The jamesdemodata package is a lightweight repository containing
demonstration data and example child records. Its goal is to provide
reproducible examples and test cases for the Joint Automatic
Measurement and Evaluation System (JAMES) — an online service that
supports real-time decision making in the monitoring and prediction of
child growth and development.
To install the jamesdemodata package from GitHub, use:
install.packages("remotes")
remotes::install_github("growthcharts/jamesdemodata")The example datasets build upon the the BDS JGZ
specification
and NICTIZ informatiestandaarden
JGZ These
specifications provide a detailed description on what information can be
collected and how it should stored. The bdsreader package implements a
subset of BDS JGZ fields related to child growth and development into a
JSON schema that can be used for validation and electronic data
communication. The current version of this JSON schema is
bds_v3.0.
The examples in the jamesdemodata package are coded according to this
JSON schema, or a previous version of it.
The json/examples directory contains a few minimal JSON datasets for
testing and development.
Use the system.file() function to construct the path to a file within
the package:
fn <- system.file("json", "examples", "maria.json", package = "jamesdemodata")
cat(paste(readLines(fn, n = 10), collapse = "\n"), "\n...")## {
## "Format": "3.0",
## "organisationCode": 1234,
## "reference": "Maria",
## "clientDetails": [
## {
## "bdsNumber": 19,
## "value": "2"
## },
## {
## ...
If you have the bdsreader package installed, you can read and inspect
the JSON data as follows:
library(bdsreader)
read_bds(fn)## <bdsreader>
## $psn:
## id name src dnr sex gad ga smo bw hgtm hgtf agem blbf blbm eduf edum
## 1 -1 Maria 1234 <NA> female 189 27 1 990 167 190 NA NA NA NA NA
## par
## 1 NA
##
## $xyz:
## # A tibble: 13 × 8
## age xname yname zname zref x y z
## <dbl> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl>
## 1 0.0849 age hgt hgt_z nl_2012_hgt_female_27 0.0849 38 -0.158
## 2 0.167 age hgt hgt_z nl_2012_hgt_female_27 0.167 43.5 0.047
## 3 0 age wgt wgt_z nl_2012_wgt_female_27 0 0.99 0.19
## 4 0.0849 age wgt wgt_z nl_2012_wgt_female_27 0.0849 1.25 -0.203
## 5 0.167 age wgt wgt_z nl_2012_wgt_female_27 0.167 2.1 0.015
## 6 0.0849 age hdc hdc_z nl_2012_hdc_female_27 0.0849 27 -0.709
## 7 0.167 age hdc hdc_z nl_2012_hdc_female_27 0.167 30.5 -0.913
## 8 0 age bmi bmi_z nl_1997_bmi_female_nl 0 NA NA
## 9 0.0849 age bmi bmi_z nl_1997_bmi_female_nl 0.0849 8.66 -5.72
## 10 0.167 age bmi bmi_z nl_1997_bmi_female_nl 0.167 11.1 -3.77
## 11 0 hgt wfh wfh_z nl_2012_wfh_female_ NA 0.99 NA
## 12 0.0849 hgt wfh wfh_z nl_2012_wfh_female_ 38 1.25 -0.001
## 13 0.167 hgt wfh wfh_z nl_2012_wfh_female_ 43.5 2.1 0.326
For installation instructions and further documentation, see the
bdsreader GitHub
repository.
To explore what is available in json/examples use
json_path <- system.file("json", "examples", package = "jamesdemodata")
list.files(json_path, recursive = TRUE)## [1] "client3.json" "Kevin_S.json" "Laura_S.json"
## [4] "maria-mangled.json" "maria.json" "maria1.json"
## [7] "maria2.json" "test.json"
The following table lists the files in the json/examples directory,
along with a brief description of each file.
| File | Description |
|---|---|
client3.json |
Example child record in minimal JSON format |
Kevin_S.json |
Preterm child Kevin_S using current JSON schema |
Laura_S.json |
Example child Laura_S using current JSON schema |
maria-mangled.json |
Same child with vastly incomplete data, for debugging |
maria.json |
Example child record in minimal JSON format |
maria1.json |
Example child record, JSON schema 1.0 (outdated) |
maria2.json |
Example child record, JSON schema 2.0 (outdated) |
test.json |
Example child record in minimal JSON format |
The extdata directory includes more comprehensive child records coded
according to various versions of the BDS specification. These files are
used by the JAMES demo
app.
