The Problem: You are a Chair for a SPIE conference, your review team has provided numerical ratings for all your oral and poster submissions, and now you have to sort through all the numbers and prepare a draft program.

The Solution: Use R!

1. Go into MySPIE into the “Review Presentations” section

2. Click on the Excel icon for “Reviewer Results” (with comments)

3. Save that file as a CSV into some directory on your machine. I saved mine to C:/SPIE12/PresRevs.csv

4. Download the R Statistical Software from http://www.r-project.org if you don’t already have it.

5. Open R and cut and paste the following code onto your R command line. (Note: Use YOUR OWN directory name or it won’t work… mine is SPIE12 on my hard drive for this year’s conference.)

setwd("C:/SPIE12")
spie <- read.csv("PresRevs.csv",header=TRUE)
names(spie)[1] = "tracking"
names(spie)[2] = "conference"
names(spie)[3] = "papernum"
names(spie)[4] = "title"
names(spie)[5] = "reviewer"
names(spie)[6] = "rating"
names(spie)[7] = "recommendation"
names(spie)[8] = "comments"
names(spie)[9] = "more.comments"
papermeans <- aggregate(spie$rating,by=list(papernum),FUN=mean,na.rm=TRUE)
t <-unique(spie$title)
all <- cbind(papermeans,t)
names(all)[1] = "papernum"
names(all)[2] = "mean.rating"
names(all)[3] = "title"
sorted <- all[rev(order(papermeans$mean.rating)),]
write.csv(all,file="ProcessedReviews.csv")
write.csv(sorted,file="SortedProcessedReviews.csv")

6. This will export two CSV files, one with all your processed reviews in order of the paper number, and the other in order of the highest ranked paper first.

7. Have fun preparing your program.

Note: If ANYONE uses this, let me know – would love to know that my solution for making my SPIE Chair life easier actually helped someone else too. Or, if you can think of improvements to make, I might be interested in coding those for future use too 🙂 Leave a comment or send an email. Thanks.

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I’m Nicole

Since 2008, I’ve been sharing insights and expertise on Digital Transformation & Data Science for Performance Excellence here. As a CxO, I’ve helped orgs build empowered teams, robust programs, and elegant strategies bridging data, analytics, and artificial intelligence (AI)/machine learning (ML)… while building models in R and Python on the side. In 2025, I help leaders drive Quality-Driven Data & AI Strategies and navigate the complex market of data/AI vendors & professional services. Need help sifting through it all? Reach out to inquire – check out my new book that reveal the one thing EVERY organization has been neglecting – Data, Strategy, Culture & Power.

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