updates

introduction.md

@@ -1,9 +1,20 @@
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 layout: default
-title: Getting Started
+title: Intro to Data Wrangling
 nav_order: 3
 ---
 
+# Introduction to Data Wrangling
+<iframe height="480" width="853" allowfullscreen frameborder=0 src="https://echo360.ca/media/fb6f9858-7230-46fa-919a-56d7b3ab0915/public?autoplay=false&automute=false"></iframe>
+
+
+## Slides
+<div style="position:relative;padding-top:66.25%;">
+<iframe src="//docs.google.com/viewer?url=https://github.com/scds/data-wrangling/raw/main/assets/docs/DMDS-data-wrangling.pdf?dl=0&hl=en_US&embedded=true" class="gde-frame" style="position:absolute;top:0;left:0;width:100%;height:100%;border:none;" scrolling="no"></iframe>
+</div>
+[Download as a PDF](https://github.com/scds/data-wrangling/raw/main/assets/docs/DMDS-data-wrangling.pdf)
+<br>
+
 <!-- Edit the content below for the workshop in question. Once you're ready to publish, remove the comment characters e.g. "<!--" at the start and end -->
 
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learn-more.md

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 layout: default
 title: Learn More
-nav_order: 4
+nav_order: 5
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-<!-- Edit the content below for the workshop in question. Once you're ready to publish, remove the comment characters e.g. "<!--" at the start and end -->
+## More information
+- The [OpenRefine home page](https://openrefine.org/) has a variety of tutorials and documentation to learn more about using OpenRefine
+- [Register](https://u.mcmaster.ca/dmds-data-wrangling-drop-in) for the post-workshop drop-in session on February 11, 2021.
 
-<!--
-
-## More info and other tools
-
-- Tableau [free training videos](https://www.tableau.com/learn/training/20201)
-- LinkedIn Learning [Tableau training page](https://www.linkedin.com/learning/topics/tableau)
-- Data visualization design considerations for beginners: [Berkeley Library](https://guides.lib.berkeley.edu/data-visualization/design) | [University of Guelph Library](https://guides.lib.uoguelph.ca/c.php?g=700755&p=4976239)
-
--->

openrefine.md

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+---
+layout: default
+title: Data Wrangling with OpenRefine
+nav_order: 4
+---
+
+# Data Wrangling with OpenRefine
+
+After ensuring that you've followed the [Preparatory steps](preparation) to install OpenRefine, navigate to the Data Carpentries' [Open Refine for Social Science Data](https://datacarpentry.org/openrefine-socialsci/) workshop page and follow along with the hands-on tutorial. 
+
+***And note*** that though the workshop uses Social Sciences data, the approaches used in this workshop are applicable in many other disciplines.