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What is qualitative and quantitative research? 

Before a researcher begins their research, they would need to establish whether their research results will be quantitative or qualitative. 

Qualitative research observes any subjective matter that can’t be measured with numbers or units, usually answering the questions “how” or “why”. This type of data is usually derived from exploratory sources like, journal entries, semi-structured interviews, videos, and photographs.

On the other hand, quantitative research is numeric and objective, which usually answers the questions “when” or “where”. This data is derived from controlled environments like surveys, structured interviews, and traditional experimental designs. Quantitative data is meant to find objective information.

What are the main differences between qualitative and quantitative research?

The main factor of differentiation between qualitative and quantitative data are the sources that the data is gathered from, as this effects the format of the results. 

Sources of Qualitative Data	Sources of Quantitative Data
Participants’ recollection of events	Polls, surveys and experiments
Focus groups	Databases of records and information
Observing ethnographic studies	Analysis of other research to identify patterns
Semi-structured interviews	Questionnaires with close-ended questions
Questionnaires with open-ended questions	Structured Interviews

When to use qualitative and quantitative research? 

When conducting a study, knowing how the results will be depicted drive the methodology and overall approach to the study. To understand whether qualitative or quantitative research results are best suited for your current project, we take a deeper dive at the several advantages and disadvantages of each. 

1. Qualitative research

Advantages: 

• Allows researchers to understand “human experience” that cannot be quantified
• Has fewer limitations, out-of-the-box answers, opinions and beliefs are included in data gathering and analysis
• Researchers can utilise personal instinct and subjective experience to identify and extract information
• Easier to derive and conduct as researchers can adapt to any changes to optimise results 

Disadvantages:

• Responses can be biased, as participants may opt for answers that are desirable. 
• Qualitative studies usually have small sample sizes, this impacts the reliability of the study as it cannot be generalised to certain demographics.
• Researchers and other’s who read the study can have interpretation bias as the information is subjective and open to interpretation

2. Quantitative research

Advantages: 

• Usually observes a large sample, ensuring a broad percentage is taken into consideration and reflected
• Produces precise results that can be widely interpreted
• Minimises any research bias through the collection and representation of objective information
• Data driven research method that depicts effectiveness, comparisons and further analysis.

Disadvantages: 

• Does not derive “meaningful” and in-depth responses, only precise figures are included in findings
• Quantitative studies are expensive to conduct as they require a large sample 
• When designing a quantitative study, it is important to pay extra attention to all factors within the study, as a small fault can largely impact all results.

How to effectively analyse qualitative and quantitative data?

Since the data collection method for qualitative and quantitative studies are different, so is the analysis and organisation of the gathered information. In this section, we dive into a step-by-step guide to effectively analyse both types of data and information to derive accurate findings and results. 

Analysing qualitative data

1. Types of qualitative data analysis

Content analysis	Identifies patterns derived from text. This is done by categorising information into themes, concepts and keywords.
Narrative analysis	Observes the manner in which people tell stories and the specific language they use to describe their narrative experience.
Discourse analysis	Used to understand political, cultural and power dynamics. This methos specifically focuses on the manner in which individuals express themselves in social contexts.
Thematic analysis	This method is used to understand the meaning behind the words participants use. This can be deduced by observing repeated themes in text.
Grounded theory	Mostly used when very little information is known about a case or phenomenon. The grounded theory is an “origin” theory and other cases and experiences are examined in comparison to the grounded theory.

2. Steps to analyse qualitative data

1. Once your data has been collected, it is important to code and categorise the information to easily identify the source. 
2. After organising the information, you will need to correlate the information logically and derive valuable insights.
3. Once the correlations are solid, you will need to choose how to depict the information. In qualitative data, researchers usually provide transcripts from interviews and visual evidence from various sources. 

Analysing quantitative data

1. Types of quantitative data analysis

Descriptive analysis	This method focuses on summarising the collected data and describing its attributes. This is when mean, median, mode, frequency or distribution is calculated.
Inferential analysis	This method allows researchers to draw conclusions from the gathered statistics. It allows researchers to analyse the relationship between variables and make predictions; this includes cross-tabulation, t-tests and factor analysis.

