MISTAKE_FIX: Not A Trait DataBase

####################
# ADD DOIs ##########
#####################
#Headers
#' @importFrom fulltext ft_get_si
#' @importFrom gdata read.xls
#' @importFrom utils read.csv read.csv2 read.delim read.table
#' @importFrom testdat sanitize_text
#' @importFrom tidyr unite
# -- this last import must be removed, because testdat isn't on cran (devtools::install_github("ropensci/testdat"))

.mesquita.2016 <- function(...){
  data <- read.delim(ft_get_si("10.5061/dryad.55610", "Data%20%28revised%29.txt"), header=TRUE)
  data <- data[,-c(2:4,7,9:10,12:13,17,25)]
  data$Species <- tolower(gsub(" ", "_", (data$Species)))
  colnames(data) <- c('species','longitude','latitude','average_female_adult_weight','mean_female_svl_adults','female_svl_at_maturity','offspring_svl','mean_clutch_size','mode_of_reproduction','clutch_per_year','clutch_frequency','relative_clutch_mass','foraging_mode','distribution','prefered_habitat_type')
  units <- c(rep(NA,2),'g', rep('mm',3),rep(NA,3),'g',rep(NA,5))
  return(.df.melt(data, "species", units=units))
}

.broeckhoven.2016 <- function(...){
  data <- read.xls(ft_get_si("10.5061/dryad.k186f", "Data%20for%20Dryad.xlsx"), skip=1)
  data <- data[,-c(23:102)]
  data$Species <- tolower(gsub(" ", "_", (data$Species)))
  names(data) <- tolower(gsub("\\.", "_", names(data)))
  units <- c(rep('mm',21))
  return(.df.melt(data, "species", units=units))
}

.rutschmann.2016 <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.qd5gj", "Rutschmann_AdaptationofPhenologyacrossPopulations_dataset.csv"),sep=';')
  names(data) <- tolower(gsub("X\\.", "", names(data)))
  data <- data[,-c(1:3)]
  data$species <- 'zootoca_vivipara'
  colnames(data) <- c('altitude','snout_vent_length','total_mass','parturition_year', 'parturition_day', 'mid_gestation_temperatures', 'forest_cover_coefficient','mountain_chain','species')
  units <- c('m','mm','g',NA,NA,'°C',NA,NA)
  data <- .df.melt(data, "species", units=units)
  return(data)
}

.kuo.2014 <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.p8740","personality_date1.csv"))
  data <- data[,-c(1:4,16)]
  colnames(data) <- c('diet','snout_vent_length','latency_to_e','perch_inspected','percent_time_newzone','percent_time_onperch','bite_force','tail_diameter', 'personality_principal_component_1','personality_principal_component_2','transformed_principal_component_1')
  data$species <- 'anolis_sagrei'
  units <- c('cm','min',NA,rep('%',2), 'N','cm',rep(NA,4))
  return(.df.melt(data, "species", units=units))
}

# .klomp.2016 <- function(...){
#   data <- read.csv('http://datadryad.org/bitstream/handle/10255/dryad.117914/draco_comparative%20data.csv?sequence=1')
#   names(data) <- tolower(gsub("\\.", "_", names(data)))
#
#   colnames(data) <- c('species', 'female_dewlap_area', 'male_dewlap_area_', sexual_dimorphism_in_dewlap_area__natural_logged_ sexual_size_dimorphism__svl_ sexual_dichromatism__chromatic_contrast_
#   data <- data[,-c(1:4,16)]
#   colnames(data) <- c('diet','svl','latency','perch_inspected','percent_time_newzone','percent_time_onperch','bite_force','tail_diameter', 'personality_principal_component_1','personality_principal_component_2','transformed_principal_component_1')
#   data$species <- 'anolis_sagrei'
#   units <- c('cm','min',NA,rep('%',2), 'N','cm',rep(NA,4))
#   data <- .df.melt(data, "species", units=units)
#   data$character$units <- NA
#   return(data)
# }

.wright.2004 <- function(...){
    raw <- read.xls("http://www.nature.com/nature/journal/v428/n6985/extref/nature02403-s2.xls", as.is=TRUE, skip=7)
    metadata <- data.frame(raw[,c("Code","Dataset","BIOME")],need_permission=TRUE)
    raw <- raw[,!names(raw) %in% c("Code","Dataset","BIOME","X","X.1","X.2","X.3","X.4","X.5","X.6")]
    raw$Species <- gsub(" ", "_", tolower(raw$Species))
    output <- .df.melt(raw, "Species", units=c(NA,NA,NA,NA,NA,"log10(mo)", "log10(g m-2)", "log10(%)", "log10(g m-2)", "log10(%)", "log10(%)", "log10(nmol g-1s-1)", "log10(micromol m-2s-1)", "?", "log10(nmol g-1s-1)", "log10(micromol m-2s-1)", "ppm"), metadata)
    class(output) <- "natdb"
    return(output)
}

.hintze.2013 <- function(...){
    data <- read.csv("http://www.sciencedirect.com/science/MiamiMultiMediaURL/1-s2.0-S1433831913000218/1-s2.0-S1433831913000218-mmc1.txt/273233/html/S1433831913000218/6bd947d6c0ccb7edd11cd8bf73648447/mmc1.txt", sep=";", as.is=TRUE, dec=",")
    data$metadata <- seq_len(nrow(data))
    data$name <- sapply(strsplit(tolower(sanitize_text(data$name)),split=" "), function(x) paste(x[1:2], collapse="_"))
    data <- data[,!names(data) %in% c("comment","family","citation_total","citation_prop_ane","citation_prop_dyso","citation_prop_endo","citation_prop_epi","citation_prop_hem","citation_prop_hydro","citation_prop_other")]
    return(.df.melt(data, "name"))
}

.cariveau.2016 <- function(...){
    data <- read.xls(ft_get_si("10.1371/journal.pone.0151482", 3), sheet="TableS1_v2")
    metadata <- data[,c(1:3,6)]
    data$species <- with(data, tolower(paste(genus, species, sep="_")))
    data <- data[-c(1:4,6)]
    data <- .df.melt(data, "species", units=c(NA, NA, NA, NA, NA, "#", "#", "#", "#", "mm","mm","mm","mm",NA,NA), metadata)
    return(data)
}

# Elton traits
# written by Sylvia
.wilman.2014a  <- function(...){
    data <- read.delim(ft_get_si("E095-178", "BirdFuncDat.txt", "esa_archives"))
    data <- data[,-c(1,23,34)]
    data <- .df.melt(data, "Scientific")
    data$numeric$species <- tolower(gsub(" ", "_", data$numeric$species))
    data$character$species <- tolower(gsub(" ", "_", data$character$species))
    data$numeric$variable <- gsub("BodyMass.SpecLevel", "total_mass", data$numeric$variable, fixed=TRUE)
    data$numeric$variable <- gsub("BodyMass.Value", "total_mass.Value", data$numeric$variable, fixed=TRUE)
    return(data)
}

.wilman.2014b  <- function(...){
    data <- read.delim(ft_get_si("E095-178", "MamFuncDat.txt", "esa_archives"))
    data <- data[,-c(1)]
    data <- .df.melt(data, "Scientific")
    data$numeric$species <- tolower(gsub(" ", "_", data$numeric$species))
    data$character$species <- tolower(gsub(" ", "_", data$character$species))
    data$numeric$variable <- gsub("BodyMass.SpecLevel", "total_mass", data$numeric$variable, fixed=TRUE)
    data$numeric$variable <- gsub("BodyMass.Value", "total_mass.Value", data$numeric$variable, fixed=TRUE)
    return(data)
}

#KW first attempt to be verified
.bellobedoy.2015a <- function(...){
    data <- read.csv(
        ft_get_si("10.6084/m9.figshare.1190766.v2","Mating success H americana.csv")
        )
    data$species <- "hetaerina_americana"
    metadata <- data.frame(id=data$id)
    data$id <- NULL
    data <- .df.melt(data, "species", c(NA, "#", "mm^2 ", "mm^2", "mm"), metadata)
    data$numeric$variable <- gsub("aspot", "wing_spot_area", data$numeric$variable, fixed=TRUE)
    data$numeric$variable <- gsub("awing", "wing_area", data$numeric$variable, fixed=TRUE)
    data$numeric$variable <- gsub("matings", "mating_events", data$numeric$variable, fixed=TRUE)
    data$numeric$variable <- gsub("lwing", "wing_length", data$numeric$variable, fixed=TRUE)
    return(data)
}
.bellobedoy.2015b <- function(...){
    data <- read.xls(
        ft_get_si("10.6084/m9.figshare.1190766.v2","mating occurrencePzoe_2010.xls")
        )
    data$species <- "paraphlebia_zoe"
    metadata <- data.frame(data$Individual)
    data$Individual <- data$Estatus <- NULL
    levels(data$Status) <- c("satellite.male", "territorial.male")
    return(.df.melt(data, "species", c(NA, NA, "mm", "mm", "?", "?", "log10(?)"), metadata))
}

.jones.2009a <- function(...){
    data <- read.delim(ft_get_si("E090-184", "PanTHERIA_1-0_WR05_Aug2008.txt", "esa_archives"))
    for(i in 1:ncol(data))
        data[data[,i]==-999 | data[,i]=="-999",i] <- NA
    metadata <- data[,c("MSW05_Order","MSW05_Family","MSW05_Genus","MSW05_Species","References")]
    data <- data[,!names(data) %in% names(metadata)]
    names(data) <- c("MSW05_Binomial", "X1.activity_cycle", "mass", "forearm_length", "head_body_length", "age_eye_open", "age_birth", "basal_metabolic_rate", "basal_metabolic_rate", "diet_breadth", "dispersal_age", "gestation_length", "habitat_breadth", "home_range", "individual_home_range", "interbirth_interval", "litter_size", "litters_per_year", "max_longevity", "neonate_mass", "neonate_body_length", "population_denisty", "population_group_size", "sexual_maturity_age", "social_group_size", "teat_number", "terrestrial", "trophic_level", "weaning_age", "weaning_mass", "weaning_body_length", "mass", "litters_per_year", "neonate_mass", "weaning_mass", "global_range_area", "max_latitude", "min_latitude", "mid_latitude", "max_longitude", "min_longitude", "mid_longitude", "min_human_population_density", "mean_human_population_density", "human_population_5p_n", "human_population_density_change", "mean_precipitation", "mean_temperature", "mean_actual_evapotranspiration", "mean_potential_evapostranspiration")
    units <- c(NA, "g", "mm", "mm", "days", "days", "mL/hour", "g", NA, "days", "days", NA, "km^2", "km^2", "days", "#", "#/year", "months", "g", "mm", "km^2", "#", "days", "#", "#", NA, NA, "days", "g", "mm", "g", "#", "g", "g", "km^2", "?", "?", "", "?", "?", "?", "n/km^2", "#/km^2", "#/km^2", ":", "mm", "0.1°C", "mm", "mm")
    data <- .df.melt(data, "MSW05_Binomial", units=units)
    
    data$character$species <- tolower(gsub(" ","_", data$character$species))
    data$numeric$species <- tolower(gsub(" ","_", data$numeric$species))
    return(data)
}

