diff --git a/R/format.data/BCI.R b/R/format.data/BCI.R
index 66c3682ae37bd7dfef2735a91988551a011a48dc..9aff47e9a55103bd5e23b56ef79073fb8dc3e705 100644
--- a/R/format.data/BCI.R
+++ b/R/format.data/BCI.R
@@ -79,7 +79,7 @@ vec.abio.var.names <- c("MAT", "MAP")
 vec.basic.var <- c("obs.id","tree.id", "sp", "sp.name","plot", "subplot", "D", "G", "dead", 
     "year", "htot", "x", "y", "census")
 data.tree <- subset(data.bci, select = c(vec.basic.var, vec.abio.var.names))
-write.csv(data.tree,file="../../output/process/data.tree.bci.csv")
+write.csv(data.tree,file="../../output/process/BCI/tree.csv")
 
 
 ###################################### MASSAGE TRAIT DATA Use HEIGHT_AVG, LMALAM_AVD, SEED_DRY
diff --git a/R/format.data/Canada.R b/R/format.data/Canada.R
index 8a3593a2f549fc01c0dd1cf322f36a00cbea0c95..fd956ae722fc6f840b466f16fe07085f8df10d77 100644
--- a/R/format.data/Canada.R
+++ b/R/format.data/Canada.R
@@ -68,5 +68,5 @@ vec.abio.var.names <- c("MAT", "MAP")
 vec.basic.var <- c("obs.id","tree.id", "sp", "sp.name","cluster","plot", "ecocode", "D", "G", "dead", 
     "year", "htot", "Lon", "Lat", "perc.dead","weights","census")
 data.tree <- subset(data.canada, select = c(vec.basic.var, vec.abio.var.names))
-write.csv(data.tree,file="../../output/process/Canada/data.tree.csv")
+write.csv(data.tree,file="../../output/process/Canada/tree.csv")
 
diff --git a/R/format.data/France.R b/R/format.data/France.R
index 34f78ef7df0287f84669306e5e6333d51fec55fe..36e646c3be1f183eaccae78986ed1ea3c435776e 100644
--- a/R/format.data/France.R
+++ b/R/format.data/France.R
@@ -20,7 +20,7 @@ res.quant.boot <- t(sapply(levels(factor(data.france[["espar"]])), FUN = f.quant
 data.max.height <- data.frame(code = rownames(res.quant.boot), Max.height.mean = res.quant.boot[, 
     1], Max.height.sd = res.quant.boot[, 2], Max.height.nobs = res.quant.boot[, 3])
 rm(res.quant.boot)
-write.csv(data.max.height,file='../../output/process/France/data.max.height.csv')
+write.csv(data.max.height,file='../../output/process/France/max.height.csv')
 rm(data.max.height)
 
