Separating column using separate (tidyr) via dplyr on a first encountered digit

I think this might do it.

library(tidyr)
separate(dta, indicator, c("indicator", "period"), "(?<=[a-z]) ?(?=[0-9])")
#           indicator   period    values
# 1     someindicator     2001 0.2655087
# 2     someindicator     2011 0.3721239
# 3         some text 20022008 0.5728534
# 4 another indicator     2003 0.9082078

The following is an explanation of the regular expression, brought to you by regex101.

• (?<=[a-z]) is a positive lookbehind - it asserts that [a-z] (match a single character present in the range between a and z (case sensitive)) can be matched
• ? matches the space character in front of it literally, between zero and one time, as many times as possible, giving back as needed
• (?=[0-9]) is a positive lookahead - it asserts that [0-9] (match a single character present in the range between 0 and 9) can be matched

You could also use unglue::unnest() :

dta <- data.frame(indicator=c("someindicator2001", "someindicator2011",
                              "some text 20022008", "another indicator 2003"),
                  values = runif(n = 4))

# remotes::install_github("moodymudskipper/unglue")
library(unglue)
unglue_unnest(dta, indicator, "{indicator}{=\\s*}{period=\\d*}")
#>       values         indicator   period
#> 1 0.43234262     someindicator     2001
#> 2 0.65890900     someindicator     2011
#> 3 0.93576805         some text 20022008
#> 4 0.01934736 another indicator     2003

^{Created on 2019-09-14 by the reprex package (v0.3.0)}