Merge pull request #16 from albarema/webpage

updates website

_site/develop/practical_workshop.html

@@ -113,10 +113,10 @@
     <nav class="navbar navbar-expand-lg " data-bs-theme="dark">
       <div class="navbar-container container-fluid">
       <div class="navbar-brand-container mx-auto">
-    <a href="../index.html" class="navbar-brand navbar-brand-logo">
+    <a href="http://hds-sandbox.github.io/" class="navbar-brand navbar-brand-logo">
     <img src="../img/logo.png" alt="" class="navbar-logo">
     </a>
-    <a class="navbar-brand" href="../index.html">
+    <a class="navbar-brand" href="http://hds-sandbox.github.io/">
     <span class="navbar-title">RDM for biodata</span>
     </a>
   </div>
@@ -128,7 +128,7 @@
             <ul class="navbar-nav navbar-nav-scroll me-auto">
   <li class="nav-item">
     <a class="nav-link" href="../index.html"> 
-<span class="menu-text">Home</span></a>
+<span class="menu-text">Intro</span></a>
   </li>  
   <li class="nav-item">
     <a class="nav-link" href="../develop/01_RDM_intro.html"> 
@@ -219,7 +219,7 @@ <h1 class="title">Practical material</h1>
     <div>
     <div class="quarto-title-meta-heading">Modified</div>
     <div class="quarto-title-meta-contents">
-      <p class="date-modified">May 15, 2024</p>
+      <p class="date-modified">June 4, 2024</p>
     </div>
   </div>
 

_site/index.html

@@ -161,7 +161,7 @@
     <div>
     <div class="quarto-title-meta-heading">Modified</div>
     <div class="quarto-title-meta-contents">
-      <p class="date-modified">May 22, 2024</p>
+      <p class="date-modified">June 4, 2024</p>
     </div>
   </div>
 
@@ -181,17 +181,15 @@
 <section id="welcome-to-rdm-for-biodata" class="level1 hero-banner">
 <h1>Welcome to RDM for biodata</h1>
 </section>
-<div class="callout callout-style-default callout-warning callout-titled" title="Practical RDM workshop">
-<div class="callout-header d-flex align-content-center">
+<div class="callout callout-style-simple callout-warning no-icon">
+<div class="callout-body d-flex">
 <div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Practical RDM workshop
+<i class="callout-icon no-icon"></i>
 </div>
-</div>
-<div class="callout-body-container callout-body">
+<div class="callout-body-container">
 <p>We offer workshops on practical RDM for biodata. Keep an eye on the upcoming events on the <a href="https://hds-sandbox.github.io/news.html">Sandbox website</a>.</p>
+<p><img src="develop/images/cookie_combined.png" class="img-fluid"></p>
+</div>
 </div>
 </div>
 <p>The course “Research Data Management (RDM) for biological data” is designed to provide participants with foundational knowledge and practical skills in handling the extensive data generated by modern studies, with a focus on Next Generation Sequencing (NGS) data. It emphasizes the importance of Open Science and FAIR principles in managing data effectively. This course covers essential principles and best practices guidelines in data organization, metadata annotation, version control, and data preservation. These principles are explored from a computational perspective, ensuring participants gain hands-on experience in applying them to real-world scenarios in their research labs. Additionally, the course delves into FAIR principles and Open Science, promoting collaboration and reproducibility in research endeavors. By the course’s conclusion, attendees will possess essential tools and techniques to address the data challenges prevalent in today’s NGS research landscape, as well as in other related fields to health and bioinformatics.</p>

