Changed book style and started adding shell per outline #6
Conversation
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@laderast I tried to add you as a reviewer to this too, but I seem to be missing how to do that. |
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No spelling errors! 🎉 |
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Re-rendered previews from the latest commit:
* note not all html features will be properly displayed in the "quick preview" but it will give you a rough idea. Updated at 2024-11-06 with changes from the latest commit 4d1b927 |
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Looks great! The only thing I might change is shifting the "What are the parts of a data visualization?" Chapter to more of an emphasis on how to know what type of plot to use. Also if the chapter titles are shorter it makes it easier for learners to navigate the table of contents (as they don't get cut off) , so you might want to consider changing them to be shorter. |
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Maybe work on learning objectives next |
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Might also be good to talk about distortions that can happen |
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| ## What is Data Visualization? | ||
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| ### Exploratory Data Analysis (EDA) |
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I do like the exploratory vs explanatory dichotomy for explaining the aims of visualization: https://laderast.github.io/data_storytelling_bdc/#5
| - {LO1} | ||
| - {LO2} | ||
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| ## Visual Design Principles |
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Can be helpful to talk about preattentive attributes and how they're used in viz design: https://laderast.github.io/data_storytelling_bdc/#22
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| ## Data types | ||
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| ## Graph types |
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Per @carriewright11 's suggestion, I like showing a decision tree like this to help people decide on visualizations: https://www.data-to-viz.com/
Probably need to also expand to include cancer informatics-specific visualizations, including genomics/volcano plots, etc
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Thank you both, @carriewright11 and @laderast -- these are very helpful! |
index.Rmd
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| ## Available course formats | ||
| This course is part of a series of courses for the [Informatics Technology for Cancer Research (ITCR)](https://itcr.cancer.gov/) called the Informatics Technology for Cancer Research Education Resource. This material was created by the ITCR Training Network (ITN) which is a collaborative effort of researchers around the United States to support cancer informatics and data science training through resources, technology, and events. This initiative is funded by the following grant: [National Cancer Institute (NCI)](https://www.cancer.gov/) UE5 CA254170. Our courses feature tools developed by ITCR Investigators and make it easier for principal investigators, scientists, and analysts to integrate cancer informatics into their workflows. Please see our website at [www.itcrtraining.org](www.itcrtraining.org) for more information. |
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| This course is part of a series of courses for the [Informatics Technology for Cancer Research (ITCR)](https://itcr.cancer.gov/) called the Informatics Technology for Cancer Research Education Resource. This material was created by the ITCR Training Network (ITN) which is a collaborative effort of researchers around the United States to support cancer informatics and data science training through resources, technology, and events. This initiative is funded by the following grant: [National Cancer Institute (NCI)](https://www.cancer.gov/) UE5 CA254170. Our courses feature tools developed by ITCR Investigators and make it easier for principal investigators, scientists, and analysts to integrate cancer informatics into their workflows. Please see our website at [www.itcrtraining.org](www.itcrtraining.org) for more information. | |
| This course is part of a series of courses for the [Informatics Technology for Cancer Research (ITCR)](https://www.cancer.gov/about-nci/organization/cssi/research/itcr). This material was created by the ITCR Training Network (ITN) which is a collaborative effort of researchers around the United States to support cancer informatics and data science training through resources, technology, and events. This initiative is funded by the following grant: [National Cancer Institute (NCI)](https://www.cancer.gov/) UE5 CA254170. Our courses feature tools developed by ITCR Investigators and make it easier for principal investigators, scientists, and analysts to integrate cancer informatics into their workflows. Please see our website at [www.itcrtraining.org](www.itcrtraining.org) for more information. |
index.Rmd
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| - This course can be taken for [free certification through Leanpub](LINK HERE). | ||
| - This course can be taken on [Coursera for certification here](LINK HERE) (but it is not available for free on Coursera). | ||
| - Our courses are open source, you can find the [source material for this course on GitHub](LINK HERE). | ||
| The second course in the series will focus on building data visualizations, pointing to resources across R and Python, while integrating the best practice considerations discussed in this course. |
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could add major objectives to the other course here
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Looks good! |
This PR begins by filling out the shell of this repo for Part 1 of the Data Visualization Course (Data Visualizations Considerations) by
making style changes per the guide on ottrproject.org
creating
.Rmdchapters with headings based on the developed outlinemaking some quick edits to the
READMEand._bookdown.ymlfilesNext steps will include filling out learning objectives and the names/motivation/goal sections of the
index.Rmdand01-intro.Rmdfiles.Looking for feedback on layout and content of the shell -- e.g., is there anything that doesn't seem to be there that should be? Do we like the addition of EDA in the what is data visualization chapter (contrasting EDA vs more polished visualizations)?