




































CHAPTER  2: 
MAKING MEANING OUT OF BIG DATA IN 

HEALTHCARE: VISUAL DESIGNERS’ PERSPECTIVE 

 

Contributed by 

Benjamin Eni-itan Afolabi 

 

INTRODUCTION 

Designing is a procedural activity that can be practised from 

diverse perspectives; it involves making plans to create a needed 

solution. Visually, a design is meant to be specific in the end result 

and that differentiates it from ‘art’ which often tilts toward more 

aesthetics. This simply does not mean a design cannot be beautiful; 

in essence, the crux of a design is both ‘function’ and ‘aesthetics’. 

A design meant for the sight is visual, this has to do with functional 

art that can be seen, felt or touched; Such design adopts graphics 

strategically to create, refine or advance a solution. It is 

exemplified in package design, branding, information/ book 

design, prints, advert campaigns, television montages, web design 

and development, interface design, user experience design, 

multimedia authoring, industrial art and product design among 

others. Additionally, it (i.e. visual arts/ design) is a branch of 

creative arts, sectioned into Fine Arts and Applied Arts (see Fig. 

1). As a result, it is about creativity which defines the feel and 

uniqueness of every result. Creativity is the ability to use clear 

imagination in the development of new and original ideas or things, 

especially in the realm of art (Bravolol, 2022). Apart from the skills 

of the designer which also matters, if a visual design will be 

outstanding, creativity must not be trivialised. The examples listed 

above apply to virtually all walks of life including the health sector. 

Print and online materials are used in healthcare while health 

practitioners make use of essential multimedia applications in daily 



Making meaning out of big data in  Healthcare:… 

21 

 

medical practices. Many products are developed innovatively, 

incorporating visual design. They are relevant medically and non-

medically for both the patient and the healthcare giver. This is 

notably exemplified in digital products that store and retrieve 

health-related data in many folds. The data are so numerous that 

they are classified as ‘big data’ – non-organised, semi-structured or 

structured information. 

Ordinarily, the health institutions: clinics or large hospitals 

rely on patients’ records or health data to cater for their patients’ 

treatment. Care for a patient can take many forms but can be 

facilitated when quality data are available. Health facilities in 

Nigeria are not faring badly but in practice, they are yet to fully key 

into health digitisation. Photius (2019) recorded that health in 

Nigeria was rated fourth worst in the world, while this is not good, 

it calls for improvement. The record was later amplified in 2023 in 

the expression of Schmale Matthias, UN Resident and 

Humanitarian Coordinator, captured by Habib (2023). The 

Coordinator lamented that Nigeria lags in the realisation of the 

Sustainable Development Goals (SDG 3 inclusive). The highlight 

of goal 3 by the UN is that there should be good health and well-

being for all. Regrettably, achieving Sustainable Development 

Goals in Nigeria remains a fantasy without a more inclusive, multi-

dimensional approach (Alozie, 2020). This shows that all hands 

must be on deck for concrete results in the area of health; but the 

Visual designer is only a creative personnel, does that mean such 

an expert cannot make an impact health-wise? Thus, it is worthy of 

exploration to determine how such a professional can use visuals 

to promote care especially from the point of meaningful data 

storytelling, hence this discourse. 



Benjamin Eni-itan Afolabi 

22 

 

 
Figure 1: Branches of Visual Art/ Design under Creative Arts in the 21st 

Century. Source: Afolabi et al (2023); 
https://doi.org/10.33093/ijcm.2023.4.1.1 

 

The Visual Designer: Skilled or Talented? 

The goal of visual design is either to: promote, persuade or 

influence the people (i.e. public) through creative work; due to this, 

the designer is expected to be well-equipped for the task. For the 

sake of clarity, a Visual Designer uses media elements to create 

artistically pleasing designs. The principles of design are further 

used in structuring every visual element adopted for a particular 

creative work. Graphics, pictures, colours, shapes, typography, 

lines etc. form the contents, and together with the principles, are 

used to improve user experience. The role of a visual designer is 

also to create a layout and solidify brand identity. He or she 

specialises in the design, look and feel of digital assets such as 

websites and applications. A Visual Designer understands clearly 

the contents therefore in agreement to General Assembly (n. d), an 

online platform on education, the knowledge of visual design is a 



Making meaning out of big data in  Healthcare:… 

23 

 

powerful extension to a variety of professional backgrounds. As a 

result, visual creators also understand the ideologies behind 

‘visual’ as an entity. Notable visual concepts that empower the 

Designer which are equally germane in art and design practises 

include: visual literacy, visual representation, visual properties, 

visual elements, visual grammar and metaphor, visual perception, 

visual display and visual culture among others. 

