Minding the Borderlands

Mark Koester (@markwkoester) on the art of travel and technology

My Year in Book Reading: 2017

2017 was another great year of reading for me.

Numbers: I read 21,687 pages across 62 books and across 14 different genres. In terms of novels, I read mostly science-fiction, but I also added a few classics too. My non-fiction reading spanned a number of topics with a slight focus on science, business, technology, and history. My biggest month of reading was September 2017 in which I finished 10 books and 3672 pages.

One other topical reading highlight for 2017 was health and fitness, especially long-distance running. Along with completing two marathons and two half marathons, I read several great books on running and you have view my ratings and review in Science and Stories of Running and Some Great Books on Running.

Below is my data visualization of my year in reading, the top 5 books I read, and a few conclusions from this year and year to come.

Running Your Best: A Comparison of Race Predictors, Calculators and Models

Running your best race requires a number of good things to happen. You need to have done solid training and gotten yourself as ready as possible. You need to be healthy and well-rested. You need to know the conditions and have the necessary gear for the race. But arguably one of the most important factors in running your best is having a good prediction.

There are a number of tools and methods online to to estimate and predict your next race time. These race predictor calculators looks at factors like weekly running distance and previous time at a short distance (like the half marathon or 5k) to guess your expected next race time.

While there is a segment of runners who just want to finish and don’t care much about performance or improvement, I don’t really include myself in that group. Like the vast majority of runners I know, we are trying to run our best at races. We want hit a target and get a Personal Best (PBs).

Later this week I’ll be running my second marathon in Chiang Mai, Thailand. I’m happy to say that my training has gone quite well. I’ve been using an smart, adaptive training program from TrainAsOne in order to push my different capacities, avoid injury and get myself ready. At the time of writing, my conditions are good. I’m not sick, and I’ve been getting good sleep and decent nutrition.

In this post, I want to look at several of the predictors, calculators and models used to estimate run times. We will be using my recent half marathon score (1:45:00) and training log to see what these models predict from my next race. Unfortunately, there are a lot of models and predictors out there and there is some degree of variance. Several of the older models were purely mathematical and their predictions are dangerously optimistic. More recent models are based on statistical data and algorithms to make their predictions.

A Year in Self-Tracking: Q4 2017 Update

2017 has been my year of tracking and personal data exploration. For the past year I’ve been meticulously tracking about 20 data points. Not only have I been tracking but I’ve been “optimizing” my life too.

As a followup to my Q2 check-in and as we head into the end of 2017, I wanted to share an update and attempt to dissect some of this tracking. Unlike my normal writing, this post is a mix of vinettes, i.e. observations and some of the things I’ve learned during my year of “tracking everything.”.

(NOTE: At the end of the post, I’ve included a full breakdown of what I’m currently tracking and the tech or process I use.)

Data-Driven Run Training With TrainAsOne: Observations From a Tracking Guy Who Runs

“We don’t rise to the level of our expectations, we fall to the level of our training.” - Archilochos (6th Century BCE Greek Poet)

Much in life is about our training and preparation. This is especially true with running. Whether it’s a shorter distance or a marathon, how well you train has a huge impact on how well you run a race.

When it comes to running, there is a lot to digest on the topic of training. There is both a lot of science as well as a lot of long-held beliefs, traditions and even folklore. As a new or even moderately experienced runner, one of the most important yet confusing areas to navigate are training plans.

Run training plans have been around a long time, and they remain a popular topic online and in fitness magazines. There are hundreds of running programs and training plans out there.

Whether it’s your first 5k or your next marathon, these plans are intended to help you prepare. Some are more geared towards just completing the race distance, while others focus on helping you improve. There are plans for pure beginners and even plans for elite athletes.

If you have no idea how or what to train, then these training plans can be a huge help. I followed a run-walk plan to complete a 5k and used a plan with a coach when I did my first marathon.