.ingram.2016 <- function(...){
  color <- read.csv(ft_get_si("10.5061/dryad.9vr0c", "Dewlap_data_archive.csv"))
  color <- color[,-c(1,3,4,7:11)]
  units <- c('cm', 'cm^2')
  color$Species <- paste0("anolis_",color$Species)
  return(.df.melt(color, "Species", units=units))
}

.munoz.2014 <- function(...){
  data <- read.table(ft_get_si("10.5061/dryad.q39h2", "Munoz_2014_AmNat_Dryad.txt"), header=T)
  names(data) <- c('species', 'clade', 'island','latitude','longitude','elevation','snout_vent_length')
  data$species <- gsub('A.','anolis_', data$species)
  units <- c('degrees', 'degrees', 'm','mm', rep(NA, 3))
  data <- .df.melt(data, "species", units=units)
  data$character$units <- NA
  return(data)
}

.artacho.2015 <- function(...){
  data <- read.csv2(ft_get_si("10.5061/dryad.qg062", "phenotypictraits.csv"), sep=';')
  data <- data[,-c(1:5,10,12:13)]
  data$species <- 'zootoca_vivipara'
  units <- c('mm', 'mm', 'g','C', 'J/h')
  data$SVL <- as.numeric(data$SVL)
  data$TTL <- as.numeric(data$TTL)
  data$weight <- as.numeric(data$weight)
  data$PBT <- as.numeric(data$PBT)
  data$RMR <- as.numeric(data$RMR)
  return(.df.melt(data, "species", units=units))
}

.kolbe.2011 <- function(...){
  data <- read.table(ft_get_si("10.5061/dryad.1d24c","21%20species%20means.txt"),header=T,sep = '\t')
  units <- c(rep('mm',20))
  data<-.df.melt(data, "Species", units=units)
  data$character$units <- NA
  return(data)
  }

.winchell.2016 <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.h234n","winchell_evol_phenshifts.csv"))
  data <- data[,-c(1:2,15:16)]
  data$species <- 'anolis_cristatellus'
  data$perch.diam.cm <- as.numeric(data$perch.diam.cm)
  units <- c(rep('C',3),'%','cm','cm','g',rep('mm',15), rep(NA, 3))
  data<-.df.melt(data, "species", units=units)
  data$character$units <- NA
  return(data)
}

.kamath.2016 <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.9vk07","KamathLososEvol_AnolissagreiMorphAvg.csv"))
  data <- data[,-c(1)]
  data$species <- 'anolis_sagrei'
  units <- c('mm','NA','mm^2','mm',NA)
  data<-.df.melt(data, "species", units=units)
  data$character$units <- NA
  return(data)
}

.husak.2016 <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.2d960","HusakFergusonLovern_Anolis_training_diet_alldata.csv"))
  data <- data[,-c(1)]
  data$species <- 'anolis_carolinensis'
  units <- c('NA',rep('mm',4), rep('g',3),rep('sec',2),'mm','%',rep('mg',4),'psi',rep('ng/mL',2),'NA','mg',rep('NA',4))
  data<-.df.melt(data, "species", units=units)
  data$character$units <- NA
  return(data)
}

# high impact invaders
# written by Sylvia
# Konrad tried to update units, turns out they're not reported with the data or in the paper WTF!
.case.2016 <- function(...){
    data <- read.csv("http://datadryad.org/bitstream/handle/10255/dryad.103099/Traits.2Feb2015.csv?sequence=1", sep = ",", header = TRUE)
    #units <- length(names(data))
    data <- .df.melt(data, "species")
    return(data)
}

# Will fix me please!!!
#issue with the setup
#.Tian.2016 <- function(...){
#  data <- read.xls("~/Documents/Programming/NerdClub/Trait_sheets/srep19703-s2.xls", as.is=TRUE)
#  for(i in 1:ncol(data))
#    data[ifelse(is.na(data[,i]== "â" | data[,i]== "âÂ§"), FALSE, data[,i]== "â" | data[,i]== "âÂ§"),i] <- NA
#  data[,-c(1,5,9,12)]
#  data$Space <- NULL
#  units <- c("sites", "species", "family", "IVI", "cm^2", "mg individual^-1", "Space","mm^2 mg^-1", "Î¼m", "mm^2", "%", "Space", "Î¼m", "%", "%", "Space", "classification", "Space", "Needle/Broad")
#  data <- .df.melt(data, "plant_spp", units=units)
#  return(data)
#}

.pearse.2014 <- function(...){
  data <- read.csv(ft_get_si("10.6084/m9.figshare.979288", 4), sep = ",", na.strings = c("","NA"))
  species <- rep(c("Carcinus_maenas"), nrow(data))
  data <- data.frame(species, data)
  metadata <- data[,c(2:3,8:15)]
  data <- data[,-c(2:3,8:15)]
  units <- c(rep(NA,7), "min", rep(NA,6))
  data <- .df.melt(data, "species", units=units, metadata)
  return(data)
}

.simmons.2014 <- function(...){
  data <- read.xls(ft_get_si("10.5061/dryad.42pg7", "Simmons%20%26%20Buzatto%202013.xlsx"), as.is=TRUE)
  species <- rep(c("Onthophagus_taurus"), nrow(data))
  data <- data.frame(species, data)
  metadata <- data[,11]
  data <- data[,-c(10:11)]
  units <- c(rep(NA,2), "mg", "mm", "mg", rep(NA, 5))
  data <- .df.melt(data, "species", units, metadata)
  return(data)
}

.grootemaat.2015 <- function(...){
    data <- read.xls(ft_get_si('10.5061/dryad.m41f1', 'Grootemaat%202015_FE_Dryad.xlsx'), sheet ='RAWdata', as.is = TRUE)
    # Ugh this is so kludgy...
    names <- names(data)
    data <- as.data.frame(as.matrix(data)[-1,], col.names=names, stringsAsFactors=FALSE)
    for(i in seq_along(names(data)))
        data[,i] <- type.convert(data[,i])
    names(data) <- names
    metadata <- data[,c(1,3)]
    data <- data[,-c(1,3)]
    units <- c(rep('mm',4), rep('g',2), rep('cm^2',2), 'cm^3', '1/cm', rep('g/cm^3',2), "odw", "cm^2/g", rep("%",4), 'NA', rep('sec',4), 'NA', 'NA')
    data <- .df.melt(data, "species", units, metadata)
    return(data)
}

.arnold.2016 <- function(...){
  data <- read.xls(ft_get_si("10.5061/dryad.t3d52", "Arnold_etal_2016_functecol_dataset.xlsx"), as.is = TRUE, skip = 3)
  species <- rep(c("Tribolium_castaneum"), nrow(data))
  data <- data.frame(species, data)
  metadata <- data[,c(2:7,24:25)]
  data <- data[,-c(2:7,23:25)]
  units <- c("µL CO2/h", "counts/h", "mg", rep("mm",7), rep("mm/s",2), rep("count",3), NA, NA, NA, NA, "days", NA, NA, NA)
  data <- .df.melt(data, "species", units, metadata)
  return(data)
}

.simpson.2015 <- function(...){
  data <- read.csv("http://datadryad.org/bitstream/handle/10255/dryad.99379/Plant%20trait%20data.csv?sequence=1")
  metadata <- data[,c(2:3)]
  data <- data[-c(2:3)]
  data$Species <- gsub(" ","_",data$Species)
  data <- .df.melt(data, "Species", units = c(NA, NA, "m", "m", "g", "g", "g/g", "g/cm", "SA/vol", "kJ/g"), metadata)
  return(data)
}

.martin.2016 <- function(...){
  data <- read.csv("http://datadryad.org/bitstream/handle/10255/dryad.127965/Martin%20et%20al.%20Functional%20Ecology.txt?sequence=1", sep = "\t")
  data$species <- rep("Coffea_arabica", nrow(data))
  metadata <- data[,c(1:10,12)]
  data <- data[-c(1:10,12)]
  units <- c("#","cm","cm","mm","mm","#","#","#","m^2","mm","m","mg","g","#","#","#",
            "#","#","#","#","#","#","#","#","g/m^2","#","g/cm^3","#","#","g/cm^2",
            "#","#","#","#","#", NA)
  data <- .df.melt(data, "species", units = units, metadata)
  return(data)
}

.gossner.2015 <- function(...){
  file<-tempfile()
  download.file("http://datadryad.org/bitstream/handle/10255/dryad.76638/ArthropodSpeciesTraits.txt?sequence=1",file)
  data <- read.delim(file)
  metaData <- data[,c(1:3)]
  data <- data[,-c(1:3,5,17)]
  units <- c("mm",rep(NA,10))
  data <- .df.melt(data,"SpeciesID",units=units, metadata)
}

.sherratt.2013<-function(...){
  file<-tempfile()
  download.file("https://datadryad.org/bitstream/handle/10255/dryad.47130/Ontogenetic%20allometry%20data.csv?sequence=1",file)
  data<-read.csv(file)
  data<-data[,-c(2:3,5)]
  units <- c("mm","cm","cm")
  data<-.df.melt(data,"Species",units=units)
}

.mccullough.2015<-function(...){
  file<-tempfile()
  download.file("http://www.sciencedirect.com/science/MiamiMultiMediaURL/1-s2.0-S0003347215003103/1-s2.0-S0003347215003103-mmc1.xlsx/272524/html/S0003347215003103/0bb76368c8bbec26cf11858140abe3e8/mmc1.xlsx",file)
  data<-read.xls(xls=file)
  units<-c("mm","mm")
  data<-.df.melt(data,"Species",units=units)
}

.grutters.2017<-function(...){
  link <- "http://datadryad.org/bitstream/handle/10255/dryad.128398/FE-2016-00091-Data-plant-traits-and-consumption.xlsx?sequence=1"
  data<-read.xls(link, na.strings=c(""," ","NA"))
  vars <- c("species", "native", "clade", "latitude_origin", "acquisition", "shared_pomacea", "consumption_rate_lymnaea", "shared_lymnaea",
           "consumption_rate_pomacea","c","n","p","dmc","total_phenolics","cn","cp","np","n_total_pheno")
  data <- data[-c(1),] #remove row with unit names
  data$plantScientificName = gsub(" ","_",data$plantScientificName) #replace spaces with underscore
  data$plantScientificName = gsub("-","_",data$plantScientificName) #replace hyphens with underscore
  data$plantScientificName <- sapply(strsplit(data$plantScientificName, "_"), function(x) paste(x[1:2], collapse="_"))
  data$plantScientificName = tolower(data$plantScientificName)
  colnames(data)<-vars
  metadata <- data[,c(2:6,8)]
  data <- data[,-c(2:6,8)]
  units <- c("mg g^-1 d^-1","mg g^-1 d^-1","percent_dry_weight", "percent_dry_weight",
            "percent_dry_weight", "g/g", "mg/g", "mol/mol","mol/mol","mol/mol", "mg g^-1 (mg g^-1)^-1")
  for(i in 2:ncol(data)){
    data[,i] = as.numeric(data[,i])
  }
  data <- .df.melt(data, "species",units=units, metadata = metadata)
  return(data)
}

