Cutting Through the Jargon: Your Instrumentation Terminology Guide

When I first got into the world of instrumentation and monitoring, I quickly realized just how much jargon was floating around. It felt like there were a dozen different ways to describe the same thing. Half the time, I wasn’t sure if the person I was talking to and I meant the same thing at all, which is why I’ve written this article. My goal is to help clear up some of the confusion by breaking down a few terms that I’ve found particularly tricky or often misunderstood.

Now, I’m not claiming to be the ultimate authority on these definitions—and I’m definitely not trying to chisel them into stone. I’d actually love to hear your thoughts! If you’ve come across terms that tripped you up or noticed definitions used differently in the field, drop a comment below. There are plenty of terms out there that didn’t make it into this article, and I’m excited to explore those in future posts. Let’s work toward a shared understanding across our community, one term at a time.

I'll cover a lot of definitions in this article. Here's a linked list if you want to move back and forth between them a little more easily:

• Advanced Data-Acquisition System (ADAS)
  
  
• Data-Acquisition System (DAQ)
  
  
• Data Logger
  
  
• Data Logging System
  
  
• Fully Automated Data-Acquisition System
  
  
• Fully Manual Data-Acquisition System
  
  
• Gateway
  
  
• Gauge
  
  
• Instrument
  
  
• Leaf
  
  
• Measurement Device
  
  
• Monitoring System
  
  
• Node
  
  
• Probe
  
  
• Programmable Logic Controller (PLC)
  
  
• Remote Terminal Unit (RTU)
  
  
• Semi-Automated Data-Acquisition System
  
  
• Sensor
  
  
• Supervisory Control and Data Acquisition (SCADA)
  
  
• Transducer
  
  

What’s a DAQ Anyway? (And Other System Terms)

When it comes to collecting and managing data in the field, you’ll hear a lot of terms thrown around, sometimes even interchangeably. Here’s how I break them down:

DAQ (Data-Acquisition System)

A DAQ, or data-acquisition system, is essentially the full package. It includes the sensors that measure physical conditions, the data logger that either takes those measurements or receives them, the communications method(s) that sends the data, and the software that helps you make sense of it all—through analysis, visualization, and reporting.

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ADAS (Advanced Data-Acquisition System)

Think of an ADAS as a more advanced version of a DAQ. It does everything a typical DAQ does, but with extra capabilities like real-time analysis, remote access, and higher levels of automation. These systems are especially useful in situations where speed and precision matter, such as high-frequency data collection or more complex analytics in the field.

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Data Logging System

This usually refers just to the “data logging” part of a DAQ. It focuses on capturing and storing data but doesn’t necessarily include the sensors, communications, or processing software.

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Monitoring System

A broader, interchangeable term with DAQ—people may use it more casually to describe the overall system doing the monitoring.

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SCADA (Supervisory Control and Data Acquisition)

SCADA stands for Supervisory Control and Data Acquisition. These systems go beyond monitoring. They’re designed for real-time control and decision-making, often in industries such as power and energy, water treatment, oil and gas, and manufacturing. They measure, analyze, and then act—automatically triggering processes such as opening valves or powering equipment.

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Gateways and Nodes: What’s the Difference?

The term “gateway” is gaining a lot of traction in the instrumentation and monitoring industry. At conferences and trade shows, people often ask me if we make a gateway, usually because someone told them that they need a gateway. It’s a common buzzword, but many people aren’t totally sure what it means or how it fits into their system. Let’s clear that up, along with a few related terms.

Gateway

A gateway is a device that helps different communications systems “talk” to each other. It acts as a bridge, moving data between your DAQ and an external system such as a server or the cloud.

One of the most common gateway examples is a device that includes both a radio module and a cellular modem. In this setup, the gateway receives data from field measurement “nodes” via a radio, then transmits that data to a server using the cell modem. But gateways aren’t limited to just radio and cell; they can connect any combination of communications protocols. For instance, it could be a wired RS-485/Modbus system that collects data from nodes and sends them out via satellite.

In fact, by this definition, many Campbell Scientific data loggers can function as gateways. For example, a CR6 Automated Monitoring Platform equipped with an RF407-series spread-spectrum radio can receive data from multiple CRVW3s (vibrating wire data loggers), then send that data to a server using a CELL200-series cellular modem.

