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diff --git a/11_data_sources.rmd b/11_data_sources.rmd
@@ -7,6 +7,7 @@
 
 What is data science without _data_?  Here's a few indexes and compendiums of data sources, including R packages that conveniently either bundle those data or provide mechanisms to access data from remote sources.
 
+* Kim, A. Y, Ismay, C., & Chunn, J. (2018). The fivethirtyeight R Package: "Tame Data" Principles for Introductory Statistics and Data Science Courses. _Technology Innovations in Statistics Education_, 11(1). Retrieved from https://escholarship.org/uc/item/0rx1231m
 
 
 ## Sources
@@ -36,13 +37,18 @@ Simon Fraser University Library: [Gender, Sexuality & Women's Studies Informatio
 ## R packages
 
 
-### **cancensus**
+### {bcdata}
+
+[bcdata](https://bcgov.github.io/bcdata/) -- An R package 📦 for searching & retrieving data from the B.C. Data Catalogue.
+
+
+### {cancensus}
 
 [Census of Canada (including the National Household Survey)](https://github.com/mountainMath/cancensus)
 
 
 
-### **cansim**
+### {cansim}
 
 **package**
 
@@ -53,7 +59,7 @@ Simon Fraser University Library: [Gender, Sexuality & Women's Studies Informatio
 Dmitry Shkolnik (2018-08-01) [The CANSIM package, Canadian tourism, and slopegraphs](https://www.dshkol.com/2018/cansim-package-tourism-slopegraphs/)
 
 
-### **CANSIM2R**
+### {CANSIM2R}
 
 [CANSIM2R: Directly Extracts Complete CANSIM Data Tables](https://cran.r-project.org/package=CANSIM2R)
 
@@ -62,14 +68,21 @@ github: [CANSIM2R](https://github.com/MarcoLugo/CANSIM2R)
 * Andrew Clarke (2017-08-09) [StatCan API's Discovered](https://www.mytinyshinys.com/2017/08/09/statcanapi/)
 
 
-### **gapminder**
+### {fivethirtyeight}
+
+[fivethirtyeight](https://fivethirtyeight-r.netlify.com/articles/fivethirtyeight.html)
+
+
+### {gapminder}
 
 [gapminder: Data from Gapminder](https://cran.r-project.org/package=gapminder) An excerpt of the data available at [Gapminder.org]. For each of 142 countries, the package provides values for life expectancy, GDP per capita, and population, every five years, from 1952 to 2007. 
 
 
-### **Lahman**
+### {Lahman}
 
 [Lahman: Sean 'Lahman' Baseball Database](https://cran.r-project.org/package=Lahman/)  Provides the tables from the 'Sean Lahman Baseball Database' as a set of R data.frames. It uses the data on pitching, hitting and fielding performance and other tables from 1871 through 2015, as recorded in the 2016 version of the database.
 
 
 
+
+
diff --git a/20_data_wrangling.Rmd b/20_data_wrangling.Rmd
@@ -1,5 +1,7 @@
 # Data Wrangling (emphasis on tidy data) {#datawrangling}
 
+> If 80% of the data scientist's job is data cleaning, perhaps that _is_ the job. (Source: Anon.)
+
 
 ## Introduction
 

diff --git a/60_spatial_data.Rmd b/60_spatial_data.Rmd
@@ -98,6 +98,8 @@ Jacinta Holloway, [raster2data](https://github.com/thejholloway/raster2data)
 
 * "This repository provides some introductory guidance for working with spatial image files, like rasters, and converting these to dataframes in R in order to perform statistical analyses. Includes an example satellite image and R code."
 