.molinari.2014<-function(...){
  link <- "http://datadryad.org/bitstream/handle/10255/dryad.55089/Dryad_Final.xlsx?sequence=1"
  data <- read.xls(link)
  vars = c("species", "native", "life_form","abundance_2007","abundance_2008", "peak_flowering", "height", "seed_mass", "specific_leaf_area")
  colnames(data) = vars
  data$species = tolower(gsub(" ","_",data$species))
  metadata = data[,c(4:5)]
  data = data[,-c(4:5)]
  units = c(NA,NA,"month","m","mg","cm^2/g")
  data = .df.melt(data, "species",units,metadata)
  return(data)
}

.anderson.2015 <- function (...){
  file<-tempfile()
  download.file("http://journals.plos.org/plosone/article/file?type=supplementary&id=info:doi/10.1371/journal.pone.0166714.s002",file)
  data<-read.csv(file)
  metadata<-data[,c(2:4,44:46)]
  data<-data[,-c(2:4,44:46)]
  units<-c("cm","g","cm^2",rep("?",4),rep("cm^2",7),"?",rep("g",7),rep("mg/g",7),rep("cm^2/g",7),rep("g",4))
  data<-.df.melt(data,"Species",units=units,metadata=metadata)
  return(data)
}

.plourde.2014 <- function (...){
  file<-tempfile()
  download.file("http://datadryad.org/bitstream/handle/10255/dryad.65737/complete.individual.data.txt?sequence=1",file)
  data<-read.delim(file)
  metadata<-data[,c(1:3,14,16)]
  data<-data[,-c(1:3,14,16,31:39)]
  units<-c("g","cm^3",rep("g",2),"cm^3",rep("g",2),"cm^3","g",rep("cm",8),rep("g/cm^3",3),rep("cm^2",4))
  data<-.df.melt(data,"species",units=units,metadata=metadata)
  return(data)
}

.buzzard.2015 <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.s8f38", "FEBuzzardSpTraits.csv"), sep = ",", as.is = TRUE, na.strings = c("","NA"))
  data <- unite(data, species, genus, species, remove = FALSE)
  metadata <- data[,c(1:2,4:9,16:18)]
  data <- data[,-c(1:2,4:9,16:18)]
  units <- c(NA, "cm^2 g^-1", NA, "mg/g", rep(NA,3),"years", rep(NA, 5), "mg ha^–1", "?", rep(NA,3))
  data <- .df.melt(data, "species", units, metadata)
  return(data)
}

.philipson.2014 <- function(...){
  data <- read.delim(ft_get_si("10.5061/dryad.qn814", "EcologyEvolution_IntensivePlotsData_forDryad.txt"), sep = ",", as.is = TRUE)
  species <- tolower(gsub(" ", "_", data$Species, ignore.case = TRUE))
  data <- data.frame(species, data[,-1])
  metadata <- data[,c(2, 9:12)]
  data <- data[,-c(2, 9:12)]
  units <- c("%", "mm", "mm", "cm", "day_since_transplant", "survival_since_transplant", rep(NA, 4), "categorical_measure_occasion")
  data <- .df.melt(data, "species", units, metadata)
  return(data)
}

#KW attempt 2
.Aubret.2012a <- function(...){
  data <- read.xls(ft_get_si("10.5061/dryad.14cr5345", "Aubret%2053172.xlsx"), as.is=TRUE, sheet=1)
  data$species <- "notechis_scutatus"
  metadata <- data.frame(data$POPULATION, data$DATE)
  data$POPULATION <- NULL
  data$DATE <- NULL
  names(data) <- c("sex", "body_mass", "body_mass", "snout_vent_length", "snout_vent_length", "species")
  units <- c(NA, "g", "log10(g)", "cm", "log10(cm)")
  return(.df.melt(data, "species", units, metadata))
}

  ## WIP
.winchell.2016 <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.h234n","winchell_evol_phenshifts.csv"))
  data <- data[,-c(1:2,15:16)]
  data$species <- 'A.cristatellus'
  data$perch.diam.cm <- as.numeric(data$perch.diam.cm)
  units <- c(rep('C',3),'%','cm','cm','g',rep('mm',15), rep(NA, 3))
  return(.df.melt(data, "species", units=units))
}

#.mesquita.2015 <- function(...){
#    data <- read.delim(unzip(ft_get_si("E096-058-D1","Life_history_data_of_lizards_of_the_world.txt.zip", "esa_data_archives"), "Data files/Data (revised).txt"))
#    metadata <- data[,c("Species","Genus","Family","Population","Longitude","Latitude","Source","Sample.Size.Female.adult.weight","Sample.size.Mean.F.SVL.adults","Sample.size.Clutch.Size.")]
#    data <- data[,!names(data) %in% names(metadata)]
#    data$Species.1 <- tolower(gsub(" ", "_", data$Species.1))
#    return(.df.melt(data, "Species.1", c("g", "g", "mm", "mm", "mm", "mm", "#", NA, "#", NA, "cc/g", NA, NA, NA), metadata))
#}

#gossner.2015 <- function(...){
#    data <- read.delim(ft_get_si("E096-102", "HeteropteraMorphometricTraitsRAW.txt", "esa_archives"), as.is=TRUE, fileEncoding="UTF-8")
#}

.falster.2015 <- function(...){
    data <- read.csv(unzip(ft_get_si("E096-128","baad_data.zip", "esa_archives"), "baad_data/baad_data.csv"))
    # Note: units "m^2/m^2 are taken from the meta-data
    units <- c(NA,"mm","deg",NA,"m^2/m^2",NA,NA,NA,NA,"year","m^2","m^2","m^2","m^2","m^2","m^2","m^2","m^2","m^2","m^2","m^2","m^2","m^2","m^2","m^2","m","m","m","m","m","m","m","kg","kg","kg","kg","kg","kg","kg","kg","kg","kg","kg","m^2","kg/m^2","kg/m^3","kg/m^3","kg/m^3","kg/m^3","kg/kg","kg/kg","kg/kg","kg/kg","kg/kg","kg/kg")
    metadata <- data[,c(c("studyName","location","latitude","longitude","species","family"))]
    data$speciesMatched <- tolower(gsub(" ", "_", data$speciesMatched))
    data <- data[,!names(data) %in% names(metadata)]
    return(.df.melt(data, "speciesMatched", units, metadata))
}

.kelt.2015 <- function(...){
    data <- read.delim(ft_get_si("E096-155","Mammal_Home_Ranges.txt", "esa_archives"))
    names(data) <- c("taxon","order","family","trophic_group","body_mass","home_range","references","notes")
    data$taxon <- tolower(gsub(" ", "_", data$taxon))
    metadata <- data[,c("order","family","references","notes")]
    data <- data[,!names(data) %in% names(metadata)]
    return(.df.melt(data, "taxon", c(NA,"log10(g)","log10(ha)"), metadata))
}

.edwards.2015a <- function(...){
    data <- read.csv(ft_get_si("E096-202", "Table1.csv", "esa_archives"))
    metadata <- data[,c("isolate","taxon","synonym", "c_citation")]
    data <- data[,!names(data) %in% names(metadata)]
    units <- c(NA, "°C", "µmol photons m-2 s-1", "hr", "µm^3", "µm^3", "µmol/cell", "day^-1", "day^-1", "µmol L-1", "µmol L-1", "µmol N cell^-1 day^-1", "µmol N µmol C-1 day -1", "µmol N cell^-1", "µmol N µmol C-1", "µmol N cell^-1", "µmol N µmol C-1", "day^-1", "day^-1", "µmol L-1", "µmol L-1", "µmol N cell^-1 day^-1", "µmol N µmol C-1 day^-1", "µmol N cell^-1", "µmol N µmol C-1", "µmol N cell^-1", "µmol N µmol C-1", "day^-1", "day^-1", "µmol L-1", "µmol L-1", "µmol P cell^-1 day^-1", "µmol P µmol C-1 day^-1", "µmol P cell^-1", "µmol P µmol C-1", "µmol P cell^-1", "µmol P µmol C-1", "citation")
    return(.df.melt(data, "species", units, metadata))
}
.edwards.2015b <- function(...){
    data <- read.csv(ft_get_si("E096-202", "Table3.csv", "esa_archives"))
    metadata <- data[,c("isolate","volume_citation")]
    data$isolate <- data$volume_citation <- NULL
    data$species <- tolower(gsub(" ", "_", data$species))
    return(.df.melt(data, "species", "µm3", metadata))
}

.albouy.2015 <- function(...){
    data <- read.csv(unzip(ft_get_si("E096-203","Functional_data.zip", "esa_archives"), "Functional_data.csv"), sep=";")
    for(i in 11:17)
        data[,i] <- as.logical(data[,i])
    names(data)[18:19] <- c("minimum_depth", "maximum_depth")
    metadata <- data[,c("id","Super_class","Order","Family","Genus")]
    data <- data[,!names(data) %in% names(metadata)]
    data$Species <- tolower(gsub("_", " ", data$Species))
    return(.df.melt(data, "Species", c(NA,"cm","cm",rep(NA,8),"m","m",rep(NA,9)), metadata))
}

.yin.2015 <- function(...){
  data <- read.xls(ft_get_si("10255/dryad.86209","Species-XylemAnatomy.xlsx"), fileEncoding="UTF-8")
  metaData <- data[,2]
  data <- data[,-c(2,13)]
  units <- c(NA, NA, rep('um',6), NA, NA, NA)
  return(.df.melt(data,"Species",units=units, metadata))
}

.klomp.2016 <- function(...){
  data <- read.csv('http://datadryad.org/bitstream/handle/10255/dryad.117914/draco_comparative%20data.csv?sequence=1')
  names(data) <- tolower(gsub("\\.", "_", names(data)))
  colnames(data) <- c('species', 'female_dewlap_area', 'male_dewlap_area', "sexual_dimorphism_in_dewlap_area", "sexual_size_dimorphism_svl", "sexual_dichromatism_chromatic_contrast",'sexual_dichromatism_achromatic_contrast', 'female_dewlap_chromatic_contrast', 'male_dewlap_chromatic_contrast','female_dewlap_achromatic_contrast', 'male_dewlap_achromatic_contrast', 'light_level_auc','predation_category')
  data$species <- tolower(gsub(" ", "_", (data$species)))
  data$species <- gsub("\\(", "", (data$species))
  data$species <- gsub("\\)", "", (data$species))
  units <- c(rep('cm^2',2), 'cm^2 (nl)', 'cm', rep('JND', 6), 'nl', NA)
  data <- .df.melt(data, "species", units=units)
  return(data)
}