In this post, I want to share my take on run training, training plans and my experience using an adaptive run training system called TrainAsOne. I’ve used TrainAsOne to successfully achieve Personal Best’s (PB) at races ranging from a 5k to two Half Marathon’s, and I’m currently following this plan to prepare for my second marathon.

To give you a bit of background, I’m a 34-year old male. I consider myself a tracking, data guy who runs. I’ve been running consistently for about a year and half.

Journaling for Self-Trackers and Quantified Self Enthusiasts

Journaling is a great exercise for your mind. It can help you deal with emotions, record a memory, capture a lingering thought, or clear your mind for the real work of your day. Writing a journal is a highly recommended habit for artists, entrepreneurs and pretty much anyone. It is also a great way to start your day. According to several research studies, regular journaling can even make your happier and more productive.

At its most basic, journaling is the act of spending some time to write something. Journaling is moment to write anything.

For self-trackers and quantified self enthusiasts, journaling also offers an opportunity to capture some personal data too. Depending on the tool you use (more on this later), when you create an entry, you also collect various metadata on that moment like date, time, location and even the weather. You could also note your mood too. These data points can be used for data analysis and data visualization.

Along with the metadata, when you journal, you are creating a piece of text. You have the word count and frequency of word usage. This text and its words can be analyzed with more sophisticated data processing techniques. For example, natural language processing (NLP) is a branch of machine learning and artificial intelligence that is capable of gathering statistics, deriving meaning, building models and understanding the sentiment of the text.

Furthermore, if you looking to build a positive habit into the start or end of your day, then journalling is one of the best. For example, you can use a few minutes of journaling at the beginning of the day to prepare your mind and feelings. This is often referred to as “morning pages,” and this is how I journal.

You can also use journalling at the end of the day as a way to express what you did, how it went and project plans for the day to come. This kind of journaling can be a great way to close out your day and building positive feelings too.

There are tons of ways you can journal. Some people like keeping a diary of events and memories. Others like journaling while traveling or keeping a log of their children’s lives. The format of journaling is wide open and highly individualized.

In this post, I want to look briefly at journaling with a particular focus on how it can be used for self-tracking. We will look at the benefits of journaling, various tools you can use to capture your words, and how you can capture and use data you can get.

How Do I Read? : a Reading Data Exploration With GoodReads and Tableau

The facts: I read between 3 and 6 books per month. I finish more books on Weekends and Friday’s than during the work week. The number of books I’ve read stands at 831 (as of late Nov 2017). The average length of the books I finish is 352 pages. Currently I’m reading 58 pages per day. At my present reading pace (~3.438 books per month), I’m on track to complete my 2000 book reading challenge by spring 2045.

How did I get to these numbers? And what else do I know about my reading trends and behaviors?

I currently use GoodReads to track my book reading. I can log when I start and finish a book. With an export of my reading history, I can use Tableau to explore that data. Tableau is a great and relatively user friendly tool for data visualization. The software allows you to pull in data from different sources and create charts and graphs of that data.

Quite simply when it came to my reading, the question was “How do I read?”

With these questions and tools in mind, let’s explore data visualization on my book reading with GoodReads and Tableau.

Running Workout Types: Knowing and Manipulating These Runs to Optimize Your Training

The goal of training is to be able maintain a higher pace or speed over a set distance.

Naturally, we run different speeds at different distances. With training we can extend our ability from a shorter distance at a higher speed to a longer distance at a higher speed. Training is about the steps we take towards improving speed and endurance over distances, and one of the best ways to do this is through different running workout types.

I started running about two years ago and learned many lessons through this journey. One notable lesson was when I started training for my first marathon was when my coach and his plan exposed me to a wider range of workout types.

The key scientific insight about training for smart runners is that you need to leverage different types of running stimuli in order to build up different physiological changes. For example, you run shorter and harder segments with rest periods to build up your speed, and you run longer and a slightly easier to build up your endurance foundation. Finally to prepare for your target race at a target time, you do race simulations and tempo runs during your training to prepare your body and mind for that target speed over the full distance.

