively study. What's it like to become a father knowing you won't meet your child for months?

Language in coding and analysis

Because of the differences in epistemological approach in qualitative research, different language has developed. Qualitative methodology tends towards data-led coding, and may even use it exclusively e.g. Phenomenology, Grounded Theory. You can use qualitative methods (i.e. Interviews, observations, focus groups) but if you do not value the subjective experience then you are using a more positivistic approach that values objective understanding, such as Framework Analysis. You may use a mixed method approach, and many qualitative researchers will start with at least some theory to generate questions in the first instance, before focussing on the data.

Pre-determined codes
  • A priori/priori
  • Deductive
  • Etic
  • Theory-led
  • Applied to the data
  • Objective
  • Index
  • Top-down
Data-led coding
  • Emergent
  • Inductive
  • Emic
  • Experiential
  • Emerging from the data
  • Subjective
  • In vivo
  • Bottom up

Please be aware that this is an oversimplification, but it should help you to grasp the concepts so you can understand the subtleties when you read more in your areas of study. We will revisit this in ❔ Analyse and transform data.

Meta issues

What is a meta issue? Well, we’re not talking about the social media giant, or the specific term of ‘meta-analysis.’ We’re really talking about the things beyond philosophy that affect how research is conducted and why it is conducted in that way. Things that research about research has indicated need to be understood and governed to maintain its integrity and professionalism. You may also need to have specific knowledge of legal requirements too, (such as requirements for working or volunteering with vulnerable adults and children, administering medical treatment, or the keeping of animals), but that is beyond the scope of this course.

As you can imagine, there are many issues that are critiqued and considered as issues to be understood and governed across research. Much of the work that you do to ✏️ Design and Plan your research deals with the meta-issues of your research. However, as they are affected by your worldview, we mention them again here.

  • Project rationale - explaining the need for and purpose of the research
  • Design protocol - outlining methods of data collection and analysis, stages of the research or decision points and timings
  • Ethical review and risk assessments - demonstrating your understanding of the threats to the research and its stakeholders (including you and any participants), and your plans for managing and mitigating
  • Data management plan - how and where your data will be stored and results made accessible for future researchers
Ethical review

You may already be re-thinking some of your design, and may now want to build in some flexibility into your methods. Identifying or signposting potential choice points in your design make it clear to those assessing your proposals that you need to be flexible, but you also understand the limits of that flexibility. Doing this makes it easier and more transparent when you need to make changes to a design, return to a steering group with adaptations, or re-submit an ethics application. These will not be seen as retrospective changes (ethics panels do not normally allow retrospective changes), but be seen instead as as part of a coherent design that has outlined the broad need and limits to the flexibility from the outset (going back to an ethics panel for the approval of changes is a pain but you could put your research in jeopardy if you don’t get approval before you make them).

You will be expected to produce an array of documents during your research which may face public or panel scrutiny. The days of trusting that researchers are reporting research fully and accurately are over. Not necessarily because researchers have set out to deceive, but because poor research practices have damaged the reputation of research, especially in the world of pharmaceuticals, psychology and technology, where poor research practice has tipped over into research misconduct. We now also have the technological means for simple and wide-spread transparency of research conduct.

Research ethics are usually expressed in the form of principles or articles rather than as rules. You can expect to see adverbs such as ‘normally’ (or ‘not normally’), ‘aim to’, or the modal verb ‘should’ rather than must. These are not loop-holes that give you licence to ignore the principles. They are an acknowledgement of the complex nature of research. They indicate that where you are not fully meeting a principle that you have a reasoned argument for your actions.

The UK Economic and Social Research Council’s (ESRC) six key principles for ethical research[2] are:

  • Research should aim to maximise benefit for individuals and society and minimise risk and harm.
  • The rights and dignity of individuals and groups should be respected.
  • Wherever possible, participation should be voluntary and appropriately informed.
  • Research should be conducted with integrity and transparency.
  • Lines of responsibility and accountability should be clearly defined.
  • Independence of research should be maintained and where conflicts of interest cannot be avoided they should be made explicit.