_site/search.json

@@ -459,7 +459,7 @@
     "href": "index.html",
     "title": "Welcome to RDM for biodata",
     "section": "",
-    "text": "Welcome to RDM for biodata\n\n\n\n\n\n\n\nPractical RDM workshop\n\n\n\nWe offer workshops on practical RDM for biodata. Keep an eye on the upcoming events on the Sandbox website.\n\n\nThe course “Research Data Management (RDM) for biological data” is designed to provide participants with foundational knowledge and practical skills in handling the extensive data generated by modern studies, with a focus on Next Generation Sequencing (NGS) data. It emphasizes the importance of Open Science and FAIR principles in managing data effectively. This course covers essential principles and best practices guidelines in data organization, metadata annotation, version control, and data preservation. These principles are explored from a computational perspective, ensuring participants gain hands-on experience in applying them to real-world scenarios in their research labs. Additionally, the course delves into FAIR principles and Open Science, promoting collaboration and reproducibility in research endeavors. By the course’s conclusion, attendees will possess essential tools and techniques to address the data challenges prevalent in today’s NGS research landscape, as well as in other related fields to health and bioinformatics.\n\n\n\n\n\n\nCourse Overview\n\n\n\n\n📖 Syllabus:\n\n\nData Lifecycle Management\nData Management Plans (DMPs)\nData Organization and storage\nDocumentation standards for biodata\nVersion Control and Collaboration\nProcessing and analyzing biodata\nStoring and sharing biodata\n\n\n⏰ Total Time Estimation: X hours\n\n📁 Supporting Materials:\n\n👨‍💻 Target Audience: Ph.D., MSc, anyone interested in RDM for NGS data or other related fields within bioinformatics.\n👩‍🎓 Level: Beginner.\n🔒 License: Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.\n\n💰 Funding: This project was funded by the Novo Nordisk Fonden (NNF20OC0063268).\n\n\n\n\n\n\n\n\n\n\nCourse Requirements\n\n\n\n\nBasic understanding Next Generation Sequencing data and formats.\nCommand Line experience\nBasic programming experience\nQuarto or Mkdocs tools\n\n\n\nThis course offers participants with an in-depth introduction to effectively managing the vast amounts of data generated in modern studies. Throughout the program, emphasis is placed on practical understanding of RDM principles and the importance of efficient handling of large datasets. In this context, participants will learn the necessity of adopting Open Science and FAIR principles for enhancing data accessibility and reusability.\nParticipants will acquire practical skills for organizing data, including the creation of folder and file structures, and the implementation of metadata to facilitate data discoverability and interpretation. Special attention is given to the development of Data Management Plans (DMPs) with examples tailored to omics data, ensuring compliance with institutional and funding agency requirements while maintaining data integrity. Attendees will also gain insights into the establishment of simple databases and the use of version control systems to track changes in data analysis, thereby promoting collaboration and reproducibility.\nThe course concludes with a focus on archiving and data repositories, enabling participants to learn strategies for preserving and sharing data for long-term scientific usage. By the end of the course, attendees will be equipped with essential tools and techniques to effectively navigate the challenges prevalent in today’s research landscape. This will not only foster successful data management practices but also enhance collaboration within the scientific community.\n\n\n\n\n\n\nCourse Goals\n\n\n\nBy the end of this workshop, you should be able to apply the following concepts in the context of Next Generation Sequencing data:\n\nUnderstand the Importance of Research Data Management (RDM)\nFamiliarize Yourself with FAIR and Open Science Principles\nDraft a Data Management Plan for your own Data\nEstablish File and Folder Naming Conventions\nEnhance Data with Descriptive Metadata\nImplement Version Control for Data Analysis\nSelect an Appropriate Repository for Data Archiving\nMake your data analysis and workflows reproducible and FAIR\n\n\n\n\n\n\n\n\n\nWarning\n\n\n\nThis is a computational workshop that focuses primarily on the digital aspect of our data. While wet lab Research Data Management (RDM) involving protocols, instruments, reagents, ELM or LIMS systems is integral to the entire RDM process, it won’t be covered in this course.\nAs part of effective data management, it’s crucial to prioritize strategies that ensure security and privacy. While these aspects are important, please note that they won’t be covered in our course. However, we highly recommend enrolling in the GDPR course offered by Center for Health Data Science, specially if you’re working with sensitive data. This course specifically focuses on GDPR compliance and will provide you with valuable insights and skills in managing data privacy and security.\n\n\n\nDanish institutional RDM links\n\nUniversity of Copenhagen\nUniversity Library of Southern Denmark\nTechnical University of Denmark\nAalborg University\nAarhus University\n\n\n\nAcknowledgements\n\nRDMkit, ELIXIR (2021) Research Data Management Kit. A deliverable from the EU-funded ELIXIR-CONVERGE project (grant agreement 871075).\nUniversity of Copenhagen Research Data Management Team.\nMartin Proks and Sarah Lundregan, Brickman Lab, NNF Center for Stem Cell Biology (reNEW), University of Copenhagen.\nRichard Dennis, Data Steward, NNF Center for Stem Cell Biology (reNEW), University of Copenhagen.\nNBISweden.\n\n\n\n\n\n\nCopyrightCC-BY-SA 4.0 license"
