It’s the size of the smile on your face when you see someone. It’s the decision to stay in touch with a niece long after family events end. It’s the fragile silence between you and a friend who couldn’t support a recent life choice.

As a data designer, I’ve always been obsessed with how we categorise the intangible. Recently, I set out to map the people who have shaped me. I didn’t want a balance sheet, but I did want to see the patterns. A relationship always evolves; this would only represent a snapshot in time.

The Taxonomy of Connection

I began by listing every person I care about. First from memory, then verified by my friends list on Facebook. But as I opened my spreadsheet, the questions started to flood in. Can family members count as friends? For example, my nieces and I have been chatting nonstop for years now. We grew fond of each other through the circumstance of birth, but we stayed in touch by choice. Does that make them friends? And what about friends who aren’t supportive of my life choices? We were very close 7-8 months ago, but we are not now. Are we still friends? If I exclude her from this, does that mean I have given up on our friendship? Also, I use the term “friend” very loosely. I am naturally familiar with strangers. Is my new neighbour — with whom I have shared a few cups of tea — my friend?

To make sense of the friend list, I distilled friendship into three core metrics, scored on a scale of one to three, three being the highest rank possible: 

• Reliability: Loyalty, faithfulness, and the feeling of being safe.
• Empathy: Supportiveness, kindness, and open communication.
• Joy: Playfulness, liveliness, and shared common ground (though one might question whether friendship is required for common ground; for the sake of this visualisation, I decided it was).

I also added two judgment values: Duration (how long we have been friends), and Contact (how recently we spoke). To keep the data honest, I limited the scope to friends I had contact with in the last 24 months. I chose 24 months as a mark because it’s the period since my daughter was born. Spoiler alert: In a time when I often felt lonely as a new mother, the data showed me I was actually deeply loved.

From Sketching to Scripting

In my notebook, the design evolved rather quickly into a series of “tiles.” I remember having the visual in my head for a while, and I felt as if I were a vessel letting it out onto the paper. I wanted something that would represent the scale’s levels easily. Level one was a simple base; level three added complex detail. 

Initially, I used background colors to denote duration, but the palette was too loud. It made the story about “how good I am at making friends” rather than “how these friendships built me.”

Then came the pivot. Usually, I build these visualizations by clicking the mouse. A thorough process of copying, pasting, and double-checking layers in Illustrator and Figma would easily take three hours. But, inspired by the “vision to execution with a click” movement, I turned to Claude and Gemini.

I asked Gemini to help me write the prompt for Claude. It generated a Python script that processed my Excel file and generated stacked layers as PNG files. Claude taught me how to install Python on my Mac. (Honestly, I felt like I was back in the 90s, typing into a terminal to launch a game.) Then, “Boom. Your tiles are ready.” With a single click, the assets were generated. A few back-and-forths with Claude, and the grid was aligned. The work was done.

The Cost of Efficiency

As I looked at the finished folder, a strange feeling washed over me: I didn’t recognize the data. By automating the execution, I had accidentally bypassed the data familiarization stage — that meditative hour where you handle each data point with care and remember the person behind it. The tiles were beautiful, but they felt distant.

It raised a fundamental question for our field:
If the AI builds the layers, are we co-creators? Or are we just curators of our own memories?

The Tokens of Gratitude

Despite the digital distance, the final grid is a testament to my life. These tiles are me. They represent the people who stayed through puberty, the ones who signed my wedding book, and the new friendship that started when I collected my son from preschool, which grew close.

This project is more than a visualization; it’s a token of gratitude. It captures a snapshot of my soul as it exists in 2026. Shaped by humans, rendered by machines, and held together by the voluntary, personal relationships that make life worth mapping.

The post The Tiles That Made Me: Mapping Friendship through the Lens of AI appeared first on Nightingale.

We both work full-time and raise two young children, so our evenings are the only moments left for connection. He is the hardest-working person I know—relentless in chasing a dream that has recently taken shape as a tech startup. His quietest, most productive hours begin when the kids sleep. I, on the other hand, go to bed alone.

At first, I texted him, “Good night.” He would reply hours later, sometimes with a simple “coming to bed now.” But after two months, I realised something: I had data. It’s not formal, tidy data- casual timestamps, scattered messages, and a discernible pattern.

So, I started tracking it deliberately. A spreadsheet. One column for the time I went to sleep, one for him. If I forgot to log it, I would ask him in the morning: “When did you come to bed?” He always knew I was tracking his bedtime time. It comforts me. Data gives shape to ambiguity. It holds stories quietly, waiting to be told.