Thus, from the foregoing, the qualities of Visual Designers 

are enormous. However, as core attributes, they must possess eyes 

for details, be well-educated, patient and also have a good sense of 

communication. Afolabi (2022) maintained that multimedia 

Specialists should embrace empathy and in so doing develop 

contents for therapeutic purposes. Logically, from inference, 

empathy is a good quality for a designer but should not be practised 

by a segment of Designers but rather by all Visual Designers. When 

this attribute is put into practice, the Visual Designer will design 

from the perspective of the client or user of the design work. In all, 

the answer to the question that a visual designer is perhaps skilled 

or talented boils down to the fact that talent without the right artistic 

skills will not yield the right creative results especially as the duo 

(skill and talent) are entirely different sets of qualities. However, 

while talent is innate (natural), skill is learnt; but the fact is, points 

discussed above that are involved in visual arts and design practices 

are certainly beyond solely talent, they must simply be learnt. A 

Visual Designer who is talented and simultaneously equipped with 

essential 21st-century design and technological skills will perform 

excellently in any field of art and design. Interestingly, if a 

Designer lacks artistic talent but is amply filled with the necessary 

skills, then such an expert is reclining on a solid foundation. 

Therefore, it is not just about talent or skill that matters, rather, the 

mean to a result (of effective and creative visual solution) which 

equally speaks volumes. They are the yardsticks or parameters that 

define a Visual Designer. 

 



Benjamin Eni-itan Afolabi 

24 

 

Healthcare in Nigeria: An Overview 

Among the (social) institutions that make up society is the 

healthcare system which is structured into Primary, Secondary and 

Tertiary healthcare delivery models. Basic health centres and 

Comprehensive health facilities make up the Primary Healthcare 

System while the various General Hospitals are classified as 

Secondary. The tertiary health institutions are Federal Medical 

Centres/ National Hospitals, University Teaching and Specialist 

Hospitals. The basic healthcare system caters for the health needs 

of the grassroots community in rural settings; any health challenge 

or case that cannot be treated at this level is referred to the 

secondary level and in turn, the tertiary facilities. The CMD (Chief 

Medical Director) heads the health facility especially at the 

Secondary and Tertiary level while the Officer in Charge (OIC) 

oversees the day-to-day affairs of the Basic/ Comprehensive health 

centres. Common wards in a health facility in Nigeria include: 

Maternity, Neonate division, Paediatrics, Dentistry, Surgery, 

Emergency wards, Guidance and Counselling unit, Intensive Care 

Unit, General Medicine ward, Psychiatric, Oncology, and 

Outpatient Services among others. Hence, different healthcare/ 

medical experts in different areas of specialisation are engaged to 

practice professionally and solve all manner of health issues, 

thereby promoting healthy lifestyle. 

From the foregoing, healthcare as a setup regulated by the 

federal and state government through assigned agencies/ ministries 

is not an institution that gulps low funds for running its operations 

and maintenance. Synchronously, irrespective of the Wards or 

Units in any of the delivery models, they all rely on data i.e. health 

information to appropriately discharge their duties and give out 

care. Sadly enough, healthcare in Nigeria is poorly funded 

(Nwachukwu, 2021; Olomola, 2009; & USAID, n.d) while the 

electronic record system is not well integrated and in some cases, 

non-existent (Teniola, 2023, Afolabi, 2021 & Farouk et al, 2023). 

Little wonder, a World Health Organisation survey conducted in 



Making meaning out of big data in  Healthcare:… 

25 

 

the year 2000 classified Nigeria’s healthcare system as the fourth 

worst in the world by ranking it- 187th globally (Photius, 2019 & 

WHO, 2000). However, in a report by Muanya and Ozioma (2021), 

Oladigbolu, National Chairman, the Association of Community 

Pharmacists of Nigeria (ACPN) claimed Nigeria has improved by 

moving from 187th to 163rd. However, the progress still calls for 

serious improvement, because the 163 simply depicts the 28th 

worst health care system in the world. This point is out of the 191 

countries in the world that were assessed in the level of compliance 

with the Universal Health Coverage. 