+Arda Kosar, 2018-05-01, [A Beginner’s Exploration of Shiny and Leaflet for Interactive Mapping](https://www.datascience.com/blog/beginners-guide-to-shiny-and-leaflet-for-interactive-mapping)
+
 Robin Lovelace (2014) ["R, an Integrated Statistical Programming Environment and GIS"](http://robinlovelace.net/r/2014/11/28/r-as-a-gis-geoinformatics.html) {blog post}
 
 Robin Lovelace, James Cheshire and others, 2015-, [_Introduction to visualising spatial data in R_](https://cran.r-project.org/doc/contrib/intro-spatial-rl.pdf) {or up-to-date version on github, [Robinlovelace/Creating-maps-in-R](https://github.com/Robinlovelace/Creating-maps-in-R) {tutorial}
@@ -190,7 +192,9 @@ CRAN page: [ggmap: Spatial Visualization with ggplot2]
 
 [Creating a custom soil attribute plot using ggmap](http://blog.revolutionanalytics.com/2015/01/creating-a-custom-soil-attribute-plot-using-ggmap.html)
 
-[ggmap: Spatial Visualization with ggplot2](https://journal.r-project.org/archive/2013-1/kahle-wickham.pdf) by David Kahle and Hadley Wickham, _The R Journal_ Vol. 5/1, June 2013, pp.144-161.
+Laura Ellis, 2018-04-15, [Map Plots Created With R And ggmap](https://www.littlemissdata.com/blog/maps)
+
+David Kahle and Hadley Wickham, [ggmap: Spatial Visualization with ggplot2](https://journal.r-project.org/archive/2013-1/kahle-wickham.pdf) _The R Journal_ Vol. 5/1, June 2013, pp.144-161.
 
 [Plotting Choropleths from Shapefiles in R with ggmap – Toronto Neighbourhoods by Population](http://www.r-bloggers.com/plotting-choropleths-from-shapefiles-in-r-with-ggmap-toronto-neighbourhoods-by-population/)
 
@@ -245,6 +249,8 @@ RStudio on github: [rstudio/leaflet](https://github.com/rstudio/leaflet)
 
 [Leaflet for R](http://rstudio.github.io/leaflet/)
 
+[Using Leaflet with Shiny](https://rstudio.github.io/leaflet/shiny.html)
+
 Robin Lovelace, [The leaflet package for online mapping in R](https://www.r-bloggers.com/the-leaflet-package-for-online-mapping-in-r/)
 
 Kyle Walker (2015) ["Creating a Leaflet choropleth map with a pop-up in R"](https://rpubs.com/walkerke/leaflet_choropleth) (2015-01-30)

diff --git a/data_science_pedagogy.Rmd b/data_science_pedagogy.Rmd
@@ -1,5 +1,11 @@
 # Data science pedagogy
 
+## Introduction
+
+Since it's a relatively new field, it's not surprising that the best way to teach data science is still evolving. Below are some resources for those who are sorting out how to teach this cross-silo discipline.
+
+
+## General
 
 
 Joyce Cahoon, [Things I Wish I Knew Before I Started Teaching](https://jcahoon.netlify.com/post/2019/07/13/things-i-wish-i-knew-before-i-started-teaching/)
@@ -15,19 +21,27 @@ and a reply:
 
 ***
 
-## Lesson planning
+### Lesson planning
 
 https://www.algonquincollege.com/profres/lesson-planning/
 
 https://carleton.ca/edc/teachingresources/course-design/lesson-planning/
 
 
-## Inclusivity 
+### Inclusivity 
 
 https://www.chronicle.com/interactives/20190719_inclusive_teaching
 
 
 
+*** 
+
+## Data sources
+
+Kim, A. Y, Ismay, C., & Chunn, J. (2018). The fivethirtyeight R Package: "Tame Data" Principles for Introductory Statistics and Data Science Courses. _Technology Innovations in Statistics Education_, 11(1). Retrieved from https://escholarship.org/uc/item/0rx1231m
+
+See also [@datasources]
+
 ***
 
 ## Teaching R
@@ -40,6 +54,10 @@ Wisdom from Roger Peng:
 Not So Standard Deviations, [Episode 84 "All the Easy Issues"](http://nssdeviations.com/84-all-the-easy-issues) (discussion starting at ~39:45)
 
 
+### Text books, etc
+
+See [@Statistics and other quantitative methods: courses and text books]
+
 ***
 
 
@@ -140,4 +158,4 @@ replies:
 [ECONOMY, SOCIETY, AND PUBLIC POLICY](https://econw19.classes.andrewheiss.com/) (MPA 612, BYU)
 
 
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