Ben Schmidt's Recenter function, which is bascially a wrapper to Claudia Engel's code to fix polygon splitting in ggplot2. Her version, which includes some tweaks for later, is at http://www.stanford.edu/~cengel/cgi-bin/anthrospace/great-circles-on-a-recentered-worldmap-in-ggplot

The chief change in mine is that it can take either a dataframe of polygons (with a defined id field) or, additionally, a path that might weave back and forth across the seam on the globe (which otherwise will leave ugly streaks).

At some projections, it still fails (I think when handling certain concave polygons: I just tend to shift around by a degree or two, until it works.)

It may not work multiple times, since it assumes that you begin with data on a -180 to 180 scale, and shifts that to be centered around higher values. That could be easily fixed.

Recenter = function(
  data=world,
  center=260,
  # positive values only - US centered view is 260
  shapeType=c("polygon","segment"),
  idfield=NULL
  ) {

  #use inherited id column, or create a new one from breaks in the data
  if(is.null(idfield)) {
    data$id=factor(cumsum(is.na(data$long)))
    }else{
    data$id = get(idfield,pos=data)
    }

  # shift coordinates to recenter worldmap
  data$long <- ifelse(data$long <= center - 180 , data$long + 360, data$long)

  ### Function to regroup split lines and polygons
  # takes dataframe, column with long and unique group variable, 
  #returns df with added column named group.regroup
  RegroupElements <- function(df, longcol, idcol){
    g <- rep(1, length(df[,longcol]))
    if (diff(range(df[,longcol])) > 300) { 
      # check if longitude within group differs more than 300 deg, ie if element was split
      d <- df[,longcol] > mean(range(df[,longcol])) 
      # we use the mean to help us separate the extreme values
      g[!d] <- 1 
      # some marker for parts that stay in place (we cheat here a little, as we do not take into account concave polygons)
      g[d] <- 2 
      # parts that are moved
    }
    g <- paste(df[, idcol], g, sep=".") # attach to id to create unique group variable for the dataset
    df$group.regroup <- g
    df
  }

  ### Function to close regrouped polygons
  # takes dataframe, checks if 1st and last longitude value are the same, if not, inserts first as last and reassigns order variable
  ClosePolygons <- function(df, longcol, ordercol){
    if (df[1,longcol] != df[nrow(df),longcol]) {
      tmp <- df[1,]
      df <- rbind(df,tmp)
    }
    df
  }

  # now regroup

  if(shapeType[1]=="segment") {
    Gap = abs(c(0,data$long[-1]-data$long[-nrow(data)]))
    split = factor(cumsum(Gap>=300))
    splitVoyages = factor(as.numeric(factor(paste(split,get(idfield,pos=data)))))
    data$group=splitVoyages
  }
  # close polys
  if(shapeType[1]=="polygon") {
    data <- ddply(data, .(id), RegroupElements, "long", "id")
    data <- ddply(data, .(group.regroup), ClosePolygons, "long", "order") # use the new grouping var
    data$group = data$group.regroup
    }
    data
}