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Notes from a panel II: Value of successful BBSRC grants

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This post follows on from the last post on BBSRC Responsive Mode funding. Another frequent question from applicants is:

“How much can I ask for?”

One answer is: the same amount as successful grants. This information is freely available and can be downloaded from the UKRI website. All awarded grants can be searched (even those that have completed) using their database. It’s possible to filter for Research Grants and by funder (in this case BBSRC). However, it can be difficult to tell what is a Responsive Mode award compared to other types of grant. There is also a BBSRC-only database available here. On the BBSRC website, they make the recent awards available. I found these files easiest to use. They can be loaded into R and analysed.

The BBSRC Requested Value is given in 1000s of GBP (£K). This value is the amount requested by the applicant. Given that the award is 80% of the full economic cost of the grant, then these figures should be multiplied by 1.25 to get the headline figure that applicants go in with.

There are three rounds per year and data is available from 2017 to the first round in 2019. A couple of things to note:

So the data-driven answer to the question above is that successful grants tend to be around £500K (requested value). This equates to one post-doc for three years with running costs, a few other items and then overheads.

Value for money can be taken into account by the committee when scoring the proposals so this is likely to affect expensive applications. In other words, the science proposed needs to be truly exceptional for a very expensive grant to be funded.

Want to rerun this analysis?

library(ggplot2)
df1 <- read.delim(file='BBSRCAwards.txt', header=TRUE, sep = '\t', stringsAsFactors=FALSE)
p1 <- ggplot(df1, aes(x=Round, y=ReqValue, colour=Round, fill=Round)) +
  geom_violin(fill='white') +
  geom_dotplot(binaxis='y', stackdir='center', position=position_dodge(0.9), binwidth=10) +
  stat_summary(fun.y=median, geom="point", size=2, shape = 23, fill = "white", position=position_dodge(0.9)) +
  labs(x = "Round", y = "BBSRC Requested Value (£K)")
p1
p2 <- ggplot(df1, aes(x=Round, y=ReqValue, colour=Panel, fill=Panel)) +
  geom_violin(fill='white') +
  geom_dotplot(binaxis='y', stackdir='center', position=position_dodge(0.9), binwidth=10) +
  stat_summary(fun.y=median, geom="point", size=2, shape = 23, fill = "white", position=position_dodge(0.9)) +
  labs(x = "Round", y = "BBSRC Requested Value (£K)")
p2
p3 <- ggplot(df1, aes(x=Panel, y=ReqValue, colour=Round, fill=Round)) +
  geom_violin(fill='white') +
  geom_dotplot(binaxis='y', stackdir='center', position=position_dodge(0.9), binwidth=10) +
  stat_summary(fun.y=median, geom="point", size=2, shape = 23, fill = "white", position=position_dodge(0.9)) +
  labs(x = "Panel", y = "BBSRC Requested Value (£K)")
p3

ggsave("ValueByRound.png", plot = p1)
ggsave("ValueByPanelAndRound.png", plot = p2)
ggsave("ValueByPanel.png", plot = p3)

The data is freely available here. I collated the available data into TSV format and added an extra column for the round.

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