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Edouard-Legoupil · Nov 2, 2023 · 1150e11 · 1150e11
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -61,7 +61,8 @@ Remotes:
     edouard-legoupil/riddle,
     edouard-legoupil/unhcrshiny,
     unhcr-americas/XlsFormUtil,
-    vidonne/unhcrdown
+    unhcr-dataviz/unhcrdown,
+    unhcr-dataviz/unhcrthemes
 Config/fusen/version: 0.5.2
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)

diff --git a/README.md b/README.md
@@ -1,5 +1,10 @@
 # {kobocruncher}
 
+<!-- badges: start -->
+[![:name status badge](https://unhcrverse.r-universe.dev/badges/:name)](https://unhcrverse.r-universe.dev/)
+[![IndicatorCalc status badge](https://unhcrverse.r-universe.dev/badges/HighFrequencyChecks)](https://unhcrverse.r-universe.dev/HighFrequencyChecks)
+<!-- badges: end -->
+
 An organized workflow generating 'Rmd' files from an extended 'xlsform' questionnaire structure to facilitate survey data crunching.  
 
 `{kobocruncher}` support organised data analysis workflow, to conduct data discovery and analysis for data collected through  [KoboToolbox](https://www.kobotoolbox.org/), [ODK](https://opendatakit.org/), [ONA](https://ona.io/home/) or any __[xlsform](http://xlsform.org)__ compliant data collection platform.
@@ -57,7 +62,9 @@ The easiest way to do that is by calling `usethis::edit_r_environ()` and adding
 
 Contributions to the packages are welcome. Please read first the [contribution guidelines](CONTRIBUTING.html), follow the [code of conduct](CODE_OF_CONDUCT.html) and use the [issue template](ISSUE_TEMPLATE.html).
 
-## References and rational for the package
+## References  
+
+ *  JIPS Essential Toolkit, "How do we process and prepare data for analysis":  https://jet.jips.org/wp-content/uploads/Guidance-Data-Processing-Phase5-JET.pdf
 
 The package falls into the category of Automatic Data Exploration package (see an [extensive review here](https://github.com/mstaniak/autoEDA-resources)) and mostly act as a __wrapper__ for different specialized packages from the [tidyverse](https://www.tidyverse.org/) . 
 
@@ -71,4 +78,4 @@ Compare to those packages, `{kobocruncher}` provides:
 
  * Relabeling functions and Questions grouping ability
 
- * Full integration with UNHCR Brand Style
+ * Full integration with [UNHCR Brand Style](https://dataviz.unhcr.org/tools/r/)
diff --git a/...s/crunching-function-for-xlsform_files/figure-html/examples-kobo_cruncher-3.png b/...s/crunching-function-for-xlsform_files/figure-html/examples-kobo_cruncher-3.png
diff --git a/...icles/crunching-function-for-xlsform_files/figure-html/examples-plot_text-1.png b/...icles/crunching-function-for-xlsform_files/figure-html/examples-plot_text-1.png
diff --git a/docs/index.html b/docs/index.html
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
@@ -4,5 +4,5 @@ pkgdown_sha: ~
 articles:
   Troubleshooting: Troubleshooting.html
   crunching-function-for-xlsform: crunching-function-for-xlsform.html
-last_built: 2023-11-02T17:39Z
+last_built: 2023-11-02T18:47Z
 
diff --git a/docs/reference/kobo_cruncher-3.png b/docs/reference/kobo_cruncher-3.png
diff --git a/docs/reference/plot_text-1.png b/docs/reference/plot_text-1.png
diff --git a/docs/search.json b/docs/search.json
diff --git a/docs/tutorial/00-Intro.Rmd b/docs/tutorial/00-Intro.Rmd
@@ -1,5 +1,5 @@
 ---
-title: "Survey Data Analysis with Kobocruncher"
+title: "Survey Data Analysis with {Kobocruncher}"
 subtitle: "Session 0 - Introduction"
 author: "[Link to Documentation](https://edouard-legoupil.github.io/kobocruncher/) -- [Link to Next Session](01-First_Report.html)  "
 date: "Training Content as of `r format(Sys.Date(),  '%d %B %Y')`"
@@ -39,19 +39,17 @@ Based on a questionnaires, __standardized indicators are calculated__ with a vie
 
 ## Survey Data, aka micro-data have secificities
 
-The raw data need to go through a number of __technical manipulations__ before one can use them for interpretation:
+[Clean and anonymized data](https://edouard-legoupil.github.io/HighFrequencyChecks/tutorial/index.html) need to go through a number of __technical manipulations__ before one can use them for interpretation:
 
- * _relabeling_ the original question wording to make them quickly legible when doing the interpretation
-
- * perform some data _cleaning_ to account for any issues on the raw data
-
- * apply some basic data _anonymization_ treatment techniques to manage statistical disclosure and re-identification risks
+ * Need to __relabel__ the original question wording to make them quickly legible when doing the interpretation
+
+ * Need to __regroup__ and  __crosstabulate__  questions
 
- * create intermediary indicator _calculations_
+ * create intermediary indicator __calculations__
 
- * use specific survey _weights_ to correctly express the representativeness of each records in the raw data in relation with the original sampling universe  
+ * use specific survey __weights__ to correctly express the representativeness of each records in the raw data in relation with the original sampling universe  
 
- * translate the data into _visual charts_ than be easily consumed (understood and intepretated) by subject matter experts 
+ * translate the data into __visual charts__ than be easily consumed (understood and interpreted) by subject matter experts 
 
 
 ---

diff --git a/docs/tutorial/00-Intro.html b/docs/tutorial/00-Intro.html
diff --git a/docs/tutorial/01-First_Report.Rmd b/docs/tutorial/01-First_Report.Rmd
@@ -1,5 +1,5 @@
 ---
-title: "Survey Data Analysis with Kobocruncher"
+title: "Survey Data Analysis with {Kobocruncher}"
 subtitle: "Session 1 - Your first report"
 author: "[Link to Documentation](https://edouard-legoupil.github.io/kobocruncher/) -- [Link to Previous Session](00-Intro.html) -- [Link to Next Session](02-Relabeling.html)  "
 date: "Training Content as of `r format(Sys.Date(),  '%d %B %Y')`"