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Data Logger

A data logger is a device that automatically measures data from sensors or instruments and stores those readings. Think of it is as the backbone of most data-acquisition setups.

Some data loggers can communicate in multiple ways—radio, cellular, satellite, etc.—while others might use just a single method. If a data logger can communicate with more than one system and send data out externally, it can also function as a gateway. But that’s not always the case. Not every data logger is used as a gateway, and many data loggers are simply used as nodes in a larger system.

What sets a data logger apart from a gateway or node is its core job: measuring sensors and storing those measurements, reliably and automatically.

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PLC (Programmable Logic Controller)

In a SCADA system, a programmable logic controller (PLC) is like the brain behind the operation. It’s an industrial computer that takes in data—often from devices such as remote terminal units (RTU). It analyzes that data and then sends out control signals to automate actions. That could mean, for example, turning motors on or off, raising gates at a dam, or starting a water pump.

While PLCs are often thought of as stand-alone units, data loggers (such as the ones from Campbell Scientific) can also play this role. If the data logger has output capabilities, it can act as a simple PLC within a SCADA setup—handling both data and control in one compact device.

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Node

A node is a system or device that measures data from sensors and sends the data to a gateway. Unlike a data logger, a node doesn’t need to store that data long-term, but it can. Its job is to take measurements and pass them along, usually in real time.

In most systems, you’ll see multiple nodes connected to a single gateway, creating a network of measurements feeding into one central point. Campbell Scientific data loggers are often used as nodes in this kind of setup, capturing sensor data and transmitting them to or through a base station.

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Leaf

“Leaf” is another word for a node in DAQs but with one small distinction: it sits at the end of a nodal network branch. In other words, it doesn’t connect to any other nodes downstream, and it isn’t used to pass data along (unlike how a repeater functions in a radio network). The leaf is simply the final stop in that branch.

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RTU (Remote Terminal Unit)

An RTU is a tough, reliable field device used in SCADA systems to measure sensor data, transmit that data, and sometimes even control processes. Most often, RTUs are used to collect data from sensors and send the data back to the central SCADA system.

While RTUs can handle control tasks, that role is typically more common with PLCs. That said, Campbell Scientific data loggers can act as RTUs, especially because they can output a wide range of analog and digital signals, making them flexible and powerful in the field.

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What Counts as a Sensor? (And Why So Many Names?)

You’ll notice a lot of different words used for a device that measures a physical phenomenon. Here are several that I have seen over the years. Please note that this is not, by any means, an exhaustive list.

Sensor

A sensor is a device that detects something happening in the physical world—such as a change in temperature, pressure, light, or motion—and turns it into a signal, usually electrical or optical, we can read.

For example, a thermocouple senses temperature changes and converts them into a small voltage (a millivolt signal). Even a mercury thermometer is considered a sensor because it responds to temperature by expanding mercury up a glass tube, which you can visually read. Different sensors speak different “languages,” but they all help us understand what’s going on around us.

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Instrument

An instrument is a broader term than sensor that refers to any device or system used to measure, monitor, or control a physical quantity. Think of it as a complete package.

For example, a digital multimeter is an instrument. It can measure voltage, current, and resistance, but it also processes and displays the results so you can actually use the information. Instruments may contain sensors inside them, but they go a step further by helping you interpret or act on the data. Put simply, an instrument can make your data more meaningful.

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Transducer

A transducer is a device that converts one form of energy into another. Typically, it takes a physical input (such as pressure or force) and turns it into an electrical signal you can measure.

You’ll often hear “sensor” and “transducer” used interchangeably. That’s okay because they’re closely related. The main difference? A sensor might give you an electrical or optical output, but a transducer specifically refers to converting something into an electrical signal. So, while all transducers are sensors, not all sensors are transducers.

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Probe

A probe is a type of sensor or transducer that’s designed to be placed directly into the environment or system it’s measuring. Typically, a probe has a sensing element that comes into direct contact with whatever it’s monitoring.

