Dynamically build call for lookup multiple columns

How can I dynamically lookup multiple fields and add by reference using character vector variable as argument. In below case I want to lookup two columns and get rid of i. prefix in them. Of course they can override already existing columns with the same name.

library(data.table)
set.seed(1)
ID <- data.table(id = 1:3, meta = rep(1,3), key = "id")
JN <- data.table(idd = sample(ID$id, 3, FALSE), value = sample(letters, 3, FALSE), meta = rep(1,3), key = "idd")
select <- c("value","meta") # my fields to lookup
j.lkp <- call(":=", select, lapply(paste0("i.",select), as.symbol))
j.lkp
# `:=`(c("value", "meta"), list(i.value, i.meta))
ID[JN, eval(j.lkp)]
# Error in eval(expr, envir, enclos) : could not find function "i.value"
ID[JN, `:=`(c("value", "meta"), list(i.value, i.meta))]
#    id meta value
# 1:  1    1     x
# 2:  2    1     v
# 3:  3    1     f

I'm aware of similar question but this one asks for vectorized argument during join and directly building call for j.
edit: I'm aware I can do it using .SDcols but then I cannot perform this by reference

This seems to be the most straightforward way to me:

ID[JN, (select) := mget(paste0('i.', select))]

In recent development version it has been made much easier

ID[JN, (select) := .list_of_fields,
   env=list(.list_of_fields=as.list(paste0('i.', select)))]

OLD solution before 1.14.1

Instead of mget or eval-parse there is still possibility to build the lookup call. While the mget is the most user friendly, this one is both flexible and actually corresponds to building the j expression.
Solution wrapped into batch.lookup helper function taking character vector of column names to lookup.

    library(data.table)
    set.seed(1)
    ID <- data.table(id = 1:3, meta = rep(1,3), key = "id")
    JN <- data.table(idd = sample(ID$id, 3, FALSE), value = sample(letters, 3, FALSE), meta = rep(1,3), key = "idd")
    select <- c("value","meta") # my fields to lookup
    batch.lookup = function(x) {
        as.call(list(
            as.name(":="),
            x,
            as.call(c(
                list(as.name("list")),
                sapply(x, function(x) as.name(paste0("i.",x)), simplify=FALSE)
            ))
        ))
    }
    batch.lookup(select)
    #`:=`(c("value", "meta"), list(value = i.value, meta = i.meta))
    ID[JN, eval(batch.lookup(select))][]
    #   id meta value
    #1:  1    1     x
    #2:  2    1     v
    #3:  3    1     f

To be fair this answer actually address call construction issue described by me as OP.

Here's the crude way:

myj <- parse(text=paste0("`:=`(",paste0(select,"=i.",select,collapse=","),")"))
ID[JN,eval(myj)]
#    id meta value
# 1:  1    1     x
# 2:  2    1     v
# 3:  3    1     f

Dynamically build call for lookup multiple columns

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