 

The Concept of Big Data 

This is the era of IoT (Internet of Things), as a result, big data which 

is all about concrete information tilts toward more digital trends; 

but that does not mean information cannot be experienced in the 

conventional settings i.e. non-digital mode. Information is crucial 

and entails the act of collecting facts about a specific subject; the 

facts are accessible data. They are essential in making facts known 

and for the advancement of knowledge. “Big data is the fuel 

that delivers real-time analytics” (Moore, n.d.) because it is about 

“collecting and analysing large amounts of data; to generate 

actionable insights that an organisation uses to enhance its 

different aspects” (AnalytixLabs, 2021). Hence, the idea behind 

big data is projected in: Volume, Velocity and Variety. These are 

the three basic characteristics of big data (InterviewBit, 2023). The 

loads of information trooping in on data-driven applications: web, 

mobile, social media feeds etc. are always plenty (i.e. in volumes); 

with a dynamic speed. Resultantly, the rate at which information is 

gathered and processed is the velocity and this is for information 

(i.e. data) which could be in varieties: structured and semi-

structured (or both) or unstructured i.e. completely disorganised set 

of information. Basically, conventional data are always structured 

and fit easily into a relational database; whereas with the advent of 

big data as an innovation, information became more of new 



Benjamin Eni-itan Afolabi 

26 

 

unstructured data (InterviewBit, 2023). For clarity, examples of 

structured data are information stored in the form of tables and 

spreadsheets. They are processed by organising them; stored and 

retrieved in a fixed format. Unstructured data have no ‘known’ 

structure and are heterogeneous information from search engines, 

webpages, videos, images, texts, audio etc. Semi-structured data is 

both structured and unstructured such as web content (with 

unstructured log files, transaction history files etc.) and a table 

definition in a relational Database Management System. The table 

has no classification into a definite database but is tagged for 

element distinctiveness (AnalytixLabs, 2021 and Adilin, 2021). 

However, “unstructured and semi-structured data types including 

video, text, and audio need extra pre-processing to determine 

meaning and support metadata, the context around the data itself”. 

(InterviewBit, 2023) 

Other salient features of big data (see Fig. 2) include 

veracity (i.e. inconsistencies witnessed in data variations), 

variability, visualisation (or visual representation) and value 

(Moore, n.d). It is to be noted that raw data are meaningless unless 

processed for tangible and meaningful information; thus ‘value’ as 

a feature of big data is the most important (InterviewBit, 2023). 

Logically, apart from other means, value can also be achieved in 

two ways, and that is technologically and creatively. Many 

technological tools are readily available for processing big data and 

good examples of these advanced tools among others are: 

‘Tableau’ and ‘DataWrapper’. They both support big data analysis 

via creative approaches such as visualisation; a core area of 

expertise attributed to the Visual designer. Notably, while 

‘Tableau’ is proprietary, acquired by ‘Salesforce’ in 2019 (Nat, 

2019), ‘DataWrapper’ the other hand, is freeware, common among 

program developers and News journalists. It is also meant for 

design experts. The advent of big data can be likened to innovation 

spurred by technology in phases. It was conceived as a concept 

many decades ago and subsequently put into practice which 



Making meaning out of big data in  Healthcare:… 

27 

 

evolved into a systematic approach till today. Despite many 

versions of report about the realisation of big data, one common 

trait in its development is that the rise in big data started in the 90s 

– the period of Computer age (Dekate, 2022). Also, “from the early 

2000s, the internet and corresponding web applications started to 

generate tremendous amounts of data” (BigData Framework, n.d). 

Currently, the rapid acceptability of mobile technology and 

devices, also aided the embrace and advancement of big data.  

 

 
 

Figure 2: Characteristics of Big Data, including Visualisation practised by 

Visual Designer. Source: Afolabi’s Compilation (2022) 

 

The essence of big data is that it will allow businesses, firms and 

organisations, including healthcare to utilise voluminous 

information effectively. Trends, patterns, and behavioural acts in a 

given situation are easily identified with big data analytics which 

would ordinarily be difficult to detect in conventional data 

processing means. It is thus easy to sum up that results from big 

data operations will foster decision-making in any organisation. 