.dmitriew.2014 <- function(...){
  data <- read.csv('http://datadryad.org/bitstream/handle/10255/dryad.72954/DataDmitriew%26BlanckenhornJEB12488%202014.csv?sequence=1',sep=';')
  data$species <- 'sepsis_punctum'
  data <- data[,-c(4)]
  colnames(data) <- c('population', 'food', 'sex', 'family', "sire",'dam','development_time','fore_femur_width','mittibial_length', 'species')
  units <- c(rep(NA, 3), 'days', 'mm','mm',rep(NA,4))
  data <- .df.melt(data, "species", units=units)
  return(data)
}

.zhang.2014 <- function(...){
  data <- read.xls('http://datadryad.org/bitstream/handle/10255/dryad.73881/data_traits.xlsx?sequence=1')
  data <- data[,-c(1:2,5:6,8:11,16)]
  data$species <- 'sterna_hirundo'
  colnames(data) <- c('age', 'sex', 'lifespan', 'egg_volume', 'clutch_size', 'brood_size', 'no_fledglings', 'species')
  units <- c('years',NA,'years', rep(NA,4))
  data <- .df.melt(data, "species", units=units)
  return(data)
}

.shibata.2015a <- function(...){
  data <- read.xls(ft_get_si("10.5061/dryad.rj480","FEShibataDataForAnalyses.xls"), fileEncoding="UTF-8")
  metadata <- data[,14]
  data <- data[,-c(14)]
  units <- c(rep('%',6), NA, NA, 'cm^2', 'g m^-2', 'MN/m^2', '%', 'g/cm^3')
  return(.df.melt(data,"Species",units=units, metadata))
}

.shibata.2015b <- function(...){
  data <- read.xls(ft_get_si("10.5061/dryad.rj480","FEShibataDataForAnalyses.xls"), fileEncoding="UTF-8", sheet=2)
  metadata <- data[,15]
  data <- data[,-c(15)]
  units <- c(NA, NA, rep('cm^2',3),'g/cm^3', 'g m^-2', 'MN/m^2', rep('%',5), NA)
  return(.df.melt(data,"Species",units=units, metadata))
}

.cavender.2015a <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.855pg","Freezing.vulnerability.csv"), fileEncoding="UTF-8")
  data <- data[1:758,]
  metadata <- data[,c(2,3)]
  data <- data[,-c(2,3)]
  units <- c('C', 'C', '%', '%')
  return(.df.melt(data,"Species",units=units, metadata))
}

.cavender.2015b <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.855pg","Tree.height.csv"))
  data <- data[1:109,1:8]
  metadata <- data[,2:6]
  data <- data[,-c(2:6)]
  units <- c("m", 'cm')
  return(.df.melt(data,"Species",units=units, metadata))
}

#principal components are metadata
.cavender.2015c <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.855pg","PCA_All_Virentes.csv"))
  metadata <- data[,c(1,2,4:9,11:18)]
  data <- data[,-c(1,2,4:9,11:18)]
  names <- data['Species']
  for(i in 1:17){
    p <- c('BR', 'FU', 'GE', 'MN', 'OL', 'SA','VI','FU2', 'OL2', 'SA2', 'VI2', 'VI3', 'MN2', 'VI4', 'GE1', 'GE3', 'HY')
    r <- c("q_brandegeei","q_fusiformis", "q_geminata", "q_minima", "q_oleoides", "q_sagraena", "q_virginiana", "q_fusiformis2", "q_oleoides2", "q_sagraena2", "q_virginiana2", "q_virginiana3","q_minima2", "q_virginiana4", "q_geminata1", "q_geminata3", "hybrid")
    names[,1] <- gsub(p[i], r[i], names[,1])
  }
  units <- c("mm^2", 'mm^2','C','C','%','%',rep('C',7),rep('mm',3),'NA',rep('mm',4), 'C', 'C', '%', 'NA', rep('C',7), rep('mm',3), 'NA', rep('mm',4))
  return(.df.melt(data,"Species",units=units, metadata))
}

.limpens.2013a <- function(...){
  data <- read.xls(ft_get_si("doi:10.5061/dryad.926nd", "Motherfile.xls"), as.is = TRUE)
  species <- gsub("gla", "picea_glauca", data$Species)
  species <- gsub("mar", "picea_mariana", species)
  species <- gsub("rub", "picea_rubens", species)
  species <- gsub("sit", "picea_sitchensis", species)
  species <- gsub("ban", "pinus_banksiana", species)
  species <- gsub("nig", "pinus_nigra", species)
  species <- gsub("syl", "pinus_slyvestris", species)
  data <- data.frame(species, data[,-3])
  metadata <- data[,c(2:4)]
  data <- data[,-c(2:4)]
  units <- c(rep("cm",2), "mm/day", "mg", rep("cm",2), "mm/day", "mg", "cm/cm", "mg/mg", "mg", rep(NA,3))
  data <- .df.melt(data, "species", units, metadata)
  return(data)
}

.fitzgerald.2017 <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.67140", "traits.csv"), sep = ",", as.is = TRUE)
  species <- tolower(gsub(".", "_", data$species, fixed = TRUE))
  species <- gsub("sp_", "sp.", species)
  data <- data.frame(species, data[,-1])
  data <- data[,-c(2, 9:12)]
  units <- c(rep("log(mm)", 5), "mm^1/2", "mm^1/3", "mm", "mm^1/2", "mm", "mm^1/2", "mm", "mm^-1", "log(mm)", "mm", "mm", "log(mm)", rep("mm", 3), "log(mm)", rep("mm", 4), "mm^-1", "log(mm)", "mm^-1/3", rep("mm^1/2",2), "mm^1/3", rep("mm",2), "mm^-1", rep("sqrt(mm)",2), "mm", "sqrt(mm)", rep("mm^-1/4",2), "mm", "log(mm)", rep("mm",3))
  data <- .df.melt(data, "species", units)
  return(data)
}

.pigot.2015 <- function(...){
    data <- read.xls(ft_get_si("10.5061/dryad.fd986","Database%20S1%20Pigot%2c%20Trisos%20and%20Tobias.xls"), as.is=TRUE)
    data <- data[,-c(26:28)]
        for(i in 12:15)
    data[,i] <- as.logical(data[,i])
    names(data)[3:11] <- c("Min.Elevation","Max.Elevation","log.Bill.Length","log.Bill.Width","log.Bill.Depth","log.Tarsus.Length","log.Kipps.Distance","log.Wing.Length","log.Tail.Length")
    names(data)[26] <- "Museum.Institution.codes"
    units <- c(NA,"m","m",rep('mm',7),rep('NA',4),rep('%',10),NA)
    metadata <- data[,c(1,3:4,26)]
    data <- .df.melt(data, "Binomial", units=units, metadata=metadata)
    return(data)
}

.marx.2016 <- function(...){
    data <- read.csv("https://ndownloader.figshare.com/files/6854532")
    names(data)[3:7] <- c("Seed.Mass","Maximum.Height","","Leaf.Size","Leaf.Nitrogen")
    units <- c("native/invasive","mg","m","cm^2/g","cm^2","specific_leaf_area")
    metadata <- data[,2]
    data <- .df.melt(data, "Species", units=units, metadata=metadata)
    return(data)
}

.olli.2015 <- function(...){
    data <- read.table("https://datadryad.org/bitstream/handle/10255/dryad.90019/fd.txt?sequence=1", header = T, sep = '\t')
    for(i in c(1:9,11))
        data[,i] <- as.logical(data[,i])
    units <- c(rep('NA',9), "micrometer", NA)
    data$species <- rownames(data)
    data <- .df.melt(data, "species", units=units)
    return(data)
}

#KW
.Aubret.2012b <- function(...){
  data <- read.xls(ft_get_si("10.5061/dryad.14cr5345", "Aubret%2053172.xlsx"), as.is=TRUE, sheet=2)
  data$X <- data$X.1 <- data$X.2 <- data$X.3 <- data$BCI <- NULL
  data$species <- "notechis_scutatus"
  metadata <- data[,c("POPULATION", "MOTHER", "BIRTH.DATE")]
  data <- data[,!names(data) %in% names(metadata)]
  names(data) <- c("snout_vent_length", "body_mass_pre", "body_mass_pre", "body_mass_post", "body_mass_post", "bm_body_mass_post", "rcm", "total_litter_body_mass", "total_litter_body_mass", "total_litter_snout_vent_length", "total_litter_snout_vent_length", "total_litter_jaw_length", "total_litter_jaw_length","species")
  units <- c("log10(cm)", "g", "log10(g)", "log10(mean(cm))", "g", "log10(g)", "?", "?", "mean(g)", "log10(mean(g))", "mean(cm)", "log10(mean(cm))", "mean(cm)", "log10(mean(cm))", NA)
  return(.df.melt(data, "species", units, metadata))
}

.Aubret.2012c <- function(...){
  data <- read.xls(ft_get_si("10.5061/dryad.14cr5345", "Aubret%2053172.xlsx"), as.is=TRUE, sheet=3)
  names(data) <- c("genus_species", "body_mass", "max_circumference")
  units <- c("g", "cm")
  return(.df.melt(data, "genus_species", units))
}

#KW
.Jennings.2015 <- function(...){
  data <- read.csv(ft_get_si("E096-226", "SIA_N_C_Atlantic_marine_fishes_squids_20150105_v1.csv", "esa_archives"))
    metadata <- data[,c("record", "year", "DOY", "latitude", "longitude", "sea")]
    data <- data[,!names(data) %in% names(metadata)]
    units <- c(NA, "g", "%", "%", "?", "?")
    return(.df.melt(data, "species", units, metadata))
}

.deraison.2014 <- function(...){
    data <- read.xls(ft_get_si("10255/dryad.72345","Plant%20traits.xls"), sheet = 2)
    name.data <- read.xls(ft_get_si("10255/dryad.72345","Plant%20traits.xls"), sheet = 1)
    data$Plant.species <- name.data$Species.name[1:22]
    names(data) <- c("species","leaf_dry_matter", "leaf_nitrogen_content", "leaf_carbon_content", "leaf_carbon_nitrogen_ratio", "leaf_thickness", "leaf_area", "perimeter_leaf_length_ratio")
    data <- data[,1:8]
    units <- c("%", rep("% g",2), NA, "mm", "cm^2", NA)
    data <- .df.melt(data, "species", units=units)
    return(data)
}

.ameztegui.2016 <- function(...){
    data <- read.xls(ft_get_si("10.5061/dryad.12b0h/2","FunctionalTraits_Dryad.xlsx"))
    data <- data[,-c(1,7,8)]
    names(data)[4:14] <- c("Phylum","leaf_habit","specific_leaf_area","photosynthetic_capacitity_per_unit_leaf_mass","N_content_per_unit_mass","P_content_per_unit_mass","leaf_lifespan","leaf_length","seed_mass","wood_density","max_tree_height")
    units <- c(rep(NA,3),"deciduous/evergreen","m/kg","mmol CO2/g s","%","%","month","mm","mg/seed","g cm^3","m")
    metadata <- data[,2:4]
    data <- .df.melt(data, "SpName", units=units, metadata=metadata)
    return(data)
}