Example: You wish to conduct covert research in a private members forum and gather data from the chat. Clearly as it is covert you are not meeting the principle of voluntary and informed participation, and neither are you being transparent.

Let’s add in the fact that you are already a moderator in this group, and you can see that there is a conflict of interest. The potential for a breach of trust and integrity here is very high.

It is almost certain that you will be refused ethical approval by these facts alone (ipso facto). However you will not be presenting those facts in isolation. The review panel would probably expect to you to explain:

  • The benefits to society in doing the research this way, proportionately balanced against the potential harms to the participants, you and the reputation of research
    • Who are your participants and what’s the nature of the forum? What normally gets discussed? What is not normally part of the discussion?
  • Why must the research be covert rather than overt? Are members anonymous in the forum?
  • What happens to the data that you do not have permission to retain and did not have permission to gather in the first place?
  • The steps you would take to debrief and gain permission post-event
  • How would you manage the conflict of interest as a current moderator? Will you create a new identity? What are the implications for your integrity of doing that?
  • …the list goes on

You may be thinking that your research is not particularly sensitive (I’m only talking to a bunch of my gaming mates about a game), but it is up to you to outline the steps you will take to maintain the integrity of your research. If there is a way of achieving similar or even less beneficial results that allows the research to be undertaken overtly, then you can expect to be steered in that direction and asked to resubmit.

Your professional organisation, department or your institution may have different perspectives on ethics and professional behaviours, or the legal basis of your responsibility. Additional principles, such as proportionality or financial probity, may be seen, or assume different levels of importance depending upon the nature of your research, the location of your research funders, your institution, and your participants. Generally speaking, for higher levels of research, don’t assume that your institution has suitable or high enough standards of ethics or oversight to satisfy your funding body, or your participants. Your exploration of this is an expected part of higher level research, typically required in a substantial independent ethical review process. Undergraduate studies are often assessed by individual tutors and only passed on for greater departmental review if greater ethical risks are identified in the research. Check your module and/or your departmental guidelines.

Question mark
Question mark
1. Take the ethical principles you are most likely to use (or use the table below).
Ethical principleWhat will you do, provide, negotiate, not do?
Benefit for individuals and society

(Minimising risk and harm)

(We will deal with Risk Assessments later)
Ensuring voluntary and appropriately informed participation
Conduct and management to ensure integrity and transparency in research
Ensuring and demonstrating respects for the rights and dignity of participants and groups to which they belong
Lines of responsibility and accountability and communication
Conflicts of interest

For each one, outline how you think you will demonstrate your adherence to the principles. It is easy to say that you respect the rights and dignity of your participants, but what will you do, provide, or negotiate over that demonstrates respect? And what will you not do?

Which parts will you discuss with colleagues now? Which parts will form part of your private reflection?

Question mark
Question mark
Now, you can do this next part privately or find a colleague or friend that you trust.

Take a while to imagine you are a participant in your own study, but the researcher is someone that you dislike. Be sure that it is someone you just dislike a bit, not hate with a passion. You see how I’m trying not to put you in a potentially psychologically risky situation. Knowing that you might feel uncomfortable is one thing, not knowing if I might provoke distress is possibly going too far.

Which parts of the process might you want to be done differently? Why? What changes would you make?

Now return to your list of principles and see if you need to change or add to your outline of how you will demonstrate your principles.

Risk assessment

Not all research will require an ethical review, but risk assessments are often used in isolation in that case. They tend to focus on handling hazardous materials and physically dangerous environments, but are present in different ways in interactions with people. Including the ethical risks in a risk assessment format means that you can structure and summarise your arguments so that panels can see ‘at a glance’ the breadth of your thinking. Risk is often expressed qualitatively as low, medium or high, although a numerical index might be used. This is viewed as a product of two functions, the possible harm (or threat), and the likelihood of that harm being done.