+    "text": "Welcome to RDM for biodata\n\n\n\n\n\n\n\nWe offer workshops on practical RDM for biodata. Keep an eye on the upcoming events on the Sandbox website.\n\n\n\n\nThe course “Research Data Management (RDM) for biological data” is designed to provide participants with foundational knowledge and practical skills in handling the extensive data generated by modern studies, with a focus on Next Generation Sequencing (NGS) data. It emphasizes the importance of Open Science and FAIR principles in managing data effectively. This course covers essential principles and best practices guidelines in data organization, metadata annotation, version control, and data preservation. These principles are explored from a computational perspective, ensuring participants gain hands-on experience in applying them to real-world scenarios in their research labs. Additionally, the course delves into FAIR principles and Open Science, promoting collaboration and reproducibility in research endeavors. By the course’s conclusion, attendees will possess essential tools and techniques to address the data challenges prevalent in today’s NGS research landscape, as well as in other related fields to health and bioinformatics.\n\n\n\n\n\n\nCourse Overview\n\n\n\n\n📖 Syllabus:\n\n\nData Lifecycle Management\nData Management Plans (DMPs)\nData Organization and storage\nDocumentation standards for biodata\nVersion Control and Collaboration\nProcessing and analyzing biodata\nStoring and sharing biodata\n\n\n⏰ Total Time Estimation: X hours\n\n📁 Supporting Materials:\n\n👨‍💻 Target Audience: Ph.D., MSc, anyone interested in RDM for NGS data or other related fields within bioinformatics.\n👩‍🎓 Level: Beginner.\n🔒 License: Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.\n\n💰 Funding: This project was funded by the Novo Nordisk Fonden (NNF20OC0063268).\n\n\n\n\n\n\n\n\n\n\nCourse Requirements\n\n\n\n\nBasic understanding Next Generation Sequencing data and formats.\nCommand Line experience\nBasic programming experience\nQuarto or Mkdocs tools\n\n\n\nThis course offers participants with an in-depth introduction to effectively managing the vast amounts of data generated in modern studies. Throughout the program, emphasis is placed on practical understanding of RDM principles and the importance of efficient handling of large datasets. In this context, participants will learn the necessity of adopting Open Science and FAIR principles for enhancing data accessibility and reusability.\nParticipants will acquire practical skills for organizing data, including the creation of folder and file structures, and the implementation of metadata to facilitate data discoverability and interpretation. Special attention is given to the development of Data Management Plans (DMPs) with examples tailored to omics data, ensuring compliance with institutional and funding agency requirements while maintaining data integrity. Attendees will also gain insights into the establishment of simple databases and the use of version control systems to track changes in data analysis, thereby promoting collaboration and reproducibility.\nThe course concludes with a focus on archiving and data repositories, enabling participants to learn strategies for preserving and sharing data for long-term scientific usage. By the end of the course, attendees will be equipped with essential tools and techniques to effectively navigate the challenges prevalent in today’s research landscape. This will not only foster successful data management practices but also enhance collaboration within the scientific community.\n\n\n\n\n\n\nCourse Goals\n\n\n\nBy the end of this workshop, you should be able to apply the following concepts in the context of Next Generation Sequencing data:\n\nUnderstand the Importance of Research Data Management (RDM)\nFamiliarize Yourself with FAIR and Open Science Principles\nDraft a Data Management Plan for your own Data\nEstablish File and Folder Naming Conventions\nEnhance Data with Descriptive Metadata\nImplement Version Control for Data Analysis\nSelect an Appropriate Repository for Data Archiving\nMake your data analysis and workflows reproducible and FAIR\n\n\n\n\n\n\n\n\n\nWarning\n\n\n\nThis is a computational workshop that focuses primarily on the digital aspect of our data. While wet lab Research Data Management (RDM) involving protocols, instruments, reagents, ELM or LIMS systems is integral to the entire RDM process, it won’t be covered in this course.\nAs part of effective data management, it’s crucial to prioritize strategies that ensure security and privacy. While these aspects are important, please note that they won’t be covered in our course. However, we highly recommend enrolling in the GDPR course offered by Center for Health Data Science, specially if you’re working with sensitive data. This course specifically focuses on GDPR compliance and will provide you with valuable insights and skills in managing data privacy and security.\n\n\n\nDanish institutional RDM links\n\nUniversity of Copenhagen\nUniversity Library of Southern Denmark\nTechnical University of Denmark\nAalborg University\nAarhus University\n\n\n\nAcknowledgements\n\nRDMkit, ELIXIR (2021) Research Data Management Kit. A deliverable from the EU-funded ELIXIR-CONVERGE project (grant agreement 871075).\nUniversity of Copenhagen Research Data Management Team.\nMartin Proks and Sarah Lundregan, Brickman Lab, NNF Center for Stem Cell Biology (reNEW), University of Copenhagen.\nRichard Dennis, Data Steward, NNF Center for Stem Cell Biology (reNEW), University of Copenhagen.\nNBISweden.\n\n\n\n\n\n\nCopyrightCC-BY-SA 4.0 license"
   },
   {
     "objectID": "develop/06_file_structure.html",