.plourde.2015 <- function(...){
  data <- read.delim(ft_get_si("10.5061/dryad.sv181", "complete.individual.data.txt"))
  data <- unite(data, species, genus, species, remove = FALSE)
  data <-data[,-c(4:5)]
  data$species <- tolower(data$species)
  metadata <- data[,c(1:2,13,15,30:34,38)]
  data <- data[,-c(1:2,13,15,30:34,38)]
  units <- c("g", "cm^3", rep("g",2), "cm^3", rep("g",2), "cm^3", "g", "cm", rep("cm", 7), rep("g/cm^3",3), rep("cm^2", 4),  "?", "?", "%", NA, NA, NA, "Na", "intercept", "y/x", "r^2", "pvalue", "class", "y/x")
  data <- .df.melt(data, "species", units, metadata)
  return(data) 
}

#.delgado.2016 <- function(...){
#  data <- read.xls(ft_get_si("10.5061/dryad.1tj60","Delagado_etal_2016_Appendix2.xlsx"), fileEncoding='UTF-8',sheet=1)
#  data <- data[1:109,1:8]
#  metadata <- data[,2:6]
#  data <- data[,-c(2:6)]
#  units <- c("m", 'cm')
#  return(.df.melt(data,"Species",units=units, metadata))
#}

.kefi.2016 <- function(...){
  link = "http://datadryad.org/bitstream/handle/10255/dryad.116249/chilean_metadata.xls?sequence=1"
  data <- read.xls(link)
  vars <- c("id", "species", "body_mass", "sessile_mobile", "cluster", "shore_height_conservative", "shore_height_C_ordinal",
            "shore_height_C_breadth", "shore_height_2_restrictive", "shore_height_R_ordinal", "shore_height_r_breadth",
            "phyllum", "subphyllum", "trophic")
  colnames(data) <- vars
  data$species <- tolower(gsub(" ","_", data$species))
  metadata <- data[,c(1, 6, 9, 12:13)]
  data <- data[,-c(1, 6, 9, 12:13)]
  units <- c("?",NA,"?", "?","?","?","?",NA)
  data <- .df.melt(data, "species", units, metadata)
  return(data)
}

.petry.2016 <- function(...){
  link <- "http://datadryad.org/bitstream/handle/10255/dryad.119003/PollenMovement.csv?sequence=1"
  data <- read.csv(link)
  data$species = rep("valeriana_edulis", nrow(data))
  metadata <- data[,c(1)]
  data <- data[,-c(1)]
  units <- c("#","#","#","#","#","#","#","#","#","#","m","m","m","m","m","m")
  data <- .df.melt(data, "species", units, metadata)

  return(data)
}

#.maire.2016 <- function(...){
#    link <- "http://datadryad.org/bitstream/handle/10255/dryad.119139/globamax_data_160609%20%28for%20GEB%20ms%29.xlsx?sequence=1"
#    data <- read.xls(link, sheet = "Data")
#    legend <- read.xls(link, sheet ="Legend")
#    data <- data[legend$Variable]
#    data <- data[,order(names(data))]
#    units <- c("µmol m^-2 s^-1","% of ECEC","nmol g^-1 s^-1","mm m^-1","kg dm^-3","g  kg^-1","cmol+ kg^-1",
#               "cmolc kg^-1",NA,"%wt","gC gN^-1",NA,"gC kg^-1",NA,NA,"cm","m",NA,NA,NA,NA,"%wt","mmol m^-2 s^-1",
#               NA,NA,NA,NA,"mm mm^-1","mm mm^-1","gN m^-2","%","gN kg^-1",NA,"W m^-2","gP m^-2","mgP2O5 kg^-1",
#               "mm month^-1","mm month^-1",NA,"%","mm","mm","mm","mm",NA,"km",NA,NA,NA,"W m-2","%","dS m^-1","%wt",
#               "%","%wt",NA,"cm2 g^-1","% of ECEC",NA,"%","%","%","%",NA,"cmol kg^-1","ºC",NA,"ºC","ºC","ºC","#","ºC")
#    
#    metadata = data[,c("Country","Latitude","Longitude","Cite", "Continent", "Dataset", "Expt_Remark", "Family","Genus","Location", "P.Method","P.retention.class", "P.Source", "Seeding_Sapling","SITECODE")]
#    units <- units[!names(data) %in% c("Genus.spp",names(metadata))]
#    data <- data[,!names(data) %in% names(metadata)]
#    data$Genus.spp <- tolower(gsub(" ","_",data$Genus.spp))
#    data <- .df.melt(data, "Genus.spp",units,metadata)
#    return(data)
#}

.myhrvold.2015 <- function(...){
    data <- read.csv("~/Downloads/Amniote_Database_Aug_2015.csv", as.is=TRUE)
    data <- read.csv(ft_get_si("E096-269","Data_Files/Amniote_Database_Aug_2015.csv", "esa_archives", cache=FALSE))
    for(i in seq_len(ncol(data)))
        data[data[,i]==-999 | data[,i]=="-999",i] <- NA
    metadata <- data[,c("class","order","family","genus","species","subspecies","common_name")]
    species <- ifelse(is.na(data$subspecies), "", data$subspecies)
    data$binomial <- tolower(paste(data$genus, data$species, data$subspecies, sep="_"))
    data <- data[,!names(data) %in% names(metadata)]
    units <- c("days", "#", "#/year", "g", "years", "days", "days", "g", "g", "g", "days", "days", "years","days", "years", "g", "g", "g", "mm", "mm", "g", "cm", "cm", "cm", "cm", "cm", "g", "cm", "days")
    return(.df.melt(data, "binomial", units, metadata))
}

.benesh.2017 <- function(...){
    data <- read.csv(unzip(ft_get_si("10.1002/ecy.1680", 1), "CLC_database_lifehistory.csv"))
    metadata <- data[,c("Parasite.genus", "Parasite.group", "Development.remarks", "Size.reported.as", "Size.remarks", "Author", "Year", "Journal", "Volume", "Pages")]
    data <- data[,!names(data) %in% names(metadata)]
    return(.df.melt(data, "Parasite.species", c(NA, "#", NA, NA, "days", "°C", "mm", "mm", "mm", "mm", "n", NA, NA, NA), metadata))
}

.lu.2016a <- function(...){
    data <- read.csv(unzip(ft_get_si("10.1002/ecy.1600", 2), "GCReW_Allom_General_Data.csv"))
    data$binomial <- data$Spp_Orig
    data$binomial <- gsub("PHAU", "phragmites_australis", data$binomial)
    data$binomial <- gsub("SCAM", "schoenoplectus_americanus", data$binomial)
    data$binomial <- gsub("SPAL", "spartina_alterniflora", data$binomial)
    data$binomial <- gsub("SPCY", "spartina_cynosuroides", data$binomial)
    data$binomial <- gsub("TYAN", "typha_angustifolia", data$binomial)
    data$binomial <- gsub("AMCA", "amaranthus_cannabinus", data$binomial)
    data$binomial <- gsub("ATPA", "atriplex_patula", data$binomial)
    data$binomial <- gsub("KOVI", "kosteletzkya_virginica", data$binomial)
    data$binomial <- gsub("POHY", "polygonum_hydropiper", data$binomial)
    data$binomial <- gsub("SOSE", "solidago_sempervirens", data$binomial)
    data$binomial <- gsub("IVFR", "iva_frutescens", data$binomial)
    data$Width[data$Width==-99] <- NA
    metadata <- data[,c("Species","Spp_Orig","Decile","ID","Year")]
    data <- data[,!names(data) %in% names(metadata)]
    names(data)[1] <- "height"
    return(.df.melt(data, "binomial", c("cm","mm","g"), metadata))
}

.lu.2016b <- function(...){
    data <- read.csv(unzip(ft_get_si("10.1002/ecy.1600", 2), "GCReW_Allom_Other_Data.csv"))
    data$binomial <- data$Species
    data$binomial <- gsub("PHAU", "phragmites_australis", data$binomial)
    data$binomial <- gsub("SCAM", "schoenoplectus_americanus", data$binomial)
    data$binomial <- gsub("SPAL", "spartina_alterniflora", data$binomial)
    data$binomial <- gsub("SPCY", "spartina_cynosuroides", data$binomial)
    data$binomial <- gsub("TYAN", "typha_angustifolia", data$binomial)
    data$binomial <- gsub("AMCA", "amaranthus_cannabinus", data$binomial)
    data$binomial <- gsub("ATPA", "atriplex_patula", data$binomial)
    data$binomial <- gsub("KOVI", "kosteletzkya_virginica", data$binomial)
    data$binomial <- gsub("POHY", "polygonum_hydropiper", data$binomial)
    data$binomial <- gsub("SOSE", "solidago_sempervirens", data$binomial)
    data$binomial <- gsub("IVFR", "iva_frutescens", data$binomial)
    data$Width[data$Width==-99] <- NA
    metadata <- data[,c("Species","ID","Year")]
    data <- data[,!names(data) %in% names(metadata)]
    names(data)[1] <- "height"
    return(.df.melt(data, "binomial", c("cm","mm","g"), metadata))
}

.lu.2016c <- function(...){
    data <- read.csv(unzip(ft_get_si("10.1002/ecy.1600", 2, cache=FALSE), "GCReW_Allom_SCAM_Data.csv"))
    data$binomial <- "schoenoplectus_americanus "
    data$Width[data$Width==-99] <- NA
    metadata <- data[,c("Species","ID","Expt","ExptAge","Year","Community","Chamber","Quadrat","InOut","CO2","N","Treatment")]
    data <- data[,!names(data) %in% names(metadata)]
    names(data)[1] <- "height"
    data$Cut_Stem <- as.logical(data$Cut_Stem)
    return(.df.melt(data, "binomial", c("cm","cm","mm","g","g","g",NA), metadata))
}

.arnold.2016 <- function(...){
  data <- read.xls(ft_get_si("10.5061/dryad.t3d52","Arnold_etal_2016_functecol_dataset.xlsx"),skip=3)
  data <- data[,1:21]
  data$Species <- "t_castaneum"
  metadata <- data[,c(1:6)]
  data <- data[,-c(1:6)]
  units <- c('uL CO2/h', 'counts/h', 'mg',rep('mm',7), 'mm/s', 'mm/s','# layers beetle reached in trial', 'number of frames no movement', 'number of frames before reaching final passage')
  return(.df.melt(data,"Species",units=units, metadata))
}

.pigot.2015 <- function(...){
  data <- read.xls(ft_get_si("10.5061/dryad.fd986","Database%20S1%20Pigot%2c%20Trisos%20and%20Tobias.xls"), sheet=1)
  metadata <- data[,c(1,16:29)]
  data <- data[,-c(1,16:29)]
  units <- c('meters', 'meters', rep('log',7),rep(NA,4))
  return(.df.melt(data,"Binomial",units=units, metadata))
}

