Our preservation metrics turn complex data into easy to understand numbers — Here's how it works.
Our Seven Preservation Metrics
Conserv has developed seven metrics to help guide you on your journey to better environmental monitoring for your collection
- % of Time in Range
- % of Time under Fluctuation
- Conserv Score
- Mold Risk Score
- Relative Damage Score
- Lux Hours
- Pest Occurence Index (POI)
These metrics are outlined in detail below and each has its own separate article that really gets into the weeds.
💡 Conserv cloud is a free, cloud-based environmental monitoring tool. To get started fill out our quick survey.
Why Preservation Metrics
Squiggly lines on a graph aren't very useful, but that's exactly what most environmental monitoring software gives you.
💻 Here's a screenshot of the analytics in the popular HOBOware software.
Preservation metrics go beyond squiggly lines and help you answer the important question, "How are we doing relative to our goals?"
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Connect with your preservation peers. Learn more about Conserv.
Start With Collection Goals
Conserv is oriented around your environmental goals for your unique collection.
Our "environmental levels" features allow you to set range and fluctuation goals for temperature, relative humidity, and light levels.
💡 Range is your target high, low, and average. As an example, you might aim for the temperature to be in a range between 65 and 75°F with an average reading of 70°F.
💡 Fluctuation is your target variation over a 24-hour period. As an example, you might aim for the temperature to not fluctuate more than 5°F during a day.
If you're not sure where to start on setting levels for your collection, someone from the Conserv team is happy to help.
Finally, we get to the preservation metrics! Each of these metrics has its own article if you want to dig in deeper.
💻 Here's a screenshot of Conserv analytics with key performance indicator (KPI) preservation metrics on the right.
% of Time in Range, % of Time under Fluctuation
We figure out the % of readings that are within your levels for temperature, relative humidity, and light levels.
With this information, you can easily say "We were within our temperature range 60% of the time last month, and 72% of the time this month. We're making progress."
📖 Read more in-depth about the range and fluctuation KPIs here
The Conserv Score combines temperature and relative humidity fluctuation numbers into a score from A (best) to E (worst).
The Conserv score is loosely based on scoring guidance developed by the Canadian Conservation Institute.
📖 Read more in-depth about the Conserv Score here.
Mold Risk Score
The Conserv mold risk score recognizes the temperature and relative humidity conditions that may encourage mold growth.
The score ranges from No Risk to High Risk. Spaces with indications of mold risk and collections in those spaces should be visually inspected for mold growth.
📖 Read more in depth about mold risk KPIs here
Relative Damage KPI
The Conserv relative damage score suggests how fast your collection is deteriorating compared to the estimated deterioration rate in your target environment.
A score of 1.15 means damage is occurring 15% faster than would be expected under optimal conditions; a score of 0.50 means damage is occurring 50% slower than expected.
Credit for this approach goes to Tim Padfield.
📖 Read more in-depth about the relative damage rate KPI here.
For starters, we've included the total dose of light exposure in lux hours in the Preservation KPI dashboard. Lux hours are determined by multiplying the amount of light exposure (in lux units) by the length of time of the exposure (in hours). For example, 50 lux for 10 hours and 100 lux for 5 hours result in the same dose of light exposure (500 lux hours). Reach out if there are other important calculations that you need for your collection.
Read more in-depth about how Conserv calculates cumulative light exposure
Pest Occurrence Index (POI)
The pest occurrence index is a research product from Jane Henderson and Christian Baars. The metric takes into account factors that may skew pest count data, like the number of pest monitors and space size, to normalize pest counts.
Baars, Christian and Henderson, Jane 2020. Novel ways of communicating museum pest monitoring data: practical implementation. Presented at: Integrated Pest Management (IPM) for Cultural Heritage, Stockholm, Sweden, 21–23 May 2019.
With preservation metrics you can get your team aligned on "how are we doing relative to our goals?"
The primary purpose of good metrics is not just to answer questions; Good metrics also help your organization ask better questions to address the root cause of problems.
Get Started with Conserv
Take Conserv's quick survey to get started with our free software or wireless data loggers. Join a growing group of museums, libraries, and archives that expect more.