Where pegs grow legs: hanging ideas on words

In two interesting blog posts about how the distinction between data and metadata is artificial, and that it is merely a functional difference, it caught my eye, so I thought I’d join in. We were also talking about this just the other day, in terms of data.gov, the site cataloging government data feeds. We felt that the site might be more accurately termed metadata.gov, since it stores data about data. (I don’t think it necessarily should be, because that would be more confusing to most)

I would argue that the physical world naturally distinguishes data and metadata, and not just in computer software. The human memory seems to do so, recording just the most important snippets of events and occurrences so that we are able to later reconstruct events past, and more importantly, find them in their complete form later. I remember places, but just enough to be able to find them again (and when I’m lucky, enough to be able to name and describe them to other interested people). I remember ideas in articles and books, but just enough to be able to summarize them later, and maybe find the full excerpt when I need it. What my brain remembers is clearly the data, but a distinct subset of the data.

Thought of in that way, metadata is the most pertinent, useful data about the data. That certainly makes it functional data. However, defining what that data is is difficult, because it clearly depends on who you ask. I find some things more pertinent than other individuals, and vice versa. But even in the physical world, I think it is entirely natural to be separating data from the metadata, as that is the only way that the finite, limited capacities of our minds are able to store our existence in a functional way.

So the distinction between metadata and data is a functional difference, but not merely one. Rather, the difference is existential, and without it in the physical world, we wouldn’t be able to function. In the computer world though, we could do without it, and hopefully with projects like FluidDB (I haven’t checked it out yet), as well as new approaches solving the limitations that keep metadata around (B-trees are still much faster than full scans), we’ll have new interesting possibilities in the digital world.

Of course, that doesn’t keep it from being messy. Where the distinction lies between data and metadata is well, in the eye of the beholder.

I recently bought a pocket sized GPS tracker that literally is meant to fit on your keychain.

I’ve been looking for something this simple for a while now – all I wanted to be able to do was keep track of where I’ve _been_ so that I can refer to it later with a full computer; for that, this device exceeds expectations. I have a motorcycle and it’s really nice to be able to show off routes and back roads I recommend taking, not to mention help remind myself where “that picturesque sunset view” was when I was serendipitously passing through a not-so-well-known part of town. Here’s a quick lowdown of what the Taiwanese designed Qstarz can do.

Features

The BT-Q1300S is primarily geared towards runners and the fitness minded since it includes a nice sweatproof arm band for physical activities. Don’t let that fool you though, because it packs a lot of functionality into a small device. It tracks latitude/longitude, plus altitude and speed over time. Like I was saying, it’s all of about the size of a regular keychain, and it only has one button, a couple of leds for status purposes, and a mini-usb port to connect to your computer in order to make the nice pretty graphs I’ve got below.

The device’s interface to start and stop logging, set a waypoint, and turn on/off takes a little time to learn, but is fairly simple and straightforward once you know what those are. For example, to turn on the device, hold the button for 4 seconds. Once it’s locked onto satellites (one of the leds starts blinking to let you know), press and hold the button again for another 2 seconds to start logging. From this point, you can save a waypoint by pressing the button each time you want to save a location, or just let it save waypoints automatically. To stop logging, press and hold for another 2 seconds. Now you’re back in power-save mode. 4 more seconds to turn it off completely. Voila.

Smart waypoint saving

If you’ve ever used a GPS device before, you’ll understand how frustrating it is to later view your trip and see “clusters of waypoints” saved on the same location, or worse, no waypoints between important roads at all because you were traveling too fast. This is the result of using only one dimension (time) for determining when to save waypoints, and it’s all too common in modern devices. One of my favorite things about the Qstarz is that you can configure it to save it across three separate criteria: time, distance, and speed. These can also be combined in any combination in a logical AND fashion, which adds to its flexibility. For example, you want to save waypoints every 1 second AND when you’ve gone greater than 50 feet AND you’re traveling faster than 5 mph. This is awesome when it comes to not logging unnecessary waypoints when you’ve come to a complete stop, or when you’re traveling really, really slow and don’t need an update every x seconds.

Let’s get to the demo!

Ok, the cool stuff now. Here is an example of a trip that I took recently. The software has the ability to export as an html file (hugging to Google Maps for the map), which I’ve included as an iframe here.

It also creates some interesting line graphs to view your datapoints. Here is an example of speed over time.

An example of one of the line graphs Qstarz creates.

What’s missing

I really wish I could give this device 5 stars, but there are a couple of important things that they forgot that unfortunately keep me from giving it ultimate honors. Most importantly, the software has no way to be able to edit waypoints. This is important if you want to build a view of part of your trip taken from the device, or if you find that some of the waypoints are inaccurate and you just want to delete them (this has happened). Since it creates the full kml and other formats for you on export, and since the software utilizes the Google Maps API within itself to view your waypoints as they are imported, this would be a trivial feature to add.

Additionally, but less important, the device’s software won’t create an export for plug-and-play into a blog like this one using an iframe. You see this on a lot of sites nowadays (including Google Maps), so it’d be nice to see this as well. I’m sure that the vast majority of bloggers wouldn’t have figured out how to take the html export and make it work in an iframe (I also had to add my site’s Google Maps API key to the html source, so if I weren’t a web software engineer, I think it would have been hard to get it to work).

While it may be old news for some, I still wanted to share what I think is definitely one of the best-of-the-best of data visualizations and data exploration I have seen. We should all take notes on, and look up to, how Hans Rosling uses the data to produce a much more vivid and valuable picture of his topic: global health.