.rahman.2013 <- function(...){
  data <- read.xls(ft_get_si("10.5061/dryad.2v68d","Data%20for%20Dryad.xls"))
  data$Species <- "P_reticulata"
  metadata <- data[,c(1:7,11,12,15,16,19,20)]
  data <- data[,-c(1:7,11,12,15,16,19,20)]
  units <- c('log10','log10','log10',NA,'mm^2',NA,'mm^2','log10','um')
  return(.df.melt(data,"Species",units=units, metadata))
}

.visser.2016 <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.fm654","final.csv"))
  data <- data[,2:8]
  metadata <- data[,c(1,2,3,5,7)]
  data <- data[,-c(2,3,5,7)]
  units <- c('cm','cm')
  return(.df.melt(data,"sp",units=units, metadata))
}

.friedman.2014 <- function(...){
  data <- read.xls(ft_get_si("10.5061/dryad.489c7","NILs_rawdata.xls"))
  metadata <- data[,c(1:6,18,19)]
  data <- data[,-c(1:6,18,19)]
  units <- c('days',NA,'mm', 'mm',NA,rep('mm',6))
  data$Species <- 'M_guttatus'
  return(.df.melt(data,"Species",units=units, metadata))
}

.martin.2014 <- function(...){
  data <- read.table(ft_get_si("10.5061/dryad.j4n82","Sexually%20antagonistic%20association%20between%20paternal%20phenotype%20and%20offspring%20viability%20reinforces%20total%20selection%20on%20a%20sexually%20selected%20trait%20-%20id%20data.txt"),sep='\t',header=TRUE)
  metadata <- data[,c(1:3,7:9)]
  data <- data[,-c(1:3,7:9)]
  units <- c('cm','kg','kg')
  data$Species <- 'O_canadensis'
  return(.df.melt(data,"Species",units=units, metadata))
}

.carmona.2014 <- function(...){
    data <- read.csv(ft_get_si("10.5061/dryad.53550", "Traits%20per%20species%20and%20quadrat.csv"), sep = ";", as.is=TRUE)
    names.data <- read.csv(ft_get_si("10.5061/dryad.53550", "Species%20key.csv"), sep = ";", as.is=TRUE)
    data$binomial <- names.data[,2][match(data$Species, names.data[,1])]
    metadata <- data[,1:3]
    data <- data[,-1:-3]
    units <- c(NA, rep("cm",10), rep("mm^2",10), rep("mm^2/mg",10))
    data <- .df.melt(data, "binomial", units, metadata)
    data$numeric$variable <- gsub("Height[0-9]*", "height", data$numeric$variable)
    data$numeric$variable <- gsub("LeafArea[0-9]*", "leaf_area", data$numeric$variable)
    data$numeric$variable <- gsub("SLA[0-9]*", "specific_leaf_area", data$numeric$variable)
    return(data)
}

.brown.2015 <- function(...){
    data <- read.xls(ft_get_si("10.5061/dryad.m3d4d/1", "BrownGrahamTraitsData.xlsx"))
    data <- data[,-c(4,16)]
    units <- c(rep(NA,12),"g")
    metadata <- data[,1]
    return(.df.melt(data, "Latin.Name", units, metadata))
}

.gossner.2015 <- function(...){
    data <- read.table(ft_get_si("10.5061/dryad.53ds2", "ArthropodSpeciesTraits.txt"), header = T, sep = '\t')
    units <- c(rep(NA,4),"mm",rep(NA,11))
    metadata <- data[,c(1:3,5,17)]
    return(.df.melt(data, "SpeciesID", units, metadata))
}

.price.2014 <- function(...){
    data <- read.xls(ft_get_si("10.5061/dryad.r3n45", "Price%20et%20al%20Data%20for%20Dryad.xlsx"))
    names(data)[7:18] <- c("growth_form","specific_leaf_area","leaf_mass_area","leaf_life_span","N_content_per_unit_mass","N_content_per_unit_area","P_content_per_unit_mass","P_content_per_unit_area","phototsynthetic_capacity_per_mass","phototsynthetic_capacity_per_area","leaf_size","height") 
    units <- c(rep(NA,6), "mm^2/mg ", "g/m^2", "month", "%", "g/m^2", "%", "g/m^2", "nmol/g s", "micromol/m^2 s", "cm^2", "m")
    metadata <- data[,c(1:2,4:7)]
    data <- data[,!names(data) %in% names(metadata)]
    data$leaf_size <- as.numeric(as.character(data$leaf_size))
    return(.df.melt(data, "genus.species", units, metadata))
}

.augspurger.2016a<-function(...){
  file<-tempfile()
  download.file("http://datadryad.org/bitstream/handle/10255/dryad.128418/Data%20File%201.%20Diaspore%20traits.csv?sequence=1",file)
  data<-read.csv(file, as.is=TRUE)
  units<-c("mg","cm^2","mg/cm^2","cm/s")
  return(.df.melt(data,"Species",units=units))
}

.augspurger.2016b<-function(...){
  file<-tempfile()
  download.file("http://datadryad.org/bitstream/handle/10255/dryad.128420/Data%20File%203.%20Parent%20tree%20information.csv?sequence=1",file)
  data<-read.csv(file)
  metadata<-data[,2]
  data<-data[,-2]
  units<-c("cm","m","m","m^2",NA,"m^2")
  data<-.df.melt(data,"Species",units=units,metadata=metadata)
}

.philipson.2016<-function(...){
  file<-tempfile()
  download.file("http://datadryad.org/bitstream/handle/10255/dryad.109340/EcologyEvolution_IntensivePlotsData_forDryad.txt?sequence=1",file)
  data<-read.delim(file,sep = ",")
  metadata<-data[,c(2,7:12)]
  data<-data[,c(1,3:6)]
  units<-c("%","mm","mm","cm")
  data<-.df.melt(data,"Species",units=units,metadata=metadata)
}

#.abakumova.2016<-function(...){
#  file<-tempfile()
#  download.file("http://datadryad.org/bitstream/handle/10255/dryad.109534/Abakumova_etal_NEWPHY2016_morphology_data.txt?sequence=1",file)
#  data<-read.delim(file)
#  metadata<-data[,c(1,3:9)]
#  data<-data[,-c(1,3:9)]
#  units<-c("cm","cm^2","g","%","cm^2/g","g","g")
#  data<-.df.melt(data,"Focal_species",units=units,metadata=metadata)
#}

.lawson.2015<-function(...){
  file<-tempfile()
  download.file("http://datadryad.org/bitstream/handle/10255/dryad.84713/riparian%20wood%20density%20data.csv?sequence=1",file)
  data<-read.csv(file)
  metadata<-data[,c(1,3,5,7,9)]
  data<-data[,-c(1,3,5,7,9)]
  units<-rep("g/cm^3",3)
  data<-.df.melt(data,"species",units=units,metadata=metadata)
}

#.valido.2011 <- function(...){
#    link = "http://datadryad.org/bitstream/handle/10255/dryad.89498/Dryad_database.xls?sequence=1"
#    data = read.xls(link,sheet="Traits")
#    metadata = data[,c(2:7)]
#    data = data[,-c(2:7)]
#    vars = c("species","height","cover","leaf_size","LDMC","specific_leaf_area","lchl","lnc","C13","SDMC","WD", "RDMC", "SRL")
#    colnames(data) = vars
#    units = c("m","m^2","cm^2","g g^-1","m^2 Kg^-1", "µg g^-1", "%","%","g g^-1","g/cm^3","g g^-1","m g^-1")
#    data$species = tolower(gsub(" ","_", data$species))
#    data = .df.melt(data, "species", units, metadata)
#    return(data)
#}

.jennings.2016a <- function(...){
  link = "http://datadryad.org/bitstream/handle/10255/dryad.112638/spiders.csv?sequence=1"
  data = read.csv(link)
  data$species = rep("sosippus_floridanus", nrow(data))
  vars = c("web_area","web_height","diff_trich","diff_trap","sum_trap", "species")
  units = c("cm^2","cm","#/cm^2","cm^2","cm^2")
  metadata = data[,c(1:7,10)]
  data = data[,-c(1:7,10)]
  colnames(data) = vars
  data = .df.melt(data, "species", units, metadata)
}
  
.lessard.2016 <- function(...){
  data <- read.delim(ft_get_si("10.5061/dryad.t897q", "hummer_traits_Lessard.txt"), sep = " ", row.names = NULL)
  species <- tolower(data[,1])
  data <- data.frame(species, data[,-c(1)])
  units <- c("g", "mm", "°C", "?", "range")
  data <- .df.melt(data, "species", units)
  return(data) 
}

.jennings.2016a <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.m23g6", "spiders.csv"), sep = ",", as.is = TRUE, na.strings = c("","NA"))
  species <- rep(c("sosippus_floridanus"), nrow(data))
  data <- data.frame(species, data)
  metadata <- data[,c(2:6)]
  data <- data[,-c(2:6)]
  units <- c("abundance", "sqrt_abundance", "cm^2", "cm", "abundance", "number_of_trichomes/cm^2", "cm^2","cm^2", NA, NA, "abundance", "condition", "condition")
  data <- .df.melt(data, "species", units, metadata)
  return(data)
}

.jennings.2016b <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.m23g6", "sundews.csv"), sep = ",", as.is = TRUE, na.strings = c("","NA"))
  species <- rep(c("drosera_capillaris"), nrow(data))
  data <- data.frame(species, data)
  metadata <- data[,c(2:6)]
  data <- data[,-c(2:6)]
  units <- c("abundance", "sqrt_abundance", "cm^2", "cm", "abundance", "number_of_trichomes/cm^2", "cm^2","cm^2", NA, NA, "abundance", "condition", "condition")
  data <- .df.melt(data, "species", units, metadata)
  return(data)
}

.jennings.2016c <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.m23g6", "toads.csv"), sep = ",", as.is = TRUE, na.strings = c("","NA"))
  species <- rep(c("anaxyrus_quercicus"), nrow(data))
  data <- data.frame(species, data)
  metadata <- data[,c(2:6)]
  data <- data[,-c(2:6)]
  units <- c("cm^2", "cm", "abundance", "sqrt_abundance", "g",  "proportion_initial_mass(g)", "abundance", "number_of_trichomes/cm^2", "cm^2","cm^2", NA, NA, "abundance", "condition", "condition")
  data <- .df.melt(data, "species", units, metadata)
  return(data)
}

.vanier.2013 <- function(...){
  data <- read.delim(ft_get_si("E094-246", "Mass_volume_data.txt", "esa_archives"), sep = "", as.is = TRUE, na.strings = c("","NA"))
  data$Individual_Species <- tolower(data$Individual_Species)
  data$Species_Groups <- tolower(data$Species_Groups)
  metadata <- data[,c(1:2,4:5)]
  data <- data[,-c(1:2,4:5)]
  units <- c("g", "m^3", "Status", "survivor_status", "life_form_type", "?", NA, NA, "treatmet_group")
  data <- .df.melt(data, "Individual_Species", units, metadata)
  return(data)
}

