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The apps you use on your phone were first thought up by people who started with just a cool idea. Do you “tweet” on Twitter? Read on to find out how your tweets might (or might not) indicate that you’re part of an emerging revolution. But not all apps are available to everyone. Companies and other organizations use computers and applications (apps) to share information with their clients and employees.
David Scheiner is an internet applications developer and architect in England. One thing he loves about his work is that “you’re interacting with code written by so many other people and through that interacting with their minds, even if you never meet them in person.” He builds systems for storing and accessing data and helps organizations choose the best designs for their needs, always problem-solving and teaching himself new programming languages and methods along the way.
Today most of his work involves listening to people at large companies and helping them figure out which systems will work best for their needs. For example, while meeting with one large defense contractor in Europe, Scheiner spent most of his time listening to employees explain what data they use and how. Eventually, he developed a system that allowed people to access the documents they needed. He points out this was “arduous” more than mathematical and involves careful listening skills more than math. But ultimately, he translated people’s needs and thoughts (unstructured data) into structured data that could be used to codify and store all of the information in the company for retrieval and use.
David wasn’t always a coding and math star. Signs of the emerging techie were more visible at home than at school.
Growing up, David loved watching his grandfather build train sets and fix things around the house. He was fascinated with his mother’s broken clock and loved to take it apart and try to put it back together. One day he pieced it together and got it working again. This made him feel like he had reached across time to the clock-maker.
But in school, he would miss one concept in a math class and fall behind. He was told he could never be anything like a programmer and felt “math was this over-arching, intimidating thing.” That partly explains why he steered clear of math, engineering, and tech in college and chose German and history as his majors at the University of Chicago.
It wasn’t until David finished college and got a job at a large law firm that he began to recognize the ways that he thought mathematically and understand just how useful that was. The lawyers he worked with needed to access a large volume of documents. Scheiner found himself creating a system to retrieve them.
“What I did — although I didn’t know it at the time — [was to become] effectively the architect of a database system, putting the [documents] into a logical structure that allowed us to retrieve them according to the needs of the case as it evolved over a period of several years.
“Any documents with anything relevant were flagged and read more thoroughly. Each [one] had a unique ID stamped on it, something very important for database structures, as I soon learned. We created a record for each relevant document and then indexed it against points in a master outline of all the relevant [issues] in the case. If the lawyers had to discuss one or another of the points, I could look it up in the database, get the IDs of all the known relevant documents and have copies of those on their desk in a few hours.”
This system was far simpler than the ones Scheiner works on today. But the work he did then laid the foundation for his career. “What I did felt so natural and straightforward to me — I never thought about its significance. It was when I left that job and people struggled to maintain the system that I realized maybe I had some talent that not everyone had.”
Scheiner had been told many times that his poor math performance as a young person meant that he could never do something technical like program computers. “I believed that myself right up to the moment a guy hired me at his startup to be a programmer,” he says. “He could see that I would learn, and that the ability to learn was what mattered, which is exactly what happened and has been happening since.“
This supervisor mentored Scheiner and encouraged him to teach himself the code he needed to know as he went along. The important thing was logic and deduction, not necessarily math as such. He used scientific methods to form theories, falsify, and test them and abandon them when they didn’t pan out.
Scheiner has also worked on projects outside the corporate world. One uses math and mapping to look for patterns in global events by analyzing social media and other data that has geo-tags in real time. Geo-tags keep track of the place where data (a photograph, social media post, or other information) gets recorded.
For example, when the Arab Spring began in 2010, riots and civil wars spread throughout the region, beginning with the Tunisian Revolution. As Scheiner puts it, he and his colleagues wanted “to try to understand the ways people were using [social media] to draw conclusions about real world events as they were happening.”
Where was the next civil war likely to occur, and how could we predict it? To do this, Scheiner built an algorithm to assign statistical scores to events that were happening across a region.
Whenever there was a lot of geographically concentrated activity on Twitter, as there had been before the demonstration at Tahrir Square in Cairo, the capital of Egypt, Scheiner’s algorithm plotted the social media data on a map with visual points. A radius around a point showed the statistical likelihood of more demonstrations in the area around that tweet. Scheiner found that using geometry and data this way, he was sometimes able to spot and track demonstrations before they were reported on major media.
He would be interested in mapping other data this way. Scheiner wonders, for example, how historical events might be investigated using people’s memories. What kind of mathematical relationships could we find between events that happened in the past that could help us predict events in the future?
The history and German Scheiner studied in college contribute to the communication skills and historical thinking he finds helpful in his work today. Despite his early struggles in math class and that old (and wrong!) sense of hopelessness, his work using mathematical thinking to solve problems for and with people has become a fulfilling career.