2. Steps to analyse quantitative data

1. Once the data has been collected, you will need to “clean” the data. This essentially means that you’ll need to observe any duplications, errors or omissions and remove them. This ensures the data is accurate and clear before analysis. 
2. You will now need to decide whether you will analyse the data using descriptive or inferential analysis, depending on the gathered data set and the findings you’d like to depict.
3. Now, you’ll need to visualise the data using charts and graphs to easily communicate the information in your research paper. 

Conduct your research on Zendy todayThis blog thoroughly covered qualitative and quantitative data and took you through how to analyse, depict and utilise each type appropriately. Continue your research into different types of studies on Zendy today, search and read through millions of studies, research and experiments now.

DOI is short for Digital Object Identifier. It is a unique alphanumeric sequence assigned to digital objects, it is used to identify intellectual property on the internet. DOI’s are usually assigned to scholarly articles, datasets, books, videos and even pieces of software. 

Understanding DOI’s

The digital object identifier is a unique number made up of a prefix and suffix, segregated by a forward slash. 

For example: 10.1000/182

The sequence always begins with a 10. The prefix is a unique 4 or more digit number assigned to establishments and the suffix is assigned by publisher as it is designed to be flexible with publisher identification standards.

Where can I find a DOI?

In most scholarly articles, the DOI should be on the cover page. If the DOI isn’t included in the article, you may search for it on CrossRef.org by using the “Search Metadata” function.

How can I use the digital object identifier to find the article it refers to?

• If the DOI starts with http:// or https://, pasting it on your web browder will help you locate the article.
• You can turn any DOI starting with 10 into a URL by adding http://doi.org/ before the DOI. For example, 10.3352/jeehp.2013.10.3 becomes https://doi.org/10.3352/jeehp.2013.10.3
• If you’re off campus when you do this, you’ll need to use this URL prefix in front of the DOI to gain access to UIC’s full text journal subscriptions: https://proxy.cc.uic.edu/login?url=https://doi.org/ . For example: https://proxy.cc.uic.edu/login?url=http://doi.org/10.3352/jeehp.2013.10.3

Strengths of Digital Object Identifier

• Permanent identification: Digital object identifier provides a permanent link to digital content, making sure it remains accessible even if URL or metadata is updated. 
• Citations: It uniquely identifies research papers, which facilitates accurate referencing and citing.
• Interoperability: DOIs are widely recognized as they can be utilised across different platforms, databases and systems.
• Tracking and metrics: DOIs provide key information like publication date, authors, keywords and more. This can be used to track usage metrics, measuring impact and improving discoverability
• Integration with services: DOIs are integrated with various tools like reference managers, academic search engines, and digital libraries. These mediums enhance the visibility and accessibility of research material with DOIs. 

Limitations of Digital Object Identifier 

• Cost: Digital object identifiers are costly for smaller organisations or individual researchers. While some services offer free digital object identifier registration for certain content, there may be fees associated with others, particularly for maintenance and updates.
• Accessibility: There may still be barriers to access for individual researchers or organisations in regions with limited resources. Ensuring equitable access to digital object identifier services and content remains a challenge.
• Content Preservation: While the sequence provide persistent links to digital content, they do not guarantee the preservation or long-term accessibility of that content. Ensuring the preservation of digital objects linked to DOIs require additional efforts and infrastructure beyond the system itself.
• Granularity: Sequences are assigned to individual digital objects, such as articles, datasets, or books. However, there may be cases where more granular identification is required, such as specific sections within a larger work or versions of a dataset. Addressing these granularity issues within the digital object identifier system can be complex.

Conduct your research on Zendy today

Now that you’ve gained a better understanding of how DOI works and impacts the world of research, you may begin your search and find your next academic discovery on Zendy! Our advanced search allows you to input DOI, ISSN, ISBN, publication, author, date, keyword and title. Give it a go on Zendy now.