 ########################################## FORMAT INDIVIDUAL TREE DATA change unit and names of variables to be the same
@@ -80,7 +80,4 @@ vec.abio.var.names <- c("MAT", "SAP", "sgdd", "WB.s", "WB.y", "WS.s", "WS.y")
 vec.basic.var <- c("obs.id","tree.id", "sp","sp.name", "cluster", "plot", "ecocode", "D", "G", "dead", 
     "year", "htot", "Lon", "Lat", "perc.dead", "weights","census")
 data.tree <- subset(data.france, select = c(vec.basic.var, vec.abio.var.names))
-write.csv(data.tree,file="../../output/process/France/data.tree.csv")
-
-
-
+write.csv(data.tree,file="../../output/process/France/tree.csv")
diff --git a/R/format.data/Fushan.R b/R/format.data/Fushan.R
index 74d5f9ba32aa277e40ed6f871f1f4595fec37aca..055413fac7ee99893d8fd89a4907d9fece8d0e0b 100644
--- a/R/format.data/Fushan.R
+++ b/R/format.data/Fushan.R
@@ -61,7 +61,7 @@ vec.abio.var.names <- c("MAT", "MAP")
 vec.basic.var <- c("obs.id","tree.id", "sp", "sp.name","cluster","plot", "ecocode", "D", "G", "dead", 
     "year", "htot", "Lon", "Lat", "perc.dead","weights","census")
 data.tree <- subset(data.fushan, select = c(vec.basic.var, vec.abio.var.names))
-write.csv(data.tree,file="../../output/process/data.tree.fushan.csv")
+write.csv(data.tree,file="../../output/process/Fushan/tree.csv")
 ############################################## COMPUTE MATRIX OF COMPETITION INDEX WITH SUM OF BA PER SPECIES IN EACH PLOT in
 ############################################## m^2/ha without the target species CANNOT DO WITHOUT A PLOT ID
 data.BA.SP <- BA.SP.FUN(id.tree = as.vector(data.fushan[["tree.id"]]), diam = as.vector(data.fushan[["D"]]), 
@@ -84,4 +84,4 @@ data.BA.sp <- merge(data.frame(tree.id = data.fushan[["tree.id"]], ecocode = dat
 if (sum(!data.BA.sp[["tree.id"]] == data.tree[["tree.id"]]) > 0) stop("competition index not in the same order than data.tree")
 ## save everything as a list
 list.canada <- list(data.tree = data.tree, data.BA.SP = data.BA.sp, data.traits = data.traits)
-save(list.spain, file = "../../output/process/list.canada.Rdata") 
+save(list.spain, file = "../../output/process/Fushan/list.canada.Rdata") 
diff --git a/R/format.data/NSW.R b/R/format.data/NSW.R
index ab3fde26beb57efc681981946924c1e85c4f4bd0..ce904fe77a72551e83eadae57ff2749d8d267834 100644
--- a/R/format.data/NSW.R
+++ b/R/format.data/NSW.R
@@ -114,7 +114,7 @@ vec.abio.var.names <- c("MAT", "MAP")
 vec.basic.var <- c("obs.id","tree.id", "sp", "sp.name","cluster","plot", "ecocode", "D", "G", "dead", 
     "year", "htot", "Lon", "Lat", "perc.dead","weights","census")
 data.tree <- subset(data.nsw, select = c(vec.basic.var, vec.abio.var.names))
-write.csv(data.tree,file="../../output/process/data.tree.nsw.csv")
+write.csv(data.tree,file="../../output/process/NSW/tree.csv")
 ############################################## COMPUTE MATRIX OF COMPETITION INDEX WITH SUM OF BA PER SPECIES IN EACH PLOT in
 ############################################## m^2/ha without the target species NEED TO COMPUTE BASED ON RADIUS AROUND TARGET
 ############################################## TREE species as factor because number
@@ -155,4 +155,4 @@ data.BA.SP <- data.BA.SP2
 # dev.off()
 ## save everything as a list
 list.nsw <- list(data.tree = data.nsw, data.BA.SP = data.BA.sp, data.traits = data.traits)
-save(list.nsw, file = "../../output/process/list.nsw.Rdata") 
+save(list.nsw, file = "../../output/process/NSW/list.nsw.Rdata") 
diff --git a/R/format.data/NVS.R b/R/format.data/NVS.R
index a77db644cc472cdfeb83817aff24f120ef8092b9..1192758d007758b9ff3ab1d81adf8af84f666b96 100644
--- a/R/format.data/NVS.R
+++ b/R/format.data/NVS.R
@@ -23,7 +23,7 @@ data.trait$Wood.density.mean <- data.trait$wood; data.trait$wood <- NULL
 data.trait$Wood.density.sd <- NA
 data.trait$Max.height.mean <- log10(data.trait$height.m); data.trait$height.m <- NULL
 data.trait$Max.height.sd <- NA
-write.csv(data.trait,file='../../output/process/NVS/data.trait.csv')
+write.csv(data.trait,file='../../output/process/NVS/trait.csv')
 
 
 