Investing appropriately will be easy when big data solutions have 

been adopted by organisations that transact based on heavy 

information such as healthcare. Interestingly, when data are 

processed, storing such comprehensible information becomes easy 

as the space needed would be minimal when compared to storing 



Benjamin Eni-itan Afolabi 

28 

 

raw data which often are bulky. ‘Big data analytics’ is important 

because it applies to virtually all walks of life especially healthcare. 

Summarily, “big data includes multiple processes: including data 

mining, data analysis, data storage, data visualization, etc. The 

term ‘big data’ refers to collecting these processes and all the tools 

that we use…” (AnalytixLabs, 2021).  

 

Nature of Big Data in Healthcare 

Data interpretation could become a complex activity, especially 

with the vast amount of information involved in big data. At the 

same time, data can become valueless when it makes no meaning, 

importantly when difficult to interpret. This is the crux of 

visualisation, to simplify the logical (mental) process, create 

meaning and form part of the communication and data 

dissemination channel. Data record in healthcare employs either 

the traditional means using manual registers or electronic 

mediums. Data itself includes: patients’ health details, vaccine 

distribution logs such as during the COVID-19 pandemic, 

community immunisation records, disbursement logs of 

intervention funds for health ministries, agencies/ parastatals in a 

country, records of epidemic and several other diseases, birth 

records among others. All the manually recorded different 

information (varieties) are usually piled up or in some cases 

sourced/ collated from a large population. Hence, they are plenty 

(i.e. voluminous) – these are attributes of ‘big data’. Digitally, 

smart devices such as mobiles and wearables generate lots of health 

data that may be difficult to comprehend; such data are meant for 

tracking and diagnosis. Interviews and Surveys, structured or 

unstructured, captured manually or electronically also make up big 

data in healthcare; importantly, if they are experienced on a large 

scale. 

 

 



Making meaning out of big data in  Healthcare:… 

29 

 

sVisual Designer and Data Mining for Health Infographics: 

Methods cum Benefits 

In big data operations, the Visual Designer would be concerned 

with visualisation since that is part of the core areas where his/ her 

expertise will be felt among the 7 Vs (See fig. 2). This professional 

is expected to ‘mine’ the data by creating information graphics: 

charts, lines, tables, illustrative pictures among other visual aids 

that best interpret and present the raw/ processed dataset. The 

objectives of visualisation in practice entail: 1. comprehension, 2. 

retention and 3. appeal (see fig. 3); especially to communicate 

information in the most comprehensible form. The order is not 

fixed but can be altered at will by the Designer, based on the 

purpose of creating the information graphics (Lankow, Ritchie & 

Crooks, 2012). “A graphic created with a commercial interest in 

mind will have many different priorities… the order of priorities of 

the commercial marketing graphic would be appeal, retention and 

then comprehension. Publishers that create editorial infographics 

have a slightly different mix: appeal, comprehension and 

retention” (Lankow, Ritchie & Crooks, 2012, p. 38-39). In 

healthcare, relying on Baruah (2020), the focus of the visualisation 

would rather suggest a mix that prioritises first, comprehension, 

retention and then appeal. Baruah (2020) listed criteria for 

visualising (data) information that, the source of data should not be 

instantly visible; perhaps abstraction. This is because information 

visualisation transforms non-visual to visual; more reason image is 

generated from the entire process. Lastly and importantly, data 

must be comprehensible and readable. The last criteria is the main 

reason for the mix as regards health. However, creative solution 

has no boundary, hence, some practical cases (e.g. health 

awareness/ sensitisation development) would rather warrant that 

appeal should be treated as most important then comprehension 

and retention. 



Benjamin Eni-itan Afolabi 

30 

 

 
Figure 3: Objectives of visualisation 

Source: Lankow, Ritchie & Crooks (2012) 

 

The view of Baruah on data readability is also based on clear 

reasoning that unnecessary details should be avoided which is in 

line with Knaflic (2015) who also opined that de-cluttering is 

essential to achieving a meaningful data visualisation. 