For example, to see the first 10 lines of the Laura_S.json file, use:
fn <- system.file("extdata", "bds_v3.0", "smocc", "Laura_S.json", package = "jamesdemodata")
cat(paste(readLines(fn, n = 10), collapse = "\n"), "\n...")## {
## "Format": "3.0",
## "organisationCode": 0,
## "reference": "Laura S",
## "clientDetails": [
## {
## "bdsNumber": 19,
## "value": "2"
## },
## {
## ...
The interesting parts of extdata are the example files using
bds_v3.0 schema:
extdata <- system.file("extdata", package = "jamesdemodata")
dirs <- list.dirs(extdata, full.names = FALSE, recursive = TRUE)
dirs[grepl("^bds_v3\\.0", dirs)]## [1] "bds_v3.0" "bds_v3.0/graham" "bds_v3.0/lollypop"
## [4] "bds_v3.0/pops" "bds_v3.0/smocc" "bds_v3.0/terneuzen"
## [7] "bds_v3.0/test"
Each subdirectory contains 10 children. For example, let us explore the
files in bds_v3.0/smocc:
smocc <- system.file("extdata", "bds_v3.0", "smocc", package = "jamesdemodata")
list.files(smocc, recursive = TRUE)## [1] "Anne_S.json" "Iris_S.json" "Jeroen_S.json" "Kevin_S.json"
## [5] "Laura_S.json" "Linda_S.json" "Mark_S.json" "Rick_S.json"
## [9] "Thomas_S.json" "Tim_S.json"
See the first few lines of the Anne_S.json file:
fn <- file.path(smocc, "Anne_S.json")
cat(paste(readLines(fn, n = 10), collapse = "\n"), "\n...")## {
## "Format": "3.0",
## "organisationCode": 0,
## "reference": "Anne S",
## "clientDetails": [
## {
## "bdsNumber": 19,
## "value": "2"
## },
## {
## ...
As before, we can read read and inspect the JSON data using the
bdsreader package:
read_bds(fn)## <bdsreader>
## $psn:
## id name src dnr sex gad ga smo bw hgtm hgtf agem blbf blbm eduf edum
## 1 -1 Anne S 0 <NA> female 283 40 0 3300 172 183 NA NA NA NA NA
## par
## 1 NA
##
## $xyz:
## # A tibble: 58 × 8
## age xname yname zname zref x y z
## <dbl> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl>
## 1 0 age hgt hgt_z nl_1997_hgt_female_nl 0 51 0.052
## 2 0.0986 age hgt hgt_z nl_1997_hgt_female_nl 0.0986 54.7 0.145
## 3 0.137 age hgt hgt_z nl_1997_hgt_female_nl 0.137 56 0.114
## 4 0.233 age hgt hgt_z nl_1997_hgt_female_nl 0.233 59.5 0.206
## 5 0.501 age hgt hgt_z nl_1997_hgt_female_nl 0.501 68 0.661
## 6 0.788 age hgt hgt_z nl_1997_hgt_female_nl 0.788 73 0.498
## 7 0.961 age hgt hgt_z nl_1997_hgt_female_nl 0.961 75.5 0.375
## 8 1.25 age hgt hgt_z nl_1997_hgt_female_nl 1.25 80 0.434
## 9 1.51 age hgt hgt_z nl_1997_hgt_female_nl 1.51 83.5 0.449
## 10 1.97 age hgt hgt_z nl_1997_hgt_female_nl 1.97 89.5 0.731
## # ℹ 48 more rows