In this post, I want to define some of core run workout types you can do and how those different runs can contribute towards your training.

Don’t Turn Left at 24km: My Story Training and Running the Chengdu Panda Marathon

As I ran down the hill and towards mile maker “24 km,” I imagined the journey to come. A sense of relief entered my mind. I’d finished over half of the race (15 miles) and a mere 18km remained.

Sure, I’d never run anywhere near this distance before, and I’d only been running consistently for about a year. But I was determined, I had trained, and I was going to make it. In spite of the obstacles, both physical and mental, I was on my way to completing my first marathon in China.

The marathon I had chosen was the aptly titled, Chengdu Panda Marathon, a pristine marathon that twisted around the mountains and rivers of Mount Qingcheng and Dujiangyan, two UNESCO Heritage sites dating back to 250 BC.

As I neared the sign, I just had to remember one thing: Don’t Turn Left at 24km. I repeated the message to myself, “Don’t Turn.” That’s all I had to do.

I turned left. It was Friday, and with two days to go before the actual event, I turned and headed towards my home. A bit over a year before, I’d bought a house here in Qingcheng Mountain, one of the most revered of Taoist mountains, and I’d started running at about that time too.

At the foot of this mountain, I’d started a new journey, a journey of running. Training had taken me to nine countries and on nearly 200 runs. I’d clocked over 150 hours and 1400 kilometers running to get here. All of this lead me back to my new home, Qingchengshan.

This was more than just a run; it was homecoming.

Tracking Your Blood Pressure, a Vital Sign

Blood pressure is one of our vital signs, and having either elevated or low blood pressure can be a important sign of health problems. Both high and low blood pressure are highly correlated with various diseases and elevated mortality and morbidity risk.

Fortunately, for self-trackers and health-conscious individuals, blood pressure (BP) is both extremely cheap and easy to measure. All you need is a simple device to record your BP non-non-invsasively and, if you want to check your results over time, a method to log these results.

Once you have it logged a few times, it’s easy to understand your blood pressure numbers, do some simple analysis, and, if your numbers are off, to start an intervention to get your blood pressure under control.

In this post, I want to share some observations on why and how to track your blood pressure as well as how to understand your blood pressure readings too.

Ultimately, my takeaway is that I personally don’t need to check my blood pressure everyday using a blood cuff. Hopefully one day our wearables will be able to capture our BP. But at the same time, blood pressure is an important metric and devices are affordable. This situation translates into periodic BP checks with a cuff each month or quarterly. This kind of habit can ensure nothing unusual happens in your underlying health and gives you a solid data point long-term too.

How to Export Your Trakt Watching History for Free (and Do Some Data Analysis)

Trakt.tv is a great, free service for tracking your TV and movie watching. You can manually log what you watch or use additional integrations and tools to automatically track everything on Netflix and other places.

Whether your goal is to decrease your TV addiction or mere curiosity at knowing which shows you watch and when, Trakt is one of the best ways to quantify your media consumption. I’ve written previously about how track your TV and movie watching using Trakt. Personally my main usage is seeing my weekly viewing time statistic, which I can employ in my data-driven weekly review as a data point to better gauge how much tube time I spent and, if excessive, potentially take action.

Let’s go one step beyond the actual tracking and start leveraging our data. But first things first is getting our data.

Tracking services that don’t allow you to export your data should be avoided and honestly have a very bad data policy. Fortunately, Trakt provides a few options to export your data. One option is to become a VIP premium member and to download a CSV export directly from Trakt.tv. Alternatively, you can use a data aggregation service called Zenobase to pull your watching history directly from Trakt.

In this post, we will look at how to export your data from Trakt using Zenobase. First, we will look at how to integrate Trakt with Zenobase; second, at how to do basic data analysis around media time; and third, from there you can use Zenobase’s tools to explore the data, create visualizations and even download a full export of your TV and movie watching history on Trakt.