There is a particular calm that comes with collecting data. For me, it is a form of emotional processing. Tracking our sleep was something small I could hold onto. A private system of meaning. Each entry felt like a whisper to myself: “You are paying attention”.

As the dataset grew, so did the emotional tension. We argued. Not because I didn’t support him, but because I missed him. Missed us. One night, I added a third column: fights. Eventually, a pattern emerged. We always argued at the start of the week after the weekend reset. I brought it up, along with the spreadsheet, and together, we coined the Sunday-In-Sync Rule. Once a week, we would meet in the middle. He would wrap up earlier, and I would stay up later—a small act of reconnection in a sea of drift.

At one point, I realised that the actual times we went to sleep didn’t matter as much as I thought. What mattered was the delta—the difference between them. That delta became the emotional signal, more about how far apart we were. From that moment on, I shifted my perspective on the data and how I wanted to visualise it. Each petal would represent a single day. My sleep time became the baseline. His would be expressed as a distance—the space between us.

Five months in, the dataset had become too complex to keep in rows and columns. I started sketching. One flower for each week. Some flowers bloomed, representing nights spent together, even if late. Some wilted, marking long gaps between bedtimes. A visual garden of our sleep patterns emerged. A bouquet of data is carefully drawn.

Why flowers? Because they are the most classic romantic gesture. A universal symbol of affection, apology, and devotion. I was not just visualising data; I was creating a love letter. One that said, “I see you. I miss you. I’m with you”. Presenting the data as a bouquet felt right. It framed the tension with tenderness.

Drawing it brought another kind of clarity. Unlike the spreadsheet, which was linear and clinical, the floral format made space for nuance and softness. It became a way to honour the emotional weight of these minor, repetitive, daily differences. A quiet ritual that helped me come to terms with what I could not control.

When I showed him the finished visual, he was speechless. Then smiling. Then laughing. He told me I was the most supportive wife he could ask for. Later, I found out he had shared the piece with his friends. That meant everything to me. He saw what I saw.

Is it a visual love letter? A quiet protest? Maybe both.

What I know is this: in tracking our distance, I found a way to feel closer. I supported him in silence, witnessed his effort, and honoured the rhythm of our parallel dreams.

The post A Garden of Sleep: Tracking the Emotional Distance Between Two Bedtimes appeared first on Nightingale.

Being a mother to an energetic toddler boy is a relentless rollercoaster. Each day demands boundless energy, endless patience, and love. Being a full-time working mum on top of that feels like an obstacle course, and when adding the first trimester of pregnancy into the mix, it’s like battling the devil. 

The first trimester of my first pregnancy was a walk in the park. That led me to believe that the first trimester of my second pregnancy would be the same. But that could not have been further from the truth. I experienced every symptom on the pregnancy list: waves of nausea, sleepless nights, countless trips to the bathroom, loss of appetite, and a relentless battle with fatigue that threatened to consume me. 

Going to bed at night became a dreaded ordeal. The once comforting haven of my pillow, where I would rest my weary head after a long day, now held a haunting sense of fear. My husband did his best to support me, taking care of our son Ethan alone during the evening routine and ensuring I had all the pillows and comfort I needed, but still, peace was out of reach. As sleep eluded my body, I started losing touch with myself.

Pulling on the anchor I gained while pursuing my Master’s Degree in Research, I found solace in collecting data on my sleepless nights and tracking my experiences. It helped me regain a semblance of control, serving as my guiding light in the darkest moments. Putting my experiences into an Excel sheet gave them a tangible form, something I could grasp and comprehend. I started noticing patterns, seeing an end to it all. 

Tracking became a ritual, documenting the time and reasons for waking up in the middle of the night and logging them into the computer each morning. It became a way to acknowledge my pregnancy and offered me a sense of control. Once I completed the first week of data collection (the nine weeks of my pregnancy by that point), the data became a testament to my resilience, a reminder of my strength, and it empowered me to keep going.

To make sense of it all, I used a Piet Mondrian-inspired design to represent my data visually. Mondrian believed that abstract art could distil the essence of realistic data and scenes into something universal and timeless. Tapping into his mastery of the abstract, I transformed my journey into a tangible display of endurance through squares of colour. 

When I finished designing my first two weeks of data, I sat in awe before the Mondrian-inspired creation. My eyes traced the lines and colours that told the story and encapsulated my data. It embodied the purpose of my data collection, and I felt grateful for the strength that carried me through but even more amazed by the beauty that emerged from it.