.castillo.2016 <- function(...){
  data <- read.csv('http://datadryad.org/bitstream/handle/10255/dryad.116802/Castillo%20and%20Delph%20isofemale%20data.csv?sequence=1')
  names(data) <- tolower(names(data))
  data$species <- 'caenorhabditis_remanei'
  units <- c('µm','µm','sec','sec','sec', rep(NA,3))
  return(.df.melt(data, "species", units=units))
}

.nandy.2013 <- function(...){
  data <- read.xls('http://datadryad.org/bitstream/handle/10255/dryad.53849/Nandy%20et%20al.%2013-0268.R2_data.xlsx?sequence=1')
  colnames(data) <- c('selection_regime', 'block', 'total_mass_dry')
  names(data) <- tolower(names(data))
  data$species <- 'drosophila_melanogaster'
  units <- c(NA,'mg',NA)
  return(.df.melt(data, "species", units=units))
}

.comeault.2013 <- function(...){
  data <- read.table('http://datadryad.org/bitstream/handle/10255/dryad.54681/Tcris_FHA_phenotypes.txt?sequence=1',header=TRUE)
  data <- data[,-c(1,4)]
  colnames(data) <- c('sex','phenotype','hue_green_color_chip', 'saturation_green_color_chip', 'brightness_green_color_chip', 'lateral_hue_average', 'lateral_saturation_average', 'lateral_brightness_average', 'midsaggital_hue_average', 'midsaggital_saturation_average', 'midsaggital_brightness_average','body_length','body_width','head_width','proportion_striped')
  data$species <- 'timema_cristinae'
  units <- c(rep(NA,9),rep('cm',4),rep(NA,2))
  return(.df.melt(data, "species", units=units))
}

.fargevieille.2017 <- function(...){
  data <- read.csv('http://datadryad.org/bitstream/handle/10255/dryad.138322/ColorTraitValuesECE3-2822.csv?sequence=1',sep=';')
  data <- data[,-c(3,4)]
  levels(data$pop)<- c('d_muro','e_muro','e_pirio','d_rouviere')
  colnames(data) <- c('year','population','male_blue_brightness','female_blue_brightness','male_blue_hue','female_blue_hue','male_blue_uv_chroma','female_blue_uv_chroma','male_yellow_brightness','female_yellow_brightness','male_yellow_contrast','female_yellow_contrast')
  data$species <- 'cyanistes_caeruleus'
  units <- c(rep(NA,12))
  return(.df.melt(data, "species", units=units))
}

.engemann.2016 <- function(...){
    data <- read.delim(unzip(ft_get_si("10.1002/ecy.1569", 1), "DataS1/GrowthForm_Final.txt"))
    metadata <- data[,c("FAMILY_STD", "CONSENSUS", "ID", "SOURCES")]
    data <- data[,!names(data) %in% names(metadata)]
    data$SPECIES_STD <- tolower(gsub(" ", "_", data$SPECIES_STD))
    return(.df.melt(data, "SPECIES_STD", rep(NA,2), metadata))
}

.pfautsch.2016 <- function(...){
    first <- read.csv(unzip(ft_get_si("10.1890/16-0147.1", 1), "Eucalyptus_vessel_anatomy_800cm.csv"), as.is=TRUE)
    first$measurement_height <- "800cm"
    names(first)[19] <- "diameter_at_breast_height"
    second <- read.csv(unzip(ft_get_si("10.1890/16-0147.1", 1), "Eucalyptus_vessel_anatomy_130cm.csv"), as.is=TRUE)
    second$measurement_height <- "130cm"
    names(second)[19] <- "diameter_at_breast_height"
    data <- rbind(first, second)
    data$vessel_area_per_image <- as.numeric(data$vessel_area_per_image)
    names(data)[5:6] <- c("latitude", "longitude")
    metadata <- data[,c("location","country","state","latitude","longitude","elevation","tree","image","measurement_height")]
    data <- data[,!names(data) %in% names(metadata)]
    units <- c("#", "#", "µm^2", "µm^2", "µm^2", "# cm^-2", "%", "µm", "µm", "cm", "cm", "cm", "g/cm^3", "g/cm^3", "°C", "°C", "mm", "mm", "mm", "mm", "mm", "mm", "?")
    return(.df.melt(data, "species", units, metadata))
}

.hebert.2016 <- function(...){
    data <- read.csv(unzip(ft_get_si("10.1890/15-1275.1",1), "zooplankton_traits.csv"), sep=";", as.is=TRUE, dec=",")
    data$binomial <- tolower(paste(data$Genus, data$Species, sep="_"))
    metadata <- data[,c("Genus","Species","Replicate.number","Group","Ref.tg","Ref.bl","Ref.dm","Ref.C","Ref.N","Ref.P","Ref.NP","Ref.prot","Ref.lip","Ref.resp","Ref.N.ex","Ref.P.ex","Ref.NPex")]
    data <- data[,!names(data) %in% names(metadata)]
    data$Min.lip <- gsub(",",".",gsub(" ", "", data$Min.lip))
    data$Temp.Pex.rt <- gsub(",",".",gsub(" ", "", data$Temp.Pex.rt))
    data$Min.dm <- gsub(",",".",gsub(" ", "", data$Min.dm))
    data$Temp.resp.rt <- gsub(",",".",gsub(" ", "", data$Temp.resp.rt))
    data$Min.Nex.rt.ug.dm <- gsub(",",".",gsub(" ", "", data$Min.Nex.rt.ug.dm))
    data$Temp.Nex.rt <- gsub(",",".",gsub(" ", "", data$Temp.Nex.rt))
    data$P.phosphate.ex.rt.ug.ind <- gsub(",",".",gsub(" ", "", data$P.phosphate.ex.rt.ug.ind))
    data$Min.NP.ex <- gsub(",",".",gsub(" ", "", data$Min.NP.ex))
    units <- c(NA, NA, "mm", "mm", "mm","mg", "mg", "mg", "%", "%", "%", "mg", "%", "%", "%", "mg", "%","%", "%", "mg", ":", ":", ":", "%", "%", "%", "%", "%", "%", "µl O2 ind-1 h-1", "µl O2 mgDM -1 h-1","µl O2 mgDM -1 h-1", "µl O2 mgDM -1 h-1", "°C", "°C", "°C", "µg N-NH4+ ind-1 h-1", "µg N-NH4+ mgDM-1 h-1", "µg N-NH4+ mgDM-1 h-1", "µg N-NH4+ mgDM-1 h-1", "nmol N-NH4+ mg DM-1 h-1", "nmol N-NH4+ ind-1 h-1", "nmol N-NH4+ ind-1 h-1", "nmol N-NH4+ ind-1 h-1", "°C", "°C", "°C", "µg P-PO43- ind-1 h-1", "ug P-PO43- mg DM-1 h-1", "ug P-PO43- mg DM-1 h-1", "ug P-PO43- mg DM-1 h-1", "nmol P-PO43- mg DM-1 h-1", "nmol P-PO43- ind-1 h-1", "nmol P-PO43- ind-1 h-1", "nmol P-PO43- ind-1 h-1", "°C", "°C", "°C", ":", ":", ":")
    return(.df.melt(data, "binomial", units, metadata))
}

#.neuheimer.2016 <- function(...){
#    data <- read.csv(unzip(ft_get_si("10.1890/15-1261.1", 1), "15-1261_Neuheimer_SizeDatabase.csv"), as.is=TRUE)
#    data$binomial <- tolower(paste(data$Genus, data$Species, sep="_"))
#    metadata <- data[,c("Phylum", "Class", "Order", "SubOrder", "Family", "Genus", "Species")]
#    combined <- cbind(data[,c("AdultSize1", "AdultSizeUnit1")])
#    units <- c("AdultSize1", "AdultSizeUnit1", "AdultSizeDescription1", "AdultSizeVariation1", "AdultSizeVariationUnit1", "AdultSizeVariationDescription1", "AdultSize2", "AdultSizeUnit2", "AdultSizeDescription2", "AdultSizeVariation2", "AdultSizeVariationUnit2", "AdultSizeVariationDescription2", "ProgenySize1", "ProgenySizeUnit1", "ProgenySizeDescription1", "ProgenySizeVariation1", "ProgenySizeVariationUnit1", "ProgenySizeVariationDescription1", "ProgenySize2", "ProgenySizeUnit2", "ProgenySizeDescription2", "ProgenySizeVariation2", "ProgenySizeVariationUnit2", "ProgenySizeVariationDescription2", "Reference")
#}

#.ebert.2013 <- function(...){
#    data <- read.delim(ft_get_si("E094-193","dissections%2054_09.txt", "esa_archives"), as.is=TRUE, fileEncoding="latin1")
#    metadata <- data[,c()]
#    data <- data[,!names(data) %in% names(metadata)]    
#}

.kraft.2015a <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.69ph0", "BCI%20data.csv"), sep = ",", as.is = TRUE, na.strings = c("","NA"))
  data$genus_species <- tolower(data$genus_species)
  metadata <- data[,c(2:4)]
  data <- data[,-c(2:4)]
  units <- c(rep("J/m^2",4), "g", "µm", "µm", "abundance", "m", "density", "abundance", NA, NA, NA)
  data <- .df.melt(data, "genus_species", units, metadata)
  return(data)
}

.kraft.2015b <- function(...){
  data <- read.csv(ft_get_si("10.5061/dryad.69ph0", "Kraft_et_al%20data.csv"), sep = ",", as.is = TRUE, na.strings = c("","NA"))
  data <-  data[1:166,-19]
  data$Species <- tolower(gsub(" ", "_", data$Species, ignore.case = TRUE))
  metadata <- data[,c(2:3)]
  data <- data[,-c(2:3)]
  units <- c(rep("mm",3), "mm^3", rep("mm",3), rep("J m^-2",2), "concentration_%equivalence_to_4ptStdCurve_ofgallicacid", "concentration_%equivalence_to_8ptStdCurve_ofcrudequebrachotannin", "abundance", "m", "abundance", "density", NA, NA)
  data <- .df.melt(data, "Species", units, metadata)
  return(data)
}

.bengtsson.2016 <- function(...){
  data <- read.csv(ft_get_si('10.5061/dryad.62054', 'bengtsson_etal_2016_traits.csv'), as.is=TRUE)
  data$species.name <- tolower(data$species.name)
  metadata <- data[,c(1:4,6:10)]
  data <- data[,-c(1:4,6:10)]
  units <- c(NA, rep("%",4), "g", "g/cm^2", "g", "g/cm^2", "g", "g/cm^2", "mm", "mm", "cm^-2", "mg/cm^3", "mm", "cm^-2", "mg/cm^3", "mg cm-^2 h^-1", "mg g^-1 h^-1", "mg h^-1", "%", "%", "C/N", "cm^-2", "mg/cm^3", "mm", NA, NA, "latitude", "longitude", NA, NA, NA, NA, NA)
  data <- .df.melt(data, "species.name", units, metadata)
  return(data)
}