Example: simple risk assessment

Let’s take a low-risk situation that almost everyone would have experienced at School; examining pH in various solutions. Your science teacher would have assessed this risk (even if you didn’t). You can see in the simple table below that damage to eye-sight is perceived as greater harm than a slight burn to the skin. So even though it’s less likely to happen, the risk is considered medium. (If the possible harm is life-altering or permanent, the risk is always automatically considered high, no matter how unlikely it is to happen). The steps taken to reduce the harm done (washing off the weak acid) or prevent the harm from happening (wear eye protection) lower the overall assessment of risk. You can also see that the decision not to do something that others may think is advisable has been outlined i.e. wearing protective gloves makes the children clumsy and therefore accidents are more likely to happen, which increases the risk of someone getting hurt.

SituationRisk (Possible harm)LikelihoodRisk levelMitigationOverall risk level
Examining pH of solutions. 11 year olds mixing weak solutions of acid and alkali. Temporary damage to eye-sight Low Medium Mandatory eye protection and eye bath available. First aider on-site Low
Superficial burns to exposed skin Medium Low Use room with water source. Advice washing if contact occurs. (Use of gloves not advised as likelihood of poor handling increases the risk). Low
Superficial damage to clothing Medium Low Wear protective apron Low

However this example is a rather limited view of risk. There will be many things that cause a project to be labelled as ‘sensitive’ or high risk. In research where permanent or irreparable harm to a stakeholder is a possible outcome, however unlikely, the research could automatically be considered High Risk, such as permanent physical, psychological and emotional, financial or reputational harm. This does not necessarily mean that the research can’t be undertaken. However, there will be close scrutiny of how the risk is managed or minimised, and mitigated, as well as the plans for what would take place should the harm actually occur. These kinds of simple labels i.e. ‘sensitive’, ‘high risk’ and tabulated formulations are controversial and are disliked by some as they are seen as overly simplistic and lacking in detail. In these cases a narrative approach may be preferred. I find that in the absence of guidance, a combination of table and narrative really allows me to helpfully summarise the issues in the table with clarifying detail in the narrative.

Remember, the aim of ethical review is not to pretend that there are no risks. Rather it is to ensure you have removed unnecessary risk to you and your participants, and mitigated against and minimised potential harm.

You may be asked to make changes to your design. As the responsibility is yours, a more experienced panel will probably steer you with questions and comments rather than tell you directly what to do. If you have good reasons for ignoring the suggestions, detail them when you re-submit your application.

Example: comments that could helpfully steer you towards thinking more deeply about the risks in your research and some possible solutions to perceived risks.

Do you really need to do covert research? You may have planned to debrief your ‘colleagues’ when you leave the field, but what if they find you filming them, before you’ve had the chance to explain why?

Do you really need to research in those nightclubs when people are at their most drunk or volatile? Couldn’t you apply a Cinderella principle and always leave by midnight?

Couldn’t you speak to those young dancers somewhere other than the changing rooms? Have you considered your legal and ethical obligations if they reveal they are being harmed?

Ethical review may be presented as a tick-box exercise with ‘helpful’ templates, but the onus is on you to think things through. And neither should the review process bind researchers so tightly that no research can be done. It might mean that it can’t be done in the way you wanted. Despite seeming a bit intimidating, the process of review can actively help you identify, manage and mitigate against threats to you, stake-holders, including participants, the reputation of your institution, and ultimately the reputation of research.

Check your department; search for examples of real risk assessments in your field. Here’s one I prepared for the Qualitative Researcher Journeys Project. It’s part of Document 5: Protocol, ethics statement and risk assessment.

