/EMLuse

How to use Ecological Metadata Language (EML)

Test using the EML package

First create an attribute metadatra

Create a table with the column names (attributeName) of a csv file (or similar) and fill in some other columns, the following table is an example

library(EML)

attributes <-tibble::tribble(
~attributeName, ~attributeDefinition,                                                 ~formatString, ~definition,        ~unit,   ~numberType,
  "run.num",    "which run number (=block). Range: 1 - 6. (integer)",                 NA,            "which run number", NA,       NA,
  "year",       "year, 2012",                                                         "YYYY",        NA,                 NA,       NA,
  "day",        "Julian day. Range: 170 - 209.",                                      "DDD",         NA,                 NA,       NA,
  "hour.min",   "hour and minute of observation. Range 1 - 2400 (integer)",           "hhmm",        NA,                 NA,       NA,
  "i.flag",     "is variable Real, Interpolated or Bad (character/factor)",           NA,            NA,                 NA,       NA,
  "variable",   "what variable being measured in what treatment (character/factor).", NA,            NA,                 NA,       NA,
  "value.i",    "value of measured variable for run.num on year/day/hour.min.",       NA,            NA,                 NA,       NA,
  "length",    "length of the species in meters (dummy example of numeric data)",     NA,            NA,                 "meter",  "real")
attributeName attributeDefinition formatString definition unit numberType
run.num which run number (=block). Range: 1 - 6. (integer) NA which run number NA NA
year year, 2012 YYYY NA NA NA
day Julian day. Range: 170 - 209. DDD NA NA NA
hour.min hour and minute of observation. Range 1 - 2400 (integer) hhmm NA NA NA
i.flag is variable Real, Interpolated or Bad (character/factor) NA NA NA NA
variable what variable being measured in what treatment (character/factor). NA NA NA NA
value.i value of measured variable for run.num on year/day/hour.min. NA NA NA NA
length length of the species in meters (dummy example of numeric data) NA NA meter real

then generate a key for factors

i.flag <- c(R = "real",
            I = "interpolated",
            B = "bad")
variable <- c(
    control  = "no prey added",
    low      = "0.125 mg prey added ml-1 d-1",
    med.low  = "0,25 mg prey added ml-1 d-1",
    med.high = "0.5 mg prey added ml-1 d-1",
    high     = "1.0 mg prey added ml-1 d-1",
    air.temp = "air temperature measured just above all plants (1 thermocouple)",
    water.temp = "water temperature measured within each pitcher",
    par       = "photosynthetic active radiation (PAR) measured just above all plants (1 sensor)"
)

value.i <- c(
    control  = "% dissolved oxygen",
    low      = "% dissolved oxygen",
    med.low  = "% dissolved oxygen",
    med.high = "% dissolved oxygen",
    high     = "% dissolved oxygen",
    air.temp = "degrees C",
    water.temp = "degrees C",
    par      = "micromoles m-1 s-1"
)

## Write these into the data.frame format
factors <- rbind(
    data.frame(
        attributeName = "i.flag",
        code = names(i.flag),
        definition = unname(i.flag)
    ),
    data.frame(
        attributeName = "variable",
        code = names(variable),
        definition = unname(variable)
    ),
    data.frame(
        attributeName = "value.i",
        code = names(value.i),
        definition = unname(value.i)
    )
)

which generates the following table

attributeName code definition
i.flag R real
i.flag I interpolated
i.flag B bad
variable control no prey added
variable low 0.125 mg prey added ml-1 d-1
variable med.low 0,25 mg prey added ml-1 d-1
variable med.high 0.5 mg prey added ml-1 d-1
variable high 1.0 mg prey added ml-1 d-1
variable air.temp air temperature measured just above all plants (1 thermocouple)
variable water.temp water temperature measured within each pitcher
variable par photosynthetic active radiation (PAR) measured just above all plants (1 sensor)
value.i control % dissolved oxygen
value.i low % dissolved oxygen
value.i med.low % dissolved oxygen
value.i med.high % dissolved oxygen
value.i high % dissolved oxygen
value.i air.temp degrees C
value.i water.temp degrees C
value.i par micromoles m-1 s-1

we then generate an attributeList

attributeList <- set_attributes(attributes, 
                                factors, 
                                col_classes = c("character", "Date", "Date", "Date", "factor", "factor", "factor", "numeric"))

We link this to the csv file

physical <- set_physical("hf205-01-TPexp1.csv")

And Assemble the dataTable

dataTable <- list(
                 entityName = "hf205-01-TPexp1.csv",
                 entityDescription = "tipping point experiment 1",
                 physical = physical,
                 attributeList = attributeList)

Now lets set the time and geographic coverage

geographicDescription <- "Harvard Forest Greenhouse, Tom Swamp Tract (Harvard Forest)"


coverage <- 
  set_coverage(begin = '2012-06-01', end = '2013-12-31',
               sci_names = "Sarracenia purpurea",
               geographicDescription = geographicDescription,
               west = -122.44, east = -117.15, 
               north = 37.38, south = 30.00,
               altitudeMin = 160, altitudeMaximum = 330,
               altitudeUnits = "meter")

and a list of authors

The main author

R_person <- person(given = "Aaron", 
                   family = "Ellison", 
                   email = "fakeaddress@email.com", 
                   role = "cre", 
                  comment = c(ORCID = "0000-0003-4151-6081"))
aaron <- as_emld(R_person)

and some collaborators

Want to learn more about EML?

External resources