Merge pull request #943 from bressler1995/open-science-101

Address minor consistency differences between MOOC GitHub

Module_1/Lesson_2/readme.md

@@ -123,7 +123,7 @@ In this activity, reflect on your answers to the questions and then compare your
 
 ### Transparent Science is Reproducible Science
 
-When computers are used to produce scientific research, the code is considered a "method". Much like a lab research setting, a set of instructions for working with cells or agar plates can be considered a method. Peer-reviewed methods are an essential step in the scientific process. When these steps are not shared, no-one else can reproduce the work or build upon it for future scientific endeavors. Open methods allow people to judge whether or not the methods are trustworthy. In Lesson 1, the story of the  Error presented a poignant example of science that was not reproducible because of a lack of data transparency.
+When computers are used to produce scientific research, the code is considered a "method". Much like a lab research setting, a set of instructions for working with cells or agar plates can be considered a method. Peer-reviewed methods are an essential step in the scientific process. When these steps are not shared, no-one else can reproduce the work or build upon it for future scientific endeavors. Open methods allow people to judge whether or not the methods are trustworthy. In Lesson 1, the story of the Global Cooling Error presented a poignant example of science that was not reproducible because of a lack of data transparency.
 
 ### Open Science Can Improve Accuracy
 
@@ -137,7 +137,7 @@ This allows others to check if they can arrive at the same conclusion as the ori
 
 <img src="../images/media/image216.jpg" style="width: 350px; height: auto;" />
 
-Here is an example of open science that was able to correct errors in a healthcare study quickly, saving lives! In 2021, a [study](https://www.nature.com/articles/s41598-021-84092-1) was published that found that COVID stay-at-home policies did not stop transmission of the virus. The study was highlighted by prominent lockdown skeptics and news sites – swiftly gaining the attention of many people right at a critical time in the pandemic. Here was a scientific research article that said lockdowns don’t work! The authors of the study published source code and data with their paper. This allowed others to quickly look at how they arrived at their conclusion. Almost immediately, questions were raised about the paper and within nine months, two papers [here](https://www.nature.com/articles/s41598-021-02461-2) and [here](https://www.nature.com/articles/s41598-021-02096-3) pointed out major analysis method errors. The original paper was retracted. We all make mistakes. In this case, the paper's lack of reproducibility had major policy implications and because the original authors had practiced open science, the error was rapidly corrected!
+Here is an example of open science that was able to correct errors in a healthcare study quickly, saving lives! In 2021, a [study](https://www.nature.com/articles/s41598-021-84092-1) was published that found that COVID stay-at-home policies did not stop transmission of the virus. The study was highlighted by prominent lockdown skeptics and news sites – swiftly gaining the attention of many people right at a critical time in the pandemic. Here was a scientific research article that said lockdowns don’t work! The authors of the study published source code and data with their paper. This allowed others to quickly look at how they arrived at their conclusion. Almost immediately, questions were raised about the paper and within nine months, two papers ([here](https://www.nature.com/articles/s41598-021-02461-2) and [here](https://www.nature.com/articles/s41598-021-02096-3)) pointed out major analysis method errors. The original paper was retracted. We all make mistakes. In this case, the paper's lack of reproducibility had major policy implications and because the original authors had practiced open science, the error was rapidly corrected!
 
 Please note: In a biological sciences context, the errors in the original paper are an example of lacking in reproducibility. In a computer science context, this could be seen as a lack of replicability.
 

Module_2/Lesson_5/readme.md

@@ -34,7 +34,7 @@ Pre-prints have gained particular significance during the COVID-19 pandemic, whe
 1. **Rapid Dissemination:** Pre-prints enable researchers to swiftly share their findings with the scientific community and the public, sometimes within days of completing their research. This swift dissemination is particularly beneficial when dealing with urgent or rapidly evolving topics.
 2. **Peer Review:** While pre-prints are not peer-reviewed, they often undergo a form of community review. Researchers and experts can provide feedback and constructive criticism, helping authors improve their work before formal journal publication.
 3. **Variety of Fields:** Pre-prints are not limited to any specific scientific discipline. They are used in fields ranging from medicine and biology to physics and social sciences, making them a versatile tool for disseminating research.
-4. **Versions and Citations:** Pre-prints can have different versions, and the final peer- reviewed paper may differ. Pre-prints may be cited when discussing ongoing research, allowing for transparency in the academic discourse.<br><br><strong>Note: if the preprint is old and has been rejected by a journal it shouldn't be cited. It also shouldn't be cited if a full published version is available.</strong>
+4. **Versions and Citations:** Pre-prints can have different versions, and the final peer-reviewed paper may differ. Pre-prints may be cited when discussing ongoing research, allowing for transparency in the academic discourse.<br><br><strong>Note: if the preprint is old and has been rejected by a journal it shouldn't be cited. It also shouldn't be cited if a full published version is available.</strong>
 5. **Free Access:** Pre-prints are typically freely accessible to anyone with an internet connection. This open access promotes equality and inclusivity in science, enabling researchers from various backgrounds and institutions to engage with the latest research.
 6. **Not a Replacement for Peer Review:** Although pre-prints are valuable tools for early sharing and collaboration, they are not a substitute for a formal peer-reviewed publication. Researchers and readers should examine pre-prints with the understanding that they have not undergone the rigorous peer review process that journals provide.
 

Module_4/Lesson_2/readme.md

@@ -187,7 +187,7 @@ These are a few links to NASA-specific repositories that may be of interest:
 
 So, you've discovered some exciting open code that might help you solve your scientific problem. Can you trust this code you discovered on the web? Will it be useful? How much time will it take to learn it? Could the code contain malware? Could you get in legal trouble for using it?
 
-**Examples:** You found the “General Ocean Turbulence Model (GOTM)” on the internet, and it looks promising. Or, you just found lots of code snippets and functions related to the Lomb-Scargle power spectrum. Now, you would like to assess these pieces of code to help you decide if you should use them. This section discusses some best practices for assessing if the code will help you.
+**Examples:** You found the "General Ocean Turbulence Model (GOTM)" on the internet, and it looks promising. Or, you just found lots of code snippets and functions related to the Lomb-Scargle power spectrum. Now, you would like to assess these pieces of code to help you decide if you should use them. This section discusses some best practices for assessing if the code will help you.
 
 ### Four General Considerations for Assessing Open Software
 
@@ -253,7 +253,7 @@ Open software is perceived to have more security risks. This is generally less o
 - Consult with your institutional open software policies and IT staff
 - Use authoritative, reputable sources to minimize security risks
 - Set strict security rules and standards when using a dependency
-- Use security tools to check for vulnerabilities (e.g., [Open Worldwide Application Security</u> Project®](https://owasp.org/))
+- Use security tools to check for vulnerabilities (e.g., [Open Worldwide Application Security Project®](https://owasp.org/))
 - Avoid unsupported open-source software. Switch to actively developed components or develop it yourself
 - Check with your latest institutional policies on using Machine Learning and Artificial Intelligence tools
 - Use caution when using external tools with secure or closed access data. It may be possible for the external tool to publicly share what should be restricted information