Data Management

As data is increasingly digitised, the volume and complexity has increased also. This poses threats (and opportunities) to the:

  • quality and reliability of the data processes
  • security of the data, and
  • reasonable access to data for posterity.
Quirkos logo
How to use qualitative analysis software (QDAS) for data management
“Feedback from our users tells us that project data management is one of the most important reasons that they use Quirkos, and we’ve designed the software to be as flexible as possible for all kinds of qualitative research projects”.

Data Management Plans are outlines of how you plan to manage those threats. It is good practice to have a Data Management Plan for any kind of research, however the scale of requirements and expectations of detail are very much less for a small undergraduate study compared with a large multi-phased, multi-institutional publicly funded body. So when you read what is required generally, don’t panic; moderate the scale of expectation to match the scale of your project. Check your departmental guidance - they may have some simple templates aimed at your level of study.

I find the FAIR principles helpful in guiding me in producing data management plans even though they are aimed at digital assets.

In order to comply with the FAIR guidelines, data should be;
  • Findable - for example, documents should be labelled and tagged appropriately, indicating file content and type, rather than vague terms such as ‘doc 1’.
  • Accessible - it’s alright to have security measures, but any authentication procedures (e.g. passwords) need to be clear, with open, free and universally implementable protocols.
  • Interoperable - for example if using branded software like Quirkos, the files should be transferable into other softwares of a similar type. Quirkos projects can be exported via the REFI-QDA protocol into other software.
  • Re-usable - It should be archived in a form that could be used by future researchers e.g. for secondary research purpose

In the Qualitative Researcher Journeys Project, (which had no requirement for a Data Management Plan as it was not publically funded) I created a Document Management Plan, which transparently addresses the need for project documentation, the methods of ensuring its protection and the ways in which it would be accessed and by whom. Feel free to critique its usefulness for your project.

Public funders in the UK have some very particular requirements for publicly funded research. But don’t worry, despite being quite extensive, they provide lots of guidance, and institutions have really upped their game in providing comprehensive and specialist support to staff and students in the last few years. Let’s consider detailed Data Management Plans as Optional for now, and you can return later when you know you need to.

Optional materials and resources

You have already covered a lot in this page, and if you are new to the concepts it can be a little overwhelming. You will probably need to do some more thinking and planning before you come back for the optional content that follows.

Epistemology and regimes of truth

If you are curious about what I describe as ‘regimes of truth’, these blogs are a good starting point. It doesn’t use that phrase, it does an excellent job (I can say that because I didn’t write it) of illuminating some of the norms and assumptions of positivist methods, as well as examining the concept of inter-rater reliability.

Post-qualitative paradigm

Going into the detail of the many epistemological differences within qualitative research is beyond the scope of the core of this curated course. There is a lot of material available, including our own blogs, for you to find out more. However, I wanted to draw your attention to a growing area of discussion in social research; the integration of human activity with technology, which has continued to push the ontological question of what it is to be human, and epistemic questions around the nature and existence of knowledge (e.g. can knowledge pre-exist human language?). Terms such as Post-qualitative, post-anthropocene and post-human have been around since the 1980s, but I notice they are becoming more mainstream. For more information on post-qualitative research you could start with Aghasaleh, R. St.Pierre, E.A. (2014), where they outline some of basics, which include:

  • “The Humanist paradigm is based on a hierarchical ontology in which human knower preexists knowing. This knower has innate agency as opposed to the known (world of reality) which is passive and lacks agency. In this hierarchical ontology, language is a transparent medium that can represent that reality. However, in a flattened ontology (Deleuze and Guattari, 1987/1980) subject, object, and language are always already entangled, and the “human” has no separate existence, but rather, all come into existence together…
  • …Importantly, post qualitative inquiry does not assume the ontology that grounds either the language or the subject of conventional methodologies…
  • …Its purpose is rather to destabilize and question the normativity of conventional research methodology in social sciences.”[4]

I would argue that you should not simply claim to be ‘post-qualitative’ in your world view without first understanding some of the conventional research methodologies you claim to be destabilising. This goes for any of the philosophical approaches you might claim to be using; structuralist, critical realist, constructivism, phenomenology and so on.

