When I tell friends, family, other mums at the school gate that I’m doing a PhD, they all ask me what my research is about. I’ve been working on my answer:

I’m looking at ‘big data’ to see what it can tell us about risks to how and whether people travel for work during severe weather events. That’s the one sentence version.

Sometimes it’s better to frame it as a question: What do commuters do when a big storm disrupts their usual journey to work, is telecommuting a preferred option, and what does that mean for how we plan for the more frequently extreme weather likely in the future?

That last bit is the aim, the purpose, the endgame of my research and why I believe a research council has agreed to fund it. I’m looking for evidence that might suggest that governments, businesses, and communities change the way they plan for and invest in resilience to severe weather and its impacts on infrastructure and property. And I’m looking in the new world of ‘big data’ because that evidence needs to be as statistically significant and scalable as possible, not just anecdotal.

Well, I’m still chasing the really ‘big’ data, but I have recently acquired some data on the transport impacts of Storm Doris on Thursday, 23 February 2017 in the Reading urban area. Trees fallen down, billboards blocking roads. Trains and buses delayed, diverted and cancelled. My data is sourced from local news reports, Twitter, and passenger numbers from Reading Buses on the day and on a more ‘average’ Thursday for comparison.

A few quick calculations and the results were suggestive. Passenger numbers were down during Storm Doris. Routes affected by diversions and delays due to fallen trees or other debris saw lower ridership than the ‘average’ day, but then so did other routes without noted storm-related problems. Did people stay home? Travel virtually or cancel their activity entirely? Were there map-able patterns?

I noticed that there were some routes which gained passengers. Why were more Vodafone employees on their dedicated services? The numbers couldn’t tell me. Why were more people on the long-distance route to Wokingham and Bracknell and on the Park & Ride service in that direction? A likely answer is that as the trains were even more affected than the buses, some people may have decided to switch. In which case, thinking of my endgame, perhaps Reading Buses should build that likelihood into their emergency planning for that route, run more buses. But was there enough evidence of actual cause and effect, of probability of recurrent behaviour to justify such an operational response?

I’ve been thinking about how much more evidence I might tease out from public data sources or a little more data from the bus operator. Are there patterns in the individual bus trips where the loss or gain of passengers was particularly noteworthy or could be matched to service disruptions? Is it worth looking at the type of tickets, the stops along the routes to get an idea of the demographics of who did or didn’t take the bus? Did anyone tweet their intentions to switch modes, to stay at home?

Yet with every dive deeper into the data, the falling probability of demonstrating statistical significance echoes ever louder. The passenger dataset was less than 90,000 on the average Thursday, falling by over 4%. The numbers on individual routes, different ticket types, different times, quickly descended into the hundreds or tens, even on the popular routes. My recently refreshed, but untested and uncertain statistical skills are already struggling with how to make a more than anecdotal comparison between one average Thursday and one disrupted Thursday during one storm in one urban area. How do I show that the most basic null hypothesis – that the storm had no impact on passenger numbers – is extremely unlikely, never mind look at any route in more depth to propose emergency service tweaks to the operator?

I have to face it. It will always be an anecdote. But it could still be an anecdote with an endgame.

Last week I observed a little-known, but very special, Jewish Holiday called Tu B’Shvat.

I explain it to my five-year-old as ‘the birthday of the trees’, which is a basic, but not inaccurate way of explaining it to adults too. Although it is not listed in the Bible as a holiday, the Bible does prescribe that fruit from trees less than three years old should not be eaten and the fruit brought to the ancient temple should be from trees in their fourth year. So trees needed a ‘birthday’ from which to calculate their age, that would broadly relate to when they had been planted, presumably in the Mediterranean Spring. In the Rabbinic writings known as the Talmud, the 15th of the Hebrew month of Shvat, or Tu B’Shvat was identified as that ‘birthday’ or the New Year of the Trees.

On Tu B’Shvat, it is traditional to plant trees and this tradition has greatly contributed to the greening of the Israeli landscape, where whole forests have been planted in land once largely desolate and desertified. We too planted trees last week, although a snowy, muddy, English woodland in February doesn’t feel much like a New Year for trees and Spring seemed a rather distant promise.

Yet Spring will be in full bloom when the next tree event I’m aware of comes around: Trees, People and the Built Environment, a conference in early April. Unfortunately, I cannot attend, but simply reading the programme was to be reminded and inspired by the ways that trees touch our lives, even in urban areas. We all know that trees make an enormous contribution to the global and local environment, that if you live on a tree-lined street, you are likely to be healthier, wealthier and perhaps even wiser. I grew up on a tree-lined street, making me one of the fortunate ones, and I feel blessed for it.

There were gaps in the row of trees, however, including in front of my childhood home when my parents moved there, the year before I was born. So they filled that gap, planting two maple trees to mark the birth of each of their daughters. By the time I left home at 18, my tree was over twice my height. Now it is much taller again, and I can still appreciate it if I visit my hometown. Without trespassing. Because my parents planted it not in the garden, but on the grass verge, between pavement and street.

Trees and streets and planning can be a trio in a messy relationship. Trees make a street more desirable at the same time as their roots crack the pavement and their falling leaves block the gutters and drains each Autumn. People fight against a favourite tree being felled in a public space, but protest Tree Preservation Orders that protect a tree blocking their planned, new extension.

