If you have the data as a CSV you can read it with read_csv() from the reader package. It will make smart choices about interpreting the data types, though you can override those with the col_types parameter if its assumptions are wrong.
For example, let's say that your data file looks like this:
"ID", "DateTime", "X", "Y", "Z"
1, "2016-01-01 00:00:00", 0, 0, 0
2, "2016-02-01 00:00:00", 20, -18.2, -4.00
3, "2016-03-01 00:00:00", 20, -10.9, -8.00
You can read that into a tibble like this:
library(readr)
df <- read_csv("datafile.csv")
Now, if you examine the class of df$DateTime you'll see that that it was properly interpreted as a date type.