When you sit back in your black lab chair and stare into the near distance—waiting for valuable minutes while yet another piece of lab equipment warms up or your PC restarts—what do you think about?

Instead of focusing on how freezing cold it always is in the lab, its true it is but that’s not that interesting is it?, try daydreaming about what a perfectly useful lab tool could look like, and what would your “perfect” dataset look like? Because at Bored Owl, we’re listening, and we’re asking you.

We’ve already delved in previous blog posts into how the Eddie Data Hub is explicitly designed to bridge the gap between an initial lab prototype and a rugged, field-deployable instrument, and what that means for Eddie’s hardware design. But what does “bridging the gap” mean for Eddie’s data? 

How can we make data collected in a lab automatically as rigorous as an industrial, commercial instrument? I should qualify this by saying that the difference between lab experiments and industrial instruments is usually because of different demands for operational functionality. Industry requires autonomous operation and the ability for the industrial instrument to be monitored and interrogated in terms of environmental and process data as well as sensor data for fault finding and to enable process control within strict limits to maintain production yields. With this in mind there is some data usually missing from a lab setup because it doesn’t have the same operational demand to be autonomous.

The Chaos of the Context Gap

From my experience, “completeness” for lab data means capturing every single variable that could explain a shift in your telemetry (or sensor readings, if you prefer).

Imagine you are a lab manager or team leader. You’ve got a handful of staff and students all doing their own thing. It is often a state of controlled chaos if we’re upfront about the data control in this environment. Most labs use a fragmented range of tools to record information: a mountain of paper notebooks, stray data files, and frantic scribbles on scraps of paper because something broke down mid-run. It’s all floating around the lab, hidden in personal cloud folders, or buried in shared drives. 

When it’s time to write research papers or heaven forbid revise them long after the data was collected. Or when you need to make sense of a project long after staff turnover has occurred, a rough recording of manual steps and standard sensor values and an excel spreadsheet or some code isn’t enough. If the record of what actually happened to the data is incomplete, the data is unusable.

The Four Pillars of Complete Data

Bored Owl’s dream is for Eddie to provide a complete, unassailable data record for an experiment. To me, true completeness relies on four pillars:

• • Telemetry: Accurate, real-time sensor recordings that are strictly timestamped.

• • Procedural Context: An accurate record of physical interactions during the experiment (e.g., when a solution was spiked). In Eddie’s design, we plan to capture this via a physical lab-step recorder button. You tap the button to anchor the exact time a step occurred, then jump onto the dashboard later to type a description of the manual intervention.

• • Environmental Metadata: Accurate, timestamped ambient data. (A vital lesson taught to me by Jonathan in my past life as an experimental scientist -thanks Jonathan :)). Recording the environment allows data analysis algorithms to automatically filter out background noise or room correlations later on.

• • Internal Diagnostics & Lineage: Monitoring power input variations and tracking hardware configuration changes. If you swap to a new temperature sensor part-way through an experiment, Eddie logs the new part ID. If that swap introduces an anomaly, it can be diagnosed instantly.

By collecting the complete environmental, procedural, and electrical context out of the box, researchers never have to guess why a dataset looks the way it does.

  [ Telemetry ] + [ Procedural ] + [ Environmental ] + [ Diagnostics ]= THE COMPLETE EDDIE DATA RECORD

Turning Data into a Proactive Lab Consultant

Because Eddie handles the complex, invisible engineering essentials—like hardware watchdog timers, automatic reboot loops for frozen sensors, and datetime-stamped file writing—it completely frees up your mind to focus entirely on the science. Woohoo, am I right?

But if we’re still daydreaming, why not extend the idea even further? What else could Eddie bring to a scientist trying to create great experimental data to test their ideas?

Data is power. If we chose to layer an “AI helper” onto Eddie’s telemetry, accessible through simple terms in the Eddie IDE (Integrated Development Environment), it could actively suggest scientific and process improvements on the fly:

• • Catching Sensor Drift and Artifacts: Sensor drift is a common trap in applied science where a hardware flaw looks like a biological or chemical change. For example, if a UniProbe’s signal noise steadily increases, Eddie could flag that you likely have a fouled sensor rather than an actual fluid change.

• • Baseline Consistency Checks: Eddie could compare data from your current experimental run to a pre-uploaded baseline from a past experiment, ensuring your current run is long enough to capture all the features present in your baseline.

• • Cross-Referencing Room Noise: Since ambient changes or electrical noise can alter a process, Eddie can cross-reference physical spikes with its ambient temperature and power logs to isolate external interference.

Help Us Build the Future of the Lab

By giving Eddie the intelligence to analyze the quality and context of incoming data, it ceases to be just a rugged data acquisition box. It turns into a proactive lab partner that ensures your data is clean, scientifically sound, and completely ready for commercial-grade deployment.

Bored Owl wants your ideas to be a part of Eddie so that together, we can make it as good as it can be.

What would the dashboard for Eddie’s IDE need to look like to fulfil the promise of a complete data record for you? I’ve been dreaming up all the different graphs and features I’d like in my dashboard widget kit, tell me what you’d like included as standard?

We look forward to your comments, feature requests, and suggestions below!

Feel free to contact us directly anytime to give your input too.