#WILL THERE IS AN UPLOADING ERROR THAT SAYS: EOF within quoted string.  I THINK IT IS AN ISSUE WITH THE QUOTES IN LAT AND LON BUT I DO NOT KNOW HOW TO FIX IT.
#PUT IT IN HERE BECAUSE EVERYTHING ELSE IS READY TO GO WITH IT, JUST CAN'T FIGURE OUT HOW TO FIX THE UPLOAD.
#.perez.2014 <- function(...){
#  data <- read.xls(ft_get_si('10.5061/dryad.d61jk/1', 'leaf%20traits%2c%20foliar%20freezing%20resistance%2c%20climatic%20niche.xlsx'), as.is=TRUE, sheet=1)
#  data$Species <- tolower(gsub(" ", "_", data$Species, ignore.case = TRUE))
#  metadata <- data[,c(2:4)]
#  data <- data[,-c(2:4)]
#  units <- c("cm^2", "gr/m^2", rep("N/mm^2",2), NA, "latitude", "longitude")
#  data <- .df.melt(data, "Species", units, metadata)
#  return(data)
#}

#similar issue for this as above.  I think it is the quotes in lat and long
.delaRiva.2015 <- function(...){
  data <- read.xls(ft_get_si('10.5061/dryad.dr275.2', 'Dryad_database.xls'), as.is=TRUE, sheet='Traits')  
  data$Species <- tolower(gsub(" ", "_", data$Species, ignore.case = TRUE))
  metadata <- data[,c(2:7)]
  data <- data[,-c(2:7)]
  units <- c("m", "m^2", "cm^2", "g^-1", "m^2 Kg^-1", "μg g^-1", "%", "%", "g^-1", "g/cm^3", "g g^-1", "m g^-1", rep(NA, 4), "Latitude", "Longitude")
  data <- .df.melt(data, "Species", units, metadata)
  return(data)
}

## Max's Functions ##

.enriquezUrzelai.2015 <- function(...){
  data <- read.csv(url("http://datadryad.org/bitstream/handle/10255/dryad.80306/WM_anurans_traits.csv?sequence=1"), as.is=T)
  data <- subset(data, select=-c(SP,COLLECTION_N,ENTRANCE_N, COLLECTION, T.F))
  data$LOC <- as.factor(data$LOC)
  colnames(data) <- c("species","locomotor_mode","snout_vent_length","tibiofibula_length","femur_length")
  units <- c(NA,"mm","mm","mm")
  data$species <- tolower(gsub(" ", "_", (data$species)))
  data <- .df.melt(data, "species", units=units)
  return(data)
}


.kamilar.2015 <- function(...){
    # http://datadryad.org/resource/doi:10.5061/dryad.pb74r
    data <- read.xls("http://datadryad.org/bitstream/handle/10255/dryad.94095/Kamilar%26Tecot-AppendixS1.xlsx?sequence=1", skip=1, method="csv", header=FALSE, stringsAsFactors=FALSE)
    # Species Order BodyMass(g) BrainMass(g)  AntLobeVol(mm3) PitVol(mm3) PostLobeVol(mm3)  FetalGrowthRate(g/d)  PostnatalGrowthRate(g/d)  Gestation(d)  NeonateBodyMass(g)  LitterSize  WeaningAge(d) WeaningBodyMass(g)  MaxLongevity(y)
    colnames(data) <- c("species","order","body_mass","brain_mass","anterior_lobe_volume","pituitary_volume","posterior_lobe_volume","fetal_growth_rate","postnatal_growth_rate","gestation_length","neonate_body_mass","litter_size","weaning_age","weaning_body_mass","max_longevity")
    meta <- data[,"order"]
    data <- subset(data, select=-c(order))
    units <- c("g","g","mm^3","mm^3","mm^3","g/day","g/day","day","g","individuals","day","g","years")
    data$species <- tolower(gsub(" ", "_", (data$species)))
    data <- .df.melt(data, "species", units=units, metadata=meta)
    return(data)
}

.kissling.2014 <- function(...){
  data <- read.delim(url("http://datadryad.org/bitstream/handle/10255/dryad.64565/MammalDIET_v1.0.txt?sequence=1"), as.is=T)
  data$species <- tolower(paste(data$Genus,data$Species,sep="_"))
  # Subsetting to only include non-interpolated data (estimates generated from taxonomy higher than species)
  data <- data[data$FillCode=="0",]
  meta <- subset(data, select=c(Order,Family,Genus,TaxonomicNote,DataSource))
  data <- subset(data, select=-c(TaxonID,Order,Family,Genus,Species,TaxonomicNote,FillCode,DataSource))
  data <- unique(data[which(!is.na(data$species)),])
  units <- rep(NA,ncol(data)-1)
  data <- .df.melt(data, "species", units=units, metadata=meta)
  return(data)
}

.lislevand.2006 <- function(...){
  require(caper)
  data(shorebird)
  data <- shorebird.data
  colnames(data) <- c("species","body_mass_male","body_mass_female","egg_mass","clutch_size","mating_system")
  units <- c("g","g","f",NA,NA)
  data$species <- tolower(gsub(" ", "_", (data$species)))
  data <- .df.melt(data, "species", units=units)
  return(data)
}

.lupold.2013 <- function(...){
  data <- read.delim(url("http://datadryad.org/bitstream/handle/10255/dryad.48489/dataset.txt?sequence=1"), as.is=T)
  data$Species[data$Species=="Aepiceros_melampus"] <- "Aepyceros_melampus"
  data$species <- tolower(gsub(" ","_", data$Species))
  meta <- subset(data, select=c(Order,Family,N,ReferenceEjaculateData,ReferenceBodyMass.TestisMass,RererenceBasalMetabolicRate))
  data <- subset(data, select=-c(Species,Order,Family,N,ReferenceEjaculateData,ReferenceBodyMass.TestisMass,RererenceBasalMetabolicRate, BodyMass_forBMR_.in_g))
  colnames(data)[6:8] <- c("body_mass","CombinedTestesMass","BasalMetabolicRate")
  units <- c(NA, NA, NA, NA, NA, "g","g","mL/h")
  data <- .df.melt(data, "species", units=units, metadata=meta)
  return(data)  
}

.madin.2016 <- function(...){
    # Currently performs aggregation to species means as original data is in long format with no unique identifiers per row
    data <- read.csv(unzip(ft_get_si("10.6084/m9.figshare.2067414",1))[1], stringsAsFactors=TRUE)
    data$species <- tolower(gsub(" ","_", data$specie_name))

    # Aggregation Code from https://coraltraits.org/procedures#reshaping-data-downloads
    my_aggregate_rules <- function(x) {
        if (length(x) > 1) {               # Does a species by trait combination have more than 1 value?
            x <- type.convert(x, as.is=TRUE)
            if (is.character(x)) {
                return(x[1])                   # If values are strings (characters), then return the first value
            } else {
                return(as.character(mean(x)))  # If values are numbers, then return the mean (converted back to numeric)
            }
        } else {
            return(x)                        # If a species by trait combination has 1 value, then just return that value 
        }
    }
    
    i <- sapply(data, is.factor)
    data[i] <- lapply(data[i], as.character)
    
    traits <- subset(data, select=c(species,trait_name,value, standard_unit))
    traits$standard_unit[traits$standard_unit%in%c("cat","dimensionless","text","bin","id","units")] <- NA  
    units <- unique(subset(traits, select=c("trait_name","standard_unit")))
    units <- units[with(units, order(trait_name)),]
    traits_with_multiple_units <- unique(units$trait_name[duplicated(units$trait_name)])
    # Some traits are reported in different units per species.
    # Removing for now - until unit lookup table is available
    # Some of these are important traits (ex. growth rate), so it would be best to keep them in
    traits <- traits[!traits$trait_name%in%traits_with_multiple_units,]
    units <- units$standard_unit[!units$trait_name%in%traits_with_multiple_units]
    data <- dcast(traits, species ~ trait_name, value.var="value", fun.aggregate=my_aggregate_rules, fill="")
    data[data == ""] <- NA
    # dcast is turning numerics into characters
    for(i in seq_len(ncol(data)))
        data[,i] <- type.convert(data[,i], as.is=TRUE)
    data <- .df.melt(data, "species", units=units)
    return(data)
}

.paquette.2015 <- function(...){
  #10.1002/ece3.1456
  data <- read.xls(unzip(ft_get_si("10.1002/ece3.1456", 1))[2], sheet=2, na.strings=c("","NA"),stringsAsFactors=FALSE)
  data <- data[7:nrow(data),2:8]
  colnames(data) <- c("species","occurrence","average_maximum_height","wood_density","seed_mass","shade_tolerance","nitrogen_per_leaf_mass_unit")
  data <- subset(data, select=-c(occurrence))
  units <- c("m","g/cm^3","mg",NA,"%")
  data$species <- tolower(gsub(" ","_", data$species))
  data[2:6] <- lapply(data[2:6], as.numeric)
  allNAs <- apply(data[2:6], 2,is.na)
  data <- data[rowSums(allNAs)<5,]
  data <- .df.melt(data, "species", units=units)
  return(data)
}

.rojas.2013 <- function(...){
  traits.morph <- read.delim(url("http://datadryad.org/bitstream/handle/10255/dryad.48968/morphological_variables.txt?sequence=1"), as.is=T)
  traits.diet <- read.delim(url("http://datadryad.org/bitstream/handle/10255/dryad.48969/ecological_variables.txt?sequence=1"), as.is=T)
  data <- merge(traits.morph,traits.diet, by.x="taxon",by.y="taxon")
  colnames(data)[1:4] <- c("species","n_individuals_sampled","body_mass","cranial_volume")
  meta <- data[,c("n_individuals_sampled")]
  data <- subset(data, select=-c(n_individuals_sampled))
  data$species <- tolower(gsub(" ","_", data$species))
  units <- c("g","mm^3", rep(NA,6))
  data <- .df.melt(data, "species", units=units, metadata=meta)
  return(data)
}

.stephens.2017 <- function(...){  
  data <- read.csv(unzip(ft_get_si("10.1002/ecy.1799", 1))[4], as.is=TRUE)
  colnames(data)[1] <- "species"
  meta <- data$ParasiteTraitsCitation
  data <- subset(data, select=-c(ParasiteTraitsCitation))
  units <- rep(NA,4)
  data$species <- tolower(gsub(" ","_", sanitize_text(data$species)))
  data <- .df.melt(data, "species", units=units, metadata=meta)
  return(data)
}

.lagisz.2013 <- function(...){
  data <- read.csv("http://datadryad.org/bitstream/handle/10255/dryad.44113/Lagisz_DATATABLE.csv?sequence=1", stringsAsFactors=FALSE)
  meta <- subset(data, select=c(Refseq,NCBI_taxID,class,size_sources))
  data <- subset(data, select=-c(ord,Refseq,NCBI_taxID,genus,species,class,log_volume_male, log_volume_female,size_sources))
  names(data)[1] <- "species"
  data$species <- tolower(gsub(" ","_", data$species))
  units <- c(rep(NA,3),rep("mm",4),rep("mm^3",2), rep(NA,16))
  data <- .df.melt(data, "species", units=units, metadata=meta)
  return(data)
}

## end of Max's Functions ##