For example, a pH probe is placed in a liquid to measure acidity levels right where the action is happening. The key feature of a probe is its form; it’s built to physically “reach in” and take a measurement at the source.

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Gauge

A gauge is a measuring instrument, often mechanical or analog, used to display values directly. You’ll see gauges commonly used to measure pressure, fluid levels, or mechanical dimensions.

Some gauges are mechanical, while others output an electrical or optical signal—similar to sensors. In fact, the terms "gauge" and "sensor" are sometimes used interchangeably, especially when the device is both measuring and displaying. For example, a strain gauge outputs an electrical signal, while a soil tensiometer might have a dial you read visually.

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Measurement Device

This is the catch-all term for any tool or system used to measure a physical parameter. It could be a sensor, an instrument, a probe, a gauge, or even an entire integrated setup.

For example, a laser distance meter qualifies as a measurement device. It might include a sensor to detect distance, a display to show the reading, and even built-in software to store or transmit that data. If it measures something, it fits under this umbrella term.

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Manual, Semi-Automated, or Automated? Let’s Talk about Workflow.

Instrumentation systems live on a spectrum from completely manual to fully automated. In this section, I want to define some of those discrete points along that line.

Fully Manual Data-Acquisition System

In a fully manual data-acquisition system, people handle every part of what I like to call “the data story.” That means taking measurements by hand, writing them down in a logbook or field notebook (Rite in the Rain^®, anyone?), and later processing that data manually—no automation involved.

There are some definite upsides to this approach. It’s low cost to get started, simple to implement, and you don’t need to learn any complicated systems or software. But manual systems also come with some challenges: they’re more prone to human error, can vary in accuracy, and tend to be time-consuming, which add up in cost over time. Plus, they’re limited by work schedules. Most data get collected only once a week or month and only during site visits, making this method very slow.

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Semi-Automated Data-Acquisition System

Semi-automated systems fall somewhere between fully manual and fully automated, and I have a couple of ways to define them, depending on which part of the process is automated.

One version is when a person takes the measurement manually but then enters it into a tablet or field computer, which digitizes and stores the data.

The other version is when sensors (also known as transducers—see above!) are used to take measurements, but the data are still collected manually. This version is the one we see most often. For example, you might have piezometers installed in a borehole but not connected to a data logger. Instead, someone uses a readout device—such as our VWAnalyzer—to manually take readings in the field.

This setup improves accuracy and reduces some human error compared to a fully manual system. But it still requires someone to physically visit each sensor, which means slower data collection and ongoing labor costs—some of the same challenges you face with manual systems.

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Fully Automated Data-Acquisition System

In a fully automated data-acquisition system, everything from taking measurements to storing and transmitting data happens electronically, with no human intervention needed after the system is up and running. Sensors are connected to a data logger, which records the data and either stores or sends that data to a computer, server, or the cloud for viewing and processing.

The benefits? These automated DAQs are incredibly accurate, highly efficient, and can collect data at rates that would be impossible to match manually. While the upfront investment may be higher, automated systems usually pay off over time. That’s because sending someone into the field to manually collect data is a recurring cost—and one that adds up quickly. An automated setup, on the other hand, can operate for years with minimal maintenance and no repeat site visits.

One challenge with automation is the learning curve. Setting up and managing this type of system can require a certain level of technical expertise. But the good news is this is getting easier. Many companies are working hard to make their systems more user-friendly. At Campbell Scientific, we offer helpful tools, including our Short Cut program generator, and we’re continually innovating to make our equipment easier to set up and use—even for those who are new to automated instrumentation.

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Final Thoughts

At a previous job as a technical writer, I learned just how powerful language can be. The right words can inform, enlighten, and educate—but the wrong ones? They can confuse, overwhelm, and leave people second-guessing.

My hope with this article is to move some of that tricky instrumentation jargon out of the “wait, what?” category and into the “oh, I get it now” zone. If even a few terms are clearer for you after reading this article, then I consider that a win.

This is just the start. If you’ve come across other terms that have caused confusion—or if you have different definitions based on your experience—I’d love to hear about them. Let’s keep the conversation going and build a shared vocabulary that helps us all work smarter and communicate more clearly in this field.

Please share your comments below.