It served as a reminder that even during endless, unwavering nights, beauty could always be found. More importantly, once again, my connection to the world of data visualisation has helped me navigate motherhood and triumph in the process.

The post <strong>Finding Solace in Tracking My First Trimester Nights</strong> appeared first on Nightingale.

In the weeks leading to Ethan’s summer break, I began working on an extensive Excel sheet, scheduling activities, playdates, and goals for the summer. Our days were filled with sensory activities, playing with toys, reading books, and exploring the great outdoors. To me, data is a vital component of our experiences. It adds a layer of information that is not visible to the participant or the observer. Yet, it must not interfere with the activity or shift the experience. Initially, I planned to record the time spent on each activity. I thought the timing layer would help me understand Ethan’s favourites. I discovered that creating timestamps in Excel consumed my focus and made me too aware of time instead of delving into the fun, so I removed the time column from my data sheet.

After a few days of data collection, I had an impressive log of 20 entries with various activities. It was time to create a visual representation of each activity. 

First, I set the colour palette. I had 12 different groups of people that Ethan spent time with. For example – grandad, granny, mummy, and daddy were one group, and grandad, granny, and mummy were another. I wanted to reflect the enthusiasm I felt for that summer in the colours: Flickr pink, pine green, neon yellow, and majestic lavender. I limited my palette to12 colours to represent all the data, background, and symbols.

Once I had the colour set, I opened my Adobe Illustrator and started doodling a symbol for each activity. Since I planned to publish my final piece on Instagram, I set a square to represent each entry so the pattern created could be displayed entirely under Instagram restrictions. I designed the symbols to touch the edges because I wanted to create a seamless effect. Additionally, I wanted the background colour, the layer with whom Ethan did the activity, to submerge into the symbol to represent that activities differed based on the participants. For example, if my husband joined Ethan and me to go to the beach, it would be an entirely different experience than without him.

I presented the pattern of Ethan’s summer 2022 activities and playdates with vivid colours. My dad helped me set up SQL to generate it automatically. This was my summer activity with him! Even though it was a self-data collection, I submitted my design to the “Information is Beautiful” award and made it to the longlist! See the full project on my Instagram account.

I cherish the opportunity I had to spend time with Ethan and set activities for him to grow and evolve. I am also grateful for the insight this activity afforded me to learn more about my toddler and his favourite activities. I wonder if, as time passes, we will still like to do the same things together. 

The post SPOTLIGHT: Using Dataviz to Inform My Childcare Decisions appeared first on Nightingale.

Blood tests are one of the most common types of medical tests. They have a wide range of uses, such as diagnosing a condition, assessing organ health, and more. The test results are highly valuable – they provide up to three times more information than other patient data sources such as medical history, physical examination, and symptoms. Traditionally, the test results are presented exclusively with numbers alongside the text of the acceptable range. This information requires an interpretation by a medical professional, as patients typically lack the training to decipher the findings on their own. Blood test results provide meaningful information to four sets of users: the doctor who ordered the tests, the nurse who draws the blood, the laboratory worker who performs the analysis, and the patient who needs information. A change in the test results display should benefit all users. Doctors, for example, can more quickly discover irregularities in the results of an individual patient.  I focused my study on the patient as the user. I was eager to research visual representations without numbers at all. I hypothesised that all patients with essential health and numerical literacy could engage with their results if those data were visualised. My project was supervised by the inspiring Dr. Simone Gumtau from the University of Portsmouth. 

Empathise and define

I believe that all design projects should follow the Design Thinking approach. Personally, I follow the “5-stages-model” as taught on IxDF; This model is based on five non-sequential phases built into an iterative process: empathise, define, ideate, prototype, and test. I interviewed a few non-medical, UK-based patients. to see if I could improve the patients’ engagement and motivate decision-making processes. I conducted two qualitative interviews with each participant. In the first interview, I aimed to gather information regarding the participant’s current experience with their blood test results, the traditional result sheet. The key was understanding the “whole picture” of needs and reasons for conducting the test, in order to get a broader understanding of the problem I wished to conquer.

After the interview, I synthesised and analysed the data and built a hierarchy map.

Ideate and prototype

 Using the granular blocks of the map, I designed a personalised prototype for each participant, representing numerical data by colours, graphs, and text. I presented this prototype at the  second interview, which was conducted in order  to evaluate my concept. 

During my studies, I had a professional crush on Alberto Cairo. It started while reading his book The Truthful Art, which gave me countless aha moments. I decided to model my data visualisations based on Alberto Cairo’s qualities for great communicative visuals.

