A Scanner Darkly

The awkward phase. It’s an unpleasant nebulous moment between two well-defined points. That uncomfortable time as people go from childhood and adulthood. Or that fearful moment full of panic as you go from dating to being in a serious relationship with someone else. It’s that interim state where you’re no longer A but you’re not quite B either.

Medical reporting is currently in its own awkward phase.

In the not so distant past lies Paper Based Reporting – filling out forms using pen and pencil, typewriters, printing out reports and having physical copies of every document located somewhere. This is the world of triplicate, of faxes and envelopes, of white-out and paper shredders. Paper charts physically shipped or moved from practice to practice, facility to facility. Paperland, as I like to call it, does have its advantages, though: a physical document that proves that something happened and to which people can refer; an artifact that precisely records how something occurred at that date and time, without any fear of tampering; a collection of data that cannot be wiped out by a virus or any sort of IT snafu.

Meanwhile, in the not so distant future lies Electronic Based Reporting – entering every information via computers. Using synoptic reports to enter structured data, information is culled directly from machines (think of vital signs being automatically recorded and logged), or easily entered using touchscreens, mouse & keyboard or a stylus of some sort. Electronic reports allow for faster sending of information to a wider range of places. Specialized fields ensure consistency in language and information captured. Required fields and “checklist” approaches encourage more completeness in reporting and more pertinent information is readily captured.¹ However, Tronworld, as I’ll refer to it, has its own share of problems. Information can be lost or stolen without any physical backups. There’s ensuring that all systems are speaking the same language when interfacing, so there’s no loss of data or need to reformat the data every time you go from one system to another.

So, between here and there, betwixt Paperland and Tronworld, lies us currently. How are people bridging the divide between the two different modes of reporting? The answer…might surprise you.

What We Talk About When We Talk About Structured Data (Part 3)

In this post, the final attempt at making structured data make sense in our daily lives, we’re going to examine one last way that we use structured data. Part one was about baseball, and how statistics are captured and presented to followers of the sport. Part two focused on baking, and how synoptic reporting can find the most concise way of presenting the record of a particular event. So what is this final part of the trilogy about? Is it a synthesis of these Baseball and Baking? Baseking? Bakeball?

Best of Both Worlds

Sorry, David Wells, but I’m going with another All-American past time. Let’s jump in the car and hit the open road as we talk about driving directions!

Was it ever established why the fish don't fry in the kitchen?

We’ve all received those invitations for some event with the directions appearing in large block paragraphs. It looks more like a riddle to be solved than steps to get from here to there. Here’s an example of directions presented in a paragraph form, this one showing how to get from our mTuitive offices to MGM Grand at Foxwoods:

From mTuitive office, drive on Old Stage Road towards Route 6W. Stay on RT 6W as it merges with/becomes MA-25W and then I-195W until you reach the exit for I-95 South (to New York). Take I-95 South to Exit 92 in Connecticut. Go straight at the stoplight. At the next stoplight, turn right onto Route 2 West for eight miles. Take the Foxwoods Blvd / Ledyard Center exit. At the bottom of the exit bear right and take a left at the third light to arrive at the MGM Grand.

Again, it lays out everything perfectly fine, and if I were to follow them, I would be able to adequately go from work to losing all of my money at the craps table.

You Hustlin' Me, Boy?

Another way of viewing these directions is using the format one gets from a GPS device or from Google Maps.

What We Talk About When We Talk About Structured Data (Part 2)

In Part One of my attempt at bringing Structured Data from the lofty heights of rhetoric and down into the every day real world, I used America’s favorite 3 hours of intermittent action – Baseball!

I suggest a new strategy, R2: let the Wookiee win.

It was a good, illustrative example of structured data – however, it was a bit impractical. Not many people conduct baseball research using data collected by statisticians. Structured Data may still seem foreign to those not interested in mapping how badly the Red Sox will break your heart this season using metrics and regressions. So let’s get even more grounded and practical – and in doing so, we’ll also examine synoptic reporting, a term that tends to accompany structured data but is not a synonym. So let’s see how we utilize structured data on a near daily basis. Let’s all head to the kitchen!

Last Known Photo of the Inventor of the Double Down

What We Talk About When We Talk About Structured Data (part 1)

Still trying to find that needle...

Sometimes it feels like my job wholly consists of talking about structured data. I give definitions and abstract examples – but it’s not easy to help people understand the real benefits of it. And so, as I try to find the best way to get my point across, I often think of real world examples of how structured data is useful in our daily lives and why it tends to be preferable to unstructured, narrative text.

With that in mind – let’s go out to the ball park!

THAT's the Chicago way!

Baseball. America’s Past Time. The Sweet Science. City of Lights. The Ghost and the darkness.

…

Okay, I’m not the biggest baseball fan. I will watch playoffs and world series. But I do know that a lot of baseball is about numbers: strike outs, home runs, bases stolen, RBIs, wins, losses, saves, ERAs, pitches thrown. Each of these play a crucial factor in determining how well your team is doing or how a player is perceived by his fans. And, following theories like those laid out in Moneyball, these metrics can even determine who will be signed on to your favorite team.

So what does this have to do with structured data? Glad you asked!