_site/sitemap.xml

@@ -2,7 +2,7 @@
 <urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
   <url>
     <loc>https://hds-sandbox.github.io/RDM_NGS_course/index.html</loc>
-    <lastmod>2024-05-22T08:52:13.227Z</lastmod>
+    <lastmod>2024-06-04T14:19:16.663Z</lastmod>
   </url>
   <url>
     <loc>https://hds-sandbox.github.io/RDM_NGS_course/develop/01_RDM_intro.html</loc>
@@ -36,4 +36,8 @@
     <loc>https://hds-sandbox.github.io/RDM_NGS_course/develop/07_repos.html</loc>
     <lastmod>2024-05-22T08:09:55.903Z</lastmod>
   </url>
+  <url>
+    <loc>https://hds-sandbox.github.io/RDM_NGS_course/develop/practical_workshop.html</loc>
+    <lastmod>2024-06-04T14:16:27.856Z</lastmod>
+  </url>
 </urlset>

index.qmd

@@ -28,8 +28,11 @@ summary: Index page, intro to course
 :::
 
 
-:::{.callout-warning title="Practical RDM workshop"}
+:::{.callout-warning appearance="minimal"}
+
 We offer workshops on practical RDM for biodata. Keep an eye on the upcoming events on the [Sandbox website](https://hds-sandbox.github.io/news.html).
+
+![](develop/images/cookie_combined.png)
 :::
 
 The course "Research Data Management (RDM) for biological data" is designed to provide participants with foundational knowledge and practical skills in handling the extensive data generated by modern studies, with a focus on Next Generation Sequencing (NGS) data. It emphasizes the importance of Open Science and FAIR principles in managing data effectively. This course covers essential principles and best practices guidelines in data organization, metadata annotation, version control, and data preservation. These principles are explored from a computational perspective, ensuring participants gain hands-on experience in applying them to real-world scenarios in their research labs. Additionally, the course delves into FAIR principles and Open Science, promoting collaboration and reproducibility in research endeavors. By the course's conclusion, attendees will possess essential tools and techniques to address the data challenges prevalent in today's NGS research landscape, as well as in other related fields to health and bioinformatics.