First, I wanted to reduce the patients’ feelings of overwhelmingness. For example, one patient was timid about sharing her results at the interview’s onset due to a lack of confidence regarding how to read the results. So, I divided the  text and data into categories and eliminated information that might be considered unnecessary for the non-medical patient. (this should be examined by a medical practitioner).

I learned that patients struggle with understanding the meaning of the test and its relation to their symptoms. Therefore, I designed the new visual to present the results using causality order: the relationship between the cause of conducting the blood test and the effect of the results. As such, I displayed the results in a nested treemap chart. The bigger the rectangle, the more likely the test result is related to the cause of symptoms or diagnosis. 

I love the functionality of a treemap because it offers both hierarchical displays and part-to-whole relationships. With it, I generated a non-linear display. There is no right/wrong method of reading the content. Also, I limited my palette and used the traffic light colour scheme to communicate effectively without numbers, as colours offer fast attribution of the relationship between value and the acceptable range. To make the traffic light palette more colour-blind friendly, I tried to avoid the green-orange problem by using light, medium and dark shades- where the red is warm, and the green is cool. 

Presented here are the medical category and test titles without numerical values. The home screen (depicted above) uses negative white space as a buffer between the elements. 

The user can “drill down” into each category by clicking on it. 

The second level offers a detailed overview of the tests it contains. The colour-coded background represents the acceptable range of the test result. Using fewer words reduces the page length (ideally with no scrolling) and allows the text to “breathe.”

The third level offers a detailed review of the test results. This level is the only place I present the result’s numerical value because the patient shows deep interest in the resulting drilling to this level. My research discovered that numbers could deliver a sense of assurance and authenticity. I display the numeric value of the test result on a one-axis bar chart without units. The axis has a definite numerical indication of start and finish. I chose this representation because it simplifies the ability to read the data; it delivers complete access to the information without requiring a high level of numerical literacy.

Test

Once I had a working prototype, I conducted the second interview that acted as user testing with participants to gather feedback on the redesign. I will focus on Participant 23’s reactions as she was the first to receive the numberless prototype.

She was content browsing the prototype because she realised most of her test results were within the acceptable range. Her natural next step was to seek a possible explanation for her symptoms. She was also eager to view the abnormal results. 

She reviewed the dietary recommendation section, as her doctor prescribed and understood the causality that led to this prescription. She was able to take action within minutes of exploring the prototype. I was so happy about that! 

Overall, the participant reported having a pleasant experience exploring the prototype. The click-ability of opening and closing categories was intuitive. She stated that she is pleased to see numbers and graphs only in relevant places, giving her a sense of validity. In conclusion, insights were gained, and actions were taken (for example, regarding vitamin D insufficiency).

To conclude, my proposed solution achieved two goals. First, it made the data approachable, so participants felt confident interacting with their results. Secondly, the visuals were insightful enough to encourage action according to stipulated diagnoses. All my participants in the study were made aware of their diagnoses and conditions through engaging with the personalised prototype, which also led to action initiations. 

Future roadmaps, only one “round” of iteration was conducted in my studies, the design thinking approach feels incomplete. Amending the prototype with the participant’s request was not part of the scope of the dissertation and is missing. Also, Interviewing more users with their results might cast light on different subjects. Ultimately, examining the visuals with a medical expert in the field could clarify the critical sections of blood test results regarding the decision-making and action-taking processes of the participant. These recommendations require further examination and might affect the visual and the outcome. But that would be a different study, or perhaps a PhD.

In addition to blood test results, other medical information could benefit from a change. I wish we could shift the power to the patient by applying data visualisation rules and a design thinking approach to all medical readings. It could potentially impact patients’ lives significantly.

The post Can We Understand Blood Test Results without Numbers? Ask Participant 23 appeared first on Nightingale.

When I got back to the dorm room, my husband wiped off my tears and cheered me up immediately. “Change your perspective,” he urged me. “You are a data-driven person. Look at your bookshelf, Observe, Collect, Draw! Do it. Read, collect data on the pregnancy, and make the most of the situation.”  

Being pregnant was not a walk in the park. It tremendously increased the number of times I had to excuse myself and rush to the loo. Whenever I was out, I had to make sure I knew where the toilets were, and my bladder couldn’t make it through the night. I was so upset about it, yet there was nothing I could do. Remembering my husband’s words, I had to change my attitude. Thus, the data collection phase began. I put a notebook in our dorm room bathroom and a piece of paper in my purse to collect the number of visits. Every bathroom break, I added a line mark next to the date. I continued collecting data throughout the pregnancy, and I absolutely loved the outcome. It was a great exercise in practicing my data collecting skills, and it encouraged me to change my perspective as my visits to the loo were not mere misery—they served a goal. 