The problem is perhaps that town and transport planning often operate on a tree by tree or street by street or development by development basis. There is inadequate consideration of strategic tree policies for urban areas. And it is inadequacies like this that the Trees, People and the Built Environment conference aim to address. Perhaps, like the holiday of Tu B’Shvat creates a holistic policy for marking the age of trees, so planners and transport planners can learn to create holistic policies for the presence of trees in the built environment once they have evidence for what they have always known – that trees make for better places.

I was feeling guilty and proud over the last couple days. Guilty that I hadn’t marched, didn’t check and hadn’t even realised that sister marches were organised in British cities until too late. And proud that so many of my family and friends in the United States did march in big cities and small towns around the country.

I’ve slightly assuaged the guilt by writing to my senator, as per the first action suggested by the #WomensMarch movement. And I’ve had a thought that has helped me regain my own sense of pride on this issue. Namely, that I march almost every day.

Or rather, I walk almost every day, and although I’ve written in the past about many of the benefits of walking, I’m not sure I’ve written that those benefits include social justice, community cohesion and generally making a place and its people more civilised.

Because when you walk, you connect to your community. You say hello to people you see regularly, even if they are not part of your social circle. If you live in a diverse community, people with different faces become familiar. People with different views become familiar.

I live in a very split area in terms of the Brexit vote – Bracknell Forest district went slightly to Leave, but it was closer even than the national results. I thought that the reason I find those who voted Leave more understandable than those who voted for Trump, even if I disagree with both, was because perhaps Leave has more persuasive and less extreme arguments. Now I wonder if the reason I understand them is simply because I know them. I know Leave voters in my neighbourhood because I’ve walked around and been in conversations with them.

Mind you, I may never see how Trump as an individual could be seen as anything but repulsive and unrepresentative of the people who voted him in. Yet the real reason I can’t understand why those individuals did what they did is because I don’t know them walking down the street. I don’t live in the United States and unsurprisingly know no one who voted for Trump personally. Yet the state where I am registered to vote, New Hampshire, is as divided as Bracknell Forest and went to Hillary Clinton by the narrowest of margins.

So if I still lived there, presumably walking would have resulted in expanding my horizons and theirs. And even if no one ever changed their minds by such encounters, being on foot and able to see and interact with people around you would still be a way to break through those ominous social media bubbles, put faces to views and improve familiarity with the ‘other’ until perhaps they weren’t so ‘other’ anymore.

Thus, it is important to realise that walking is not only good for your health, your wallet and the environment. It is also good for solidarity, not only on marches with people you agree with, but around your neighbourhood with people you don’t. If we can walk together, we can work together to fight the politics of fear and division, no matter who is peddling them in the future.

Early in December, I wrote a blog about big data in the abstract. I had just been to a workshop on the topic, which defined big data as datasets that are uncomfortably large for a single machine to process into information. In my blog, I wondered whether actually big data should be defined as datasets that are uncomfortably large for a single human to conceive of and then to trust when they are processed into information.

Now, I have just returned from another workshop where we were taught one way we can make people more comfortable with the information we may derive from our big data research: by presenting it visually in a compelling, creative and coherent manner. A picture is worth a thousand words. Or an infographic should be.

Again, we started the workshop with a definition. Infographics “are graphic, visual representations of information, data or knowledge intended to present information quickly and clearly,” says Wikipedia. Infographics can help explain things, especially patterns, trends or changes over time or within complex systems or geographies. Ideally, they should represent ideas, facts and statistics without distorting them. They should teach, warn, and persuade whoever is the target audience.

They are not new. They can be found in 19th century policy documents, early social science textbooks, every publication of census information for general consumption. More recently, as websites seek to increase content to increase clicks, infographics have proliferated. Their quality has not kept pace with their quantity, although great examples can be found with a little digging. Many at the workshop shared a few favourites, and in the past I have tweeted ones that stir my imagination when I have come across them.

Still, as we turned to more practical exercises at the workshop, we soon learned why there are so many terrible infographics out there. Because whilst a picture may be worth a thousand words, it takes at least as long if not longer to create said picture than to write the thousand words. So it would appear that such an investment of time (and skill, and having decent tools) is not granted to the majority of infographics in circulation today. Thus they are not worth 100 words, never mind 1,000.

Time is also needed to practice and build skills in this area, and the workshop gave me a greater appreciation for the professionals out there, including my brother. Although a novice can quickly grasp the basics of graphic design tools, mastery takes years. On the other hand, with professionals on hand to help, our group of PhD students were able to produce some pretty neat infographics in one long day that did actually convey scientific information.

Which brings us back to comfort. Various audiences struggle to be comfortable with the outcomes of big data analysis, especially if it is scientific. Climate change and other global environmental issues are key examples, as some of our workshop groups grappled with. But if this discomfort and mistrust can be overcome, fantastic infographics are a likely way to do it, because a good picture is something we all can understand, no matter our age, education or the language we speak.

I felt more comfortable trying to create something in the visual language of graphics at this workshop than in a computer programming language at the previous workshop, so I hope that my comfort will be transferred to my audience as I start trying to illustrate my own research. Once I have the information I want to illustrate, of course!