Understanding your RALI Data
RALI's connected electronic devices and sensors can collect information as you use them. You may also provide information yourself through RALI's applications and services.
Together, these sources can create a history of measurements, events, activities, observations, and information you have provided.
Learning how to interpret this information can help you understand individual measurements, compare changes over time, recognize patterns, and put information from different sources into context.
Understanding Your Measurements
A measurement represents information captured by a device or sensor at a particular point in time or during a particular event.
When reviewing a measurement, don't look only at the number or result itself. Consider the context surrounding it.
Ask:
- When was the measurement collected?
- Which RALI device or sensor collected it?
- How does it compare with earlier measurements?
- What other information was recorded around the same time?
- Did you provide any information that adds context?
- Have you seen a similar measurement or change before?
An individual measurement provides one piece of information. Comparing it with other information can give you a more complete picture.
Comparing Measurements Over Time
One measurement is a snapshot. A history of measurements lets you see how your information changes over time.
When comparing measurements, start by looking at the period they cover. A recent change may look different when viewed across a day, week, month, or longer period.
Rather than focusing only on whether the latest measurement is higher or lower than the previous one, consider:
- the size of the change;
- how frequently similar changes occur;
- whether the change continues across additional measurements;
- how the current measurement compares with your previous range; and
- what other information was recorded during the same period.
Looking across multiple measurements can help distinguish an isolated change from a broader trend.
Understanding Changes in Your Data
Changes are easier to interpret when you examine what happened before, during, and after them.
If a measurement changes, compare it with your previous information. Look at when the change occurred, whether similar changes have occurred before, and what your devices and sensors recorded around the same time.
Information you provided can also add context.
For example, if you recorded an activity, event, observation, or other information around the time of a change, reviewing that information alongside your device and sensor data may help you better understand the circumstances surrounding it.
A change by itself does not necessarily explain why something happened. Use the information available around the change to understand it in context.
Understanding Trends and Patterns
As RALI collects information over time, trends and recurring patterns may become easier to recognize.
A trend describes the general direction of information across multiple measurements. Your measurements may increase, decrease, remain relatively consistent, or fluctuate while still showing a broader direction over time.
A pattern occurs when similar measurements, changes, events, or circumstances appear repeatedly.
When you notice a possible trend or pattern, ask:
- How many measurements does it include?
- How long has it been occurring?
- Does it appear at similar times?
- What other information appears alongside it?
- Does information you provided add useful context?
- Are there times when the expected pattern does not occur?
Looking at both repeated patterns and exceptions can help you understand your information more completely.
Combining Device, Sensor, and User-Provided Information
RALI can work with information from different sources, and each source can provide a different type of context.
Connected electronic devices can record information and events as you use them.
Sensors can capture measurements or detect changes automatically.
User inputs can add information that a device or sensor may not capture on its own.
When interpreting your data, consider these sources together.
For example, a sensor may record a change at a particular time. Your history may show whether similar changes have occurred before. Information you provided may add context about what was happening around that time.
Instead of looking at each source in isolation, consider how the information relates:
- What did the device record?
- What did the sensor measure?
- What information did you provide?
- When did each event occur?
- How does the information compare with your previous data?
- Have these circumstances appeared together before?
Reviewing multiple sources together can provide context that may not be apparent from any single piece of information.
Understanding Your Inputs
Information you provide can be an important part of interpreting your collected data.
Your inputs may describe an event, activity, observation, selection, preference, or other information relevant to what your devices and sensors recorded.
When reviewing your inputs, pay attention to timing. Compare when you provided the information with when related device or sensor measurements were collected.
You can also compare similar inputs across different periods. This may help you identify whether the same circumstances tend to appear alongside similar measurements or patterns.
User-provided information doesn't replace automatically collected data. Instead, it can provide another layer of context for understanding it.
Using Your Data
Once you understand where your information comes from, you can use it to explore how your data changes and relates over time.
You can use your RALI data to:
- Compare current and previous measurements.
- Review changes across different periods.
- Identify trends that develop over time.
- Recognize recurring patterns.
- Compare information from different devices and sensors.
- Use information you provided to add context to automatically collected data.
- Examine what happened before and after a particular measurement or event.
- Review related information together instead of relying on a single data point.
The purpose isn't simply to collect more information. It's to make the information you already have easier to understand and use.
Asking Better Questions About Your Data
When you're unsure how to interpret something in your data, start with the information surrounding it.
Useful questions include:
- What does this measurement represent?
- Where did this information come from?
- When was it collected?
- How does it compare with my previous information?
- Is this an isolated change or part of a trend?
- Have I seen this pattern before?
- What did my other devices or sensors record around the same time?
- Did I provide information that adds context?
- Does the pattern look different when I examine a longer period?
These questions can help you move from simply viewing data to understanding how different pieces of information relate to one another.
Using Automated Explanations
RALI may use automated systems to organize, summarize, compare, or explain information collected from your connected devices, sensors, and inputs.
When reviewing an automated explanation, consider the information behind it.
Look at which measurements or events are being discussed, the period being considered, and whether other information provides additional context.
For example, if an explanation identifies a change or pattern, you can review the underlying measurements, compare them with previous periods, and consider relevant information you provided.
Automated explanations can make information easier to explore. Understanding the underlying data and its context can help you use those explanations more effectively.
Building Understanding Over Time
The meaning of an individual measurement often becomes clearer when you can compare it with additional information.
One measurement provides a snapshot.
Multiple measurements allow comparison.
Measurements over time can reveal trends and patterns.
Information from different devices and sensors can provide additional context.
Information you provide can add details that automatically collected data may not contain.
By reviewing these sources together, you can develop a clearer understanding of what your information represents, how it changes, and how different pieces of data relate to one another.
RALI helps make collected information more understandable by giving you the tools and information to interpret your data, explore its context, and use it more effectively.