A score from 0 to 100% that shows how often you meet your ideal environmental conditions.
Understanding Preservation Metrics helps you know how you are doing.
The following example shows a temperature and relative humidity (RH) chart that is common in environmental monitoring reports.
Instead of complex charts, you can say, "We meet our RH goal 68% of the time, and this month, we achieved 100%."
This straightforward insight helps your team quickly understand performance and focus on improving the collection environment.
Range and Fluctuation Calculations
The following range and fluctuation calculations are for temperature, RH, and illuminance.
% in range
To calculate the percentage of time that your readings are within the set range:
- All of the readings within your specified levels are counted (shown as green bands on your analytics graphs).
- That number is divided by the total number of readings for the chosen period.
- That number is multiplied by 100% for the final percentage.
% in range formula
# of readings within your set levels / total # of readings for your period chosen * 100%
For a quick visual estimate, check how much of your line falls within the green bands on the graph.
Caution:
The % in range can be impacted by sensors that do not read every 15 minutes. Readings from sensors with less frequent reporting or imported data with longer intervals may skew the calculation.
Illuminance % in range is also calculated using this formula, although it currently cannot be visualized on the graphs.
% in flux
The % fluctuation calculation is a little bit more complex because we add a rolling 24-hour variable. The logic for what % of the time the readings are within the maximum allowed 24h-fluctuation set by the user is the following:
For every reading within the time period the user requests, the software looks at all the readings 12 hours before and 12 hours after. Within that 24h period, it subtracts the maximum reading it finds minus the minimum reading it finds.
This difference will be either under or over the maximum fluctuation the user has set (which can be found in the level profile settings). If the difference is below the target set by the user, it marks the reading as within specification.
If not, it marks it as outside specification. Once it has that in/out specification defined for every individual reading in the chosen time period, it divides all the within specification readings over the total number of readings for the period.
% in flux (fluctuation) formula
# of within specification readings / total # of readings for your period chosen * 100%
To visually see your % in fluctuation in Analytics v.1, follow these steps in the Analyze tab:
- In the Date Range section, select Aggregate by Daily.
- In the Additional section, enable Show 24H Fluctuation.
This displays a histogram below your sensor graph. The histogram shows a thin line representing your target maximum fluctuation. Each bar represents the max difference between readings over a 24-hour period. The more bars that fall under this line, the higher your % in flux.
This feature is not yet available in Analytics v.2. If this feature is a priority for you, please submit your feedback here.
Note
Illuminance does not use a fluctuation percentage; instead, cumulative lux hours are key for light exposure tracking.
Setting Levels
In this section, RH is used as an example, but the same range and fluctuation metrics apply to temperature and illuminance. These metrics depend on the levels you set for your collection spaces. The following graph helps you easily visualize your target levels, making it simple to monitor your environment's performance.
In this example, the RH range is set between 40-60% (shaded green band), with a daily fluctuation target of less than 10%.
For more information, see Set Relative Humidity Levels.
A quick look at the RH metrics (blue circles) on the right shows that you are within your target levels 15% and 19% of the time.
Making observations
Think of observations as a way to document your collection's story for others and your future self. When readings fall outside ideal levels, you can add annotations to help diagnose the issue.
When you combine readings, levels, metrics, and observations, you have a powerful set of tools to understand and improve your collection environment.
Important
Some users notice that the average % in range from individual sensor graphs does not match the Space Performance Report percentage. This is because the Space Performance Report calculates based on every data point, including manually uploaded imported data logger data, rather than averaging individual sensor percentages.