This January, the Forum of Open Reseach MENA hosted its first community development activity of 2024. The “Decolonising Open Science Symposium: Dismantling Global Heirarchies of Knowledge” addressed the influence of western prominence on knowledge distribution and research, highlighting how these ideologies and standards impact the Arab region.

Within the landscape of research, conversations and collaborations not only address inequalities but also break barriers to accessibility. In this blog, we interviewed Nahil Nassar who is the community engagement manager at the Forum of Open Research MENA. At the symposium, Nahil touched on the work that open science has in building stronger foundations for diverse research consumption and the biases that exist in the research landscape. We take a deeper dive into this conversation. 

1. How does F.O.R.M. facilitate conversations around decolonising academia?

FORM is a community based organisation that centers its attention on the Arab region. That means prioritising Arab voices in academia to develop a regionally and culturally relevant model of Open Science to implement across the board.

While we do, of course, work with organisations that are based in the Global North, we try to be transparent when it comes to power dynamics, and recognise that we are only as strong as our community. 

2. What role does open science play in escalating research outside western europe?

Open Science has the potential to really build an even playing field for researchers in the Global South because of its financially and digitally accessible model. In its best form, Open Science should allow researchers from the Global South to publish their work without limitations in cost or geography.

The problem is that Open Science publishing is not always functioning in its most optimum form, and things like APCs, metric frameworks, and language hierarchies (English being a dominant language across the research landscape) can still limit researchers in the same ways that traditional academic publishing models do.

3. What are some biases that exist in the open science landscape?

A major bias that comes out of the Open Science landscape, especially when it comes to the Global South, is that Open Science research is bad research. There’s this assumption that if research isn’t published in perfect English, or focuses on a very niche subject that’s really only relevant to specific local contexts, then that means the research is either low quality or irrelevant. 

This is especially because of how research is prioritised in its value these days, and this is one of the many places where commodification enters the conversation as a major issue. Often times, major funding is only allocated to research that is deemed important by multinational corporations or prestigous research institutions in the Global North who sort of set the agenda of what is necessary to study and what isn’t – and these topics are usually prioritised based on the needs of these entities and their contexts, and completely ignore the localised needs of researchers in the Global South, who then don’t have access to that same funding. 

4. Please explain how absolute objectivity is colonial ideology

This is a really interesting ideology to ponder on in decolonial discourse, because it seems very out there to say that there’s no such thing as objective truth, especially in a world that is run by scientific innovation. The idea of objectivity may seem to be clear and cut, but it goes back to the idea of intellectual dominance and colonialism. There was an ideological hierarchy set by colonial powers that placed their “truth” as the only “truth”, and took objectivity to mean that their truth is the only one with any substance or value. 

Many indigenous knowledge systems question this idea of absolute objectivity, because it is often rooted in inherently colonial, patriarchal, and violent understandings of nature, human experience, and society. I was first introduced to this philosophy through postcolonial gender theory, where researchers like Vandana Shiva questioned the very idea of scientific knowledge as we know it today as something that was forced on us as the only virtuous fact, but is sometimes actually the most harmful opinion. 

5. What is the direct impact of colonisation on knowledge production today?

The impact of colonisation on knowledge production today can be found in a plethora of arenas. While colonisation as we once knew it is not nearly as prominent as it was in the 19th and 20th centuries, neo-imperial and neo-colonial ideologies are still very much strong holding the majority of the world’s systems. You can see legacies of it in how we think about scientific studies, methodologies, or even the metrics that we use to classify ‘good’ and ‘bad’ research. 

It informs how we think about credibility, and determines who gets to speak the loudest and whose voice gets silenced. It marginalises researchers who use indigenous knowledge methodologies (often rooted in intuition and connection to land and spirit) and prioritises the voices of liberal scientists who believe in objective fact rooted in numbers and rationality. 

Overall, it prioritises knowledge produced and disseminated by Western organisations and researchers that then have an impact on Western communities, and leave the global majority out of the conversation.

Watch the webinar here