Further reading: Post qualitative inquiry
Data Management Plans

A general guide to what data management plans will need to cover (publicly funded research projects).[3]

  • Assessment and evaluation of data already available, and the need for the new data to be produced
  • Information about the new data, including methods for collection and analysis
  • Quality assurance of data. In qualitative research this could mean details of the ‘paper’-trail that you create when gathering the data (field-notes, recording equipment, record keeping, transcription protocols), and information on any analysis software or other tools, and any data validation approaches used, such as participant validation or peer review of data.
  • Security and back-up of data. Your institutions should have guidance on this (especially where there are legal implications), and where personal data is stored. You are trying to prevent data loss, version corruption, as well as keeping the data safe from those who have no right or need to access it
  • Management and curation of data. What you will do to ensure that the data can be understood and used correctly by others. It will help you too.
  • Expected difficulties in sharing data. Sometimes limits exist to what you can share. Any participants need to understand what sharing means, and any limits to anonymisation and confidentiality.
  • Consent, anonymisation and the enablement of data re-use
  • Copyright and intellectual property. Who will the data belong to?
  • Responsibilities. Who is responsible for meta-data, quality control and delivery for sharing or archiving?
  • Preparation of data for sharing and archiving. This especially relates to future use of the data, e.g. as a secondary data source.

UKRI (formerly Research Councils UK) has different advice for different disciplinary areas, for example Economic and Social Research Council (ESRC), Natural Environment (NERC) and Arts and Humanities (AHRC) and Medical (MRC).

However you can look up many public funders’ requirements (and sometimes examples and templates) for Data Management Plans from 89 different countries at DMP Online. However you should always cross-check for the latest requirements directly with the source, even though they move stuff around; a lot!

Top tip: Typically in linear models, as you finish one stage you would plan to make sure that everything is neat and tidy, making any necessary changes to the research plan, before you move on to the next stage of your research. As qualitative research is iterative, you will often find yourself starting a new part of the research cycle before you have truly finished an earlier part of the cycle. For instance, you may still be recruiting, whilst you are gathering data and starting your analysis. However, the principle of making sure that things are in order before you start a new phase remains true. Having key management mile-stones throughout your project delivery is a good way to make sure that you don’t lose track, and ensure your well intentioned plans are matched by a professional reality. It’s reassuring to know that one of the key functions of Quirkos (and other CAQDAS) is data management.

Resources: Ethics
Optional task
Use the table and headings below to start a risk assessment for your research project. Add (or remove) items as appropriate for your project.
Situation typeRisk (Possible harm)LikelihoodRisk levelMitigation
Threats to project completionFailure to recruitMedium
Timings of authority to access files
Burden on participants
(Design requires multiple engagements between researcher and participants)
There is no requirement to engage beyond first contact. Explicit withdrawal points are clearly identified in shared project plan
Early withdrawal of participants
Physical safetyParticipantsLowAdult participants will be in their own home, exposed to no more than normal domestic hazards.
ResearcherLowPractical advice is given here
Damage or theft of equipment
Psychological or emotional harmExperiencing distress at unexpected recall of emotionally challenging eventsHighProject purpose (Exploring grief at parental loss in old age) is explicit. Project information will be distributed to participants.


Example project materials

Remember you can see example documents here: Quirkos - Research Project Information or if you want to see something independent from Quirkos have a look at the Irish project, Beyond Opposition.

Tell us what you think!

We'd love to hear from you so we can make this course as useful as possible. If you'd like to leave feedback, suggestions or comments, please use the button below.

Fill out our survey

Try today!

Ready to give Quirkos a try? Register for a free 14-day trial of Quirkos today,
with no restrictions on features or projects.
with no restrictions on features or projects.

Want to learn more? Read more about our features or see Quirkos in action!