Two Types of Field Data Collection
There are two different types of field data that can be collected.
The first you can think of as raw footage – the most basic form of information that we, data collection vendors, gather and give back to the clients.
And they, in turn, feed it into their algorithm.
In other words, this field data helps to build the baseline functionality of the product.
The second occurs once there is a tangible product in-hand.
This type of field data is used for testing purposes.
Field testing should take place continuously throughout every stage of the product’s development life cycle. It’s closely related to field data collection and shares a lot of the same challenges.
Here, real-world end-users come on board to take the product out for a spin, use it as they would in a natural scenario.
The feedback they give shows what’s working and what is not.
If the device doesn’t react to a particular command, perhaps that’s a sign that a wider breadth of data needs to be collected for that function.
Importance of a Natural Environment
Regardless of the different types of field data, both are collected in the natural environment for which the product is intended to be used.
For example, companies developing in-car speech systems need data collected inside cars and by drivers who are—well—driving around.
If the in-car speech system reacts to the sound of your engine revving, or a car honking in the background, that could actually increase distracted driving.
This would compromise the safety of the driver and their passengers.
This example highlights the importance of field data collection (and subsequently, testing) to the success and usability of the product.
The process allows developers to see how their end-users interact with the device, as well as if there are any environmental hindrances to improve upon.
After all, you can’t have a sports wearable that breaks down if sweat gets into the seams, or that overheats and stops working when the sun is shining too brightly.
Challenges of Field Data Collection
As with any project, there are lots of moving pieces to manage.
Data collection projects in particular typically have very specific demographic requirements.
This may lead to hundreds or thousands of participants; multiple languages and/or accents; multiple countries and/or cities; specific age ranges and so on.
Thus, recruiting is one of the most interesting challenges we are often faced with.
Field data collection is in many cases also dependent on the weather. In rainy Vancouver, where Globalme is located, this can prove to be challenging.
Unless of course, we’re conducting field data collection for a voice-activated umbrella.
How do we solve this problem? In one particularly rainy winter, we packed our bags and moved our data collection project to sunny Arizona.
Doing so allowed us to provide the data our client needed year-round.
Equipment & Tools
Talking about moving, the project teams normally face quite a few logistical challenges as well.
Those include having access to the right equipment and tools and making sure the equipment will function reliably.
If the project requires a specific environment, you’ll also have to ensure the equipment makes it to the necessary destination.
Note: It can be tricky convincing border patrol that we aren’t spies when we have seven laptops, boxes full of wires, and multiple microphones on-hand.
How Data Collection Powers the Development of Emerging Tech
Ultimately, field data collection is a necessary part in the development of emerging technologies.
Apple wouldn’t have been able to come out with their new face-recognition technology without collecting facial imaging data from thousands of different people (in multiple stages of hair-growth) of different ethnicities and in different environments (in the evening, when it’s raining out, when the subject is backlit).
Speech recognition technologies such as Amazon’s Alexa wouldn’t be able to understand or respond to our voice-commands without having collected thousands of hours of speech data from people with accents, speech impediments, in different languages, with multiple voices or music playing in the background, and so on.
Luckily, we’re experts in the subject and have a host of experience with previous data collection projects. Check out our data collection services page for more information.
Free Data Collection Resources
Looking for resources to assist with your in-field data collection project? Check out these helpful resources:
The Ultimate Guide to Data Collection (PDF) – Learn how to collect data for emerging technology.
Alexa Wake Word Dataset (Audio Download) – Download 24 custom multilingual Alexa wake word samples to hear the difference data variance makes for your voice assistant
Eye Gaze Sample Set (Download) – Get a sample of high-quality eye gaze data.
Road, Car, and People Dataset (Download) – Training a system that requires road image data? Download our sample dataset.
Building an Advanced Smart Home AI (PDF) – What data collection is necessary to build an modern smart home AI system?
Want even more? Check our our Data Collection & Localization Resources page for more guides and downloads.
Considering field data collection? Let’s talk about collecting custom field data