“Communication is most effective when you say neither more nor 

less than what is relevant to your message. Don’t make people 

wade through meaningless visual content in your display to find 

what matters” (Few, 2006, p. 6). The zig-zag method has also been 

suggested as a solution, notably in the area of visual design. The 

eyes scan through contents or across the screen in a zigzag motion 

(i.e. Z): Top Left – Top Right – Across – Down Left – Down Right. 

Hence, important elements or visuals must be placed from the ‘Top 

Left’ to the ‘Top Right’ first (Knaflic, 2015). Interestingly, 

designing creative visual content is also believed to be both 



Making meaning out of big data in  Healthcare:… 

31 

 

systematic and strategic. The former, in the words of Baruah (2020) 

means a definition of a problem such as identifying the need/ 

preference of the end users as regards information/ data 

visualisation. The next is to define the data set (for visual 

representation) which could be: ordinal, categorical, interval, 

continuous, nominal and discrete (Lankow, Ritchie & Crooks, 

2012). They are to be in the right category for mapping. Thirdly, 

the definition of attributes and dimensions that would depict the 

data matters. Attributes are the variables which could be in 

multiples, single or double and after that is the sorting out of data 

structure: linearly, in tabular or hierarchical form etc. (see Fig. 4).  

 

 
Figure 4: Types of Data Structure/ Organisation 

Source: Tidwell (2011) 

 

 



Benjamin Eni-itan Afolabi 

32 

 

Lastly, the determination of the amount of interaction preferred by 

the user and likewise the right format for the visual content. 

Lankow, Ritchie & Crooks (2012) tagged the format as a vehicle 

comprising: static, motion and interactive models. Strategically, 

“when you use cutting-edge tools and technologies to stitch 

together different metrics (i.e. data) and reveal the relationships 

between them, you are virtually building an entire world of 

narratives”. (Rodriguez, 2022). This is known as data story telling 

(Knaflic, 2015); the idea behind this approach is to allow the data 

to narrate its own story to derive meaning (see Fig. 5) while visuals 

are embedded to further enrich essential details. This kind of 

information visualisation, according to Dykes (2016) is persuasive, 

engagement oriented and aids memorability. Concurrently, 

persuasion is a core attribute needed in healthcare. It therefore 

approaches fitting for healthcare (big) data simplification. Positive 

persuasion is needed to make patients believe in the treatment 

being administered or for the public to adjust and respond to a 

tailored health campaign. Government and Stakeholders, in some 

cases, would need to be persuaded as well to rise to health matters 

and make impactful contributions. Originally, the strategy was 

postulated for business enterprises but by operation, it can also be 

applied to healthcare. It should be marked that, though ‘health’ is 

about care and patients, yet, it can also be seen from the lens of a 

business. However, irrespective of the motive, whether patient-

oriented or business inclined, the strategy fits perfectly into big data 

in healthcare. 

 



Making meaning out of big data in  Healthcare:… 

33 

 

 
Figure 5: Strategic Development of Information Visualisation via 

Storytelling Approach. Source: Dykes (2016) 

 

By operation, Rodriguez (2022) maintained that to achieve the 

right approach, firstly, a plotline with a clear objective is to be 

developed, which is the foundation for a good data story. The 

second is to create a narrative that holds attention while the data 

tell the story. Fourthly, the recipients of the information visuals are 

to be categorised by their level of understanding of the data story 

and finally, incorporation/ integration of the right visuals. The last 

bit is to be observed relying on pre-attentive attributes (see Fig. 6) 

and Gestalt principles. The data structure used (see Fig. 4) signals 

to the user, subconsciously, a lot about the nature of the data. It is 

very easy for the brain to quickly process pre-attentive features. 

Therefore, variables with similar attributes must be weaved or 

placed together. Irrespective of the big data, they simply convey 

the information at once, even before the viewer pays conscious 

attention (Tidwell, 2011; Lankow, Ritchie & Crooks, 2012). Pre-

attentive attribute and Gestalt principle of visual perception (see 

Fig. 7) are about similarity, enclosure, proximity, continuity, 

enclosure and closure (Knaflic, 2015). These together with other 



Benjamin Eni-itan Afolabi 

34 

 

visual elements: especially colours/ white space, to draw attention 

(Knaflic, 2015; Tidwell, 2011; Lankow, J., Ritchie J. & Crooks, R., 

2012) are needed for orderliness and solution-based visual design 

for data communication. 