The pregnancy made me have butterfingers; I dropped almost every item I was holding. Presumably, my phone suffered the most. Worst of all, I could not bend to pick up my phone when it inevitably fell to the floor. In the beginning, every time my husband retrieved the phone, he’d say, smiling, “You are welcome times X,” where X is his added number of times he assisted me. His charming response sparked my curiosity about the correct number of dropped items, and I started collecting the data on these clumsy mishaps. I hated dropping things, and as the frequency increased, my irritation levels rose to a boiling point. I started to swear like a sailor. I recorded my reactions in these moments, too. When I reached the end of the second trimester of my pregnancy, my husband and I decided to fly back to Israel and continue our studies via Zoom. When we moved, I misplaced my notebook with the data collected. It probably slipped through my fingers when packing and I had to retrieve part of it from memory. For that reason, I removed all numbers and made a bar chart presenting the comparison between trimesters and responses. 

Time throughout my pregnancy passed by very quickly. With a blink of an eye, I had my newborn son in my hands. I was trying to find my pathway in this “unknown territory” called motherhood. Even though I was confident in my ways, that time just after my son’s birth was overwhelming. 

When Ethan was two and a half months old, I believed I was doing everything wrong. It was chaotic. I did not feel like me anymore. I was Ethan’s mum while also trying to fit in my roles of being a person, a designer, and a wife. 

Whenever I craved some “me” time, I would go out for a walk around the neighbourhood. Usually, the rays of sunshine cured everything and put a smile on my face. But then, the presence of other people on that sidewalk—all with unwanted advice and unpleasant questions or comments—was infuriating. Every time I received unwarranted advice about Ethan, my emotions would elevate and I would text my husband for moral support. Alas—another opportunity to collect data. One quiet afternoon I read all our back-and-forth texts and tried to find a pattern. I found some comments from strangers to be ridiculous, comments about covering Ethan with a blanket due to the air being too cold, and some the opposite. I cumulated the amount of advice I received and added the number of questions I asked on social media. I wanted to present the balance without “over-explaining” it. The solution was a fabulous vis showing the advice I asked for compared to critical comments.

Since Ethan was two days old—before he was even named Ethan—I have been collecting his every move using a “Baby Tracker” mobile app. I gathered data on food, sleep, exercise, poop, amongst other stuff. Tracking him made me feel like a skilled mother, as it helped me foresee when he would be tired or hungry based on past data.

When Ethan was five months old, we went to the doctor for a regular check-up. The doctor asked me about time spent on his tummy, suggesting that he should be doing this for at least five minutes a day. I took out my phone, and with a few clicks on the app, I could see the amount of tummy time I had measured. Happily, I discovered that he was spending a tremendous amount of time on his tummy, data I could not have known from observation alone.

Every month delivered new challenges and struggles. By the time Ethan was six months old, he was waking up a lot at night. I was losing my sense of self by waking up every hour and twenty minutes. Whenever I was designing a vis, I pondered something a professor told me in undergrad about sleep impairing creativity. I learned firsthand that this is true. Sparking a creative way to convey the data was easy; however, practising data vis and applying Alberto Cairo’s rules that I recently learned in my Master’s degree was difficult. For example, “eliminating things that do not support the narrative” was the hardest to follow. My visualisations appeared crowded with decorations, diverse data, numbers, and long titles. Luckily, we hired a sleep trainer who helped Ethan (and, by proxy, me) sleep better. This extra sleep, in turn, helped me with designing.

Ethan is now just short of one year old. I do not have the perfect equation for being a mum. But one thing I do know now is that motherhood is a matter of perspective. I decided to look at my struggles, problems, and difficulties as an opportunity and seek the story within the data. I chose to learn from my observations, and I was determined to search for patterns within the data. I resolved conflicts using the data, found solutions, and viewed the learning curve. 

Overall, I am grateful for the data that helps me understand my baby’s life experience better. I’m continuing to collect data, especially about his day naps, which helps me optimise naptime and reduces the amount of crying. 

I am longing for the pandemic to be over, affording us the ability to fly back to the UK and visit Victoria Park. I want to show my son the place where I felt as if the world was caving in on me and share how blessed I am that it all happened. 

Check out my Instagram for more vis.

The post How I Survived Being a New Mum Using My Dataviz Goggles appeared first on Nightingale.