@@ -108,6 +108,4 @@ vec.abio.var.names <- c("MAT", "MAP")
 vec.basic.var <- c("obs.id","tree.id", "sp", "sp.name","cluster","plot", "ecocode", "D", "G", "dead", 
     "year", "htot", "Lon", "Lat", "perc.dead","weights","census")
 data.tree <- subset(data.nz, select = c(vec.basic.var, vec.abio.var.names))
-write.csv(data.tree,file="../../output/process/NVS/data.tree.csv")
-
-
+write.csv(data.tree,file="../../output/process/NVS/tree.csv")
diff --git a/R/format.data/Paracou.R b/R/format.data/Paracou.R
index dc6335334a855ad1c3d80ad8f40f8b20c8c3f7b8..a07a2c41e0372cafdd5d6777ca174b04d59da4c2 100644
--- a/R/format.data/Paracou.R
+++ b/R/format.data/Paracou.R
@@ -151,4 +151,4 @@ data.tree <- subset(data.tree,subset=not.in.buffer.zone)
 data.BA.sp <- subset(data.BA.sp,subset=not.in.buffer.zone)
 ## ## save everything as a list
 ## list.paracou <- list(data.tree=data.tree,data.BA.SP=data.BA.sp,data.traits=data.traits)
-## save(list.spain,file="../../output/process/list.paracou.Rdata")
+## save(list.spain,file="../../output/process/Paracou/list.paracou.Rdata")
diff --git a/R/format.data/Sweden.R b/R/format.data/Sweden.R
index 87abe8953fcda8a010440b56d147a76a82002a5b..2e673e1946f1f1fe8fa9ec296e9491365872c237 100644
--- a/R/format.data/Sweden.R
+++ b/R/format.data/Sweden.R
@@ -47,7 +47,7 @@ res.quant.boot <- t(sapply(levels(factor(data.swe[["sp"]])), FUN = f.quantile.bo
 data.max.height <- data.frame(code = rownames(res.quant.boot), Max.height.mean = res.quant.boot[, 
     1], Max.height.sd = res.quant.boot[, 2], Max.height.nobs = res.quant.boot[, 3], stringsAsFactors =FALSE)
 rm(res.quant.boot)
-write.csv(data.max.height,file='../../output/process/Sweden/data.max.height.csv') ### GEORGES NOT SURE WE SHOULD USE THAT
+write.csv(data.max.height,file='../../output/process/Sweden/max.height.csv') ### GEORGES NOT SURE WE SHOULD USE THAT
 
 #################
 ##### change the projection of xy to wgs84 lat long.
diff --git a/R/format.data/Swiss.R b/R/format.data/Swiss.R
index 3cfd9699fd9fad3bac45f1232e958f2d6b4ff685..175a8902d8c0bb3fc7c293602ec295e7ca4e034d 100644
--- a/R/format.data/Swiss.R
+++ b/R/format.data/Swiss.R
@@ -61,11 +61,7 @@ res.quant.boot <- suppressWarnings(t(sapply(levels(factor(data.swiss[["sp"]])),
 data.max.height <- data.frame(code = rownames(res.quant.boot), Max.height.mean = res.quant.boot[, 
     1], Max.height.sd = res.quant.boot[, 2], Max.height.nobs = res.quant.boot[, 3], stringsAsFactors =FALSE)
 rm(res.quant.boot)
-<<<<<<< HEAD
-write.csv(data.max.height,file='../../output/process/Swiss/data.max.height.csv')
-=======
 write.csv(data.max.height,file='../../output/process/Swiss/max.height.csv')
->>>>>>> Makefile for data processing
 
 ########################################## FORMAT INDIVIDUAL TREE DATA 
 data.swiss$G <- 10 * (data.swiss$dbh_diff)/data.swiss$year  ## diameter growth in mm per year
diff --git a/R/format.data/US.R b/R/format.data/US.R
index cac12685f35307561f2dea3f15f6c06e66663c78..c921af56b80940e83eea05bb189153b20e5f5e02 100644
--- a/R/format.data/US.R
+++ b/R/format.data/US.R
@@ -22,7 +22,7 @@ species.clean[["sp"]] <- paste("sp", species.clean[["sp"]], sep = ".")
 data.max.height <- read.csv("../../data/raw/US/FiaSpMaxHt.csv", stringsAsFactors = FALSE)
 data.max.height <- data.frame(sp=data.max.height$SpCd,Max.height.mean=data.max.height$Ht99,
            Max.height.sd=rep(NA,nrow(data.max.height)), Max.height.nobs=rep(NA,nrow(data.max.height)))
-write.csv(data.max.height, file = "../../output/process/US/data.max.height.csv")  ## I was planning to save processed data in that folder
+write.csv(data.max.height, file = "../../output/process/US/max.height.csv")  ## I was planning to save processed data in that folder
 
 #### READ DATA US
 data.us <- read.csv("../../data/raw/US/FIA51_trees_w_supp.csv",header=TRUE,stringsAsFactors =FALSE)