 
Fig. 6: Pre-attentive attributes guiding placement of visuals to make meaning 

out of big data. Source: Tidwell (2011); Lankow, Ritchie & Crooks (2012) 

 

In the same vein, the logic to achieving a catchy, compelling and 

engaging narrative is to allow the audience to choose the story they 

see and by using Exploratory Data Analysis (EDA) with interactive 

visuals, audiences would be involved in the visual message. Also, 

the data can dictate the narrative story solely by being truthful, with 

no manipulation of data. Visuals that combine well with the data 

should be adopted while standardised units be considered; 

precisely when comparisons are involved in the (big) data story 

(Rodriguez, 2022). 



Making meaning out of big data in  Healthcare:… 

35 

 

 

 
Fig. 7: Four Gestalt principles for manipulation of layout for content/ 

visual display. Source: Tidwell (2011) 

 

The actual focus of the big data production will also influence the 

narrative for visualisation. Basically, ‘big data analytics’ is either: 

descriptive, diagnostic, predictive or prescriptive; they are simply 

four in that hierarchical order. The last analytic “has good use in 

the healthcare industry. It can be used to enhance the process of 

drug development, finding the right patients for clinical trials etc.” 

(Pathak, 2021). The strategy described above for visualising big 

data will then have to be executed through the lens of either of the 

four analytics, important as the case may be. This must be 



Benjamin Eni-itan Afolabi 

36 

 

creatively put into consideration, if not the Designer may run fowl 

of erroneously and unconsciously manipulating the result of the 

data analytics. In reality, this is a clear example of how one may 

not be truthful with data (either big or small). This must be watched 

to keep all the data intact, precise and truthful as much as possible. 

 

Conclusion 

“Medical records are tough to come by in so many developing 

countries. The few hospitals with medical records are challenged 

with incomplete, inaccessible, and inconsistent patient data” 

(Teniola, 2023). Deductively, this is simply that manual records 

(which can pile up to become ‘big’) still dominate the nation’s 

health system (Nigeria precisely). It is a serious area of concern 

that calls for effective digitisation of healthcare. Quality healthcare 

also requires digitised records and “practically impossible without 

efficient data to support an Electronic Health System” (Teniola, 

2023). Data, in any form, are an integral part of the operations of 

health institutions which aptly (in the digital sense), accumulate to 

make ‘big data’. This is characterised by its volume, velocity, 

variety, variability, veracity, visualisation and value. 

Unfortunately, big data is valueless unless it can be presented in a 

simplified manner. This is the essence of visualisation which is 

important to achieving meaning in big data in healthcare. It is better 

to get health infographics (i.e. data visualisation) done 

systematically and strategically. By the former, it means a carefully 

mapped-out process towards creating data visualisation. The latter 

solidifies the (data mining) process in which one stage rolls in to 

another; dwelling on relevant visual elements and (Gestalt) 

principles of design. Visual (data) communication as a means to a 

result can therefore be integrated into any e-health platform for 

seamless operations, especially for meaningful big data. When data 

information is easily understood, it fosters the decision making 

process for the Government and health-reform stakeholders. Health 

institutions via refined data presented as infographics, will be able 



Making meaning out of big data in  Healthcare:… 

37 

 

to provide improved or personalised care experience for patients. 

Health facilities can increase their revenue and advance their care 

services through processed data that also dwells on visual 

communication. In all, as a Visual Designer, it is therefore 

important to understand the concept of ‘big data’ from the angle of 

communication design. By having sound knowledge, Visual 

Designers should then be able to provide better data 

communication and design solutions. This is necessary, especially 

at a time when there is also a call for investment in medical research 

(Edema, 2023); such research will equally rely on data that must 

be presented meaningfully, with the aid of data visualisation tools 

e.g. charts: pie, scatter plot, histogram, cartogram, dendrogram etc. 

 

Question 

1. What is big data visualisation? 

2. Discuss the essence of information graphics in healthcare. 

3. Explain the term ‘visual design’ and discuss the 

characteristics of a Visual Designer. 

 

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