Merge pull request #67 from ESA-EarthCODE/rebase-review2

Review Edits from table 2

Author: sunnydean

.gitignore

@@ -2,3 +2,11 @@ node_modules
 .vitepress/dist
 .vitepress/cache
 examples/_build
+.DS_Store
+pages/.DS_Store
+pages/Community and Collaboration/.DS_Store
+pages/Community and Collaboration/Getting Started With The EarthCODE Discourse/.DS_Store
+pages/Integrating New Platforms to EarthCODE/.DS_Store
+pages/public/img/.DS_Store
+pages/public/img/platforms/.DS_Store
+pages/public/img/terms/.DS_Store

.vitepress/config.mjs

@@ -8,6 +8,7 @@ const sideBar = withSidebar(
     cleanUrls: true,
     title: "EarthCODE Documentation",
     titleTemplate: " EarthCODE",
+    collapsed: true,
     description: "Documentation for the EarthCODE website",
     base: "/documentation/documentation/",
     ignoreDeadLinks: [
@@ -111,6 +112,10 @@ const sideBar = withSidebar(
 const trainingSection = sideBar.themeConfig.sidebar.find(section => section.text === 'Training and Resources')
 trainingSection.items.push({ text: 'Examples', link: 'https://esa-earthcode.github.io/documentation/examples/' })
 
+sideBar.themeConfig.sidebar.forEach(group => {
+  group.collapsed = true;
+});
+
 export default defineConfig(
   sideBar
 );

.vitepress/theme/components/FeatureCard.vue

@@ -0,0 +1,43 @@
+<template>
+    <div class="feature-card">
+      <div class="text"><slot /></div>
+      <div class="image">
+        <img :src="resolvedSrc" :alt="alt" />
+      </div>
+    </div>
+  </template>
+  
+  <script setup>
+  // resolve relative image paths to work with Vite's base URL
+  import { computed } from 'vue'
+    const props = defineProps({
+    img: { type: String, required: true },
+    alt: { type: String, default: '' }
+  })
+    const base = import.meta.env.BASE_URL
+    const resolvedSrc = computed(() => {
+    if (props.img.startsWith('/')) {
+      return base + props.img.slice(1)
+    }
+    return props.img
+  })
+  </script>
+  
+  <style>
+  .feature-card {
+    display: flex;
+    align-items: center;
+    gap: 1rem;
+    margin: 1.5rem 0;
+  }
+  .feature-card .text {
+    flex: 1;
+    padding-right: 1rem;
+  }
+  .feature-card .image img {
+    max-width: 250px;
+    height: auto;
+    border-radius: 4px;
+  }
+  </style>
+  

.vitepress/theme/index.js

@@ -1,5 +1,7 @@
 import Layout from "./Layout.vue";
 import "./style.css";
+import FeatureCard from './components/FeatureCard.vue'
+
 
 /** @type {import('vitepress').Theme} */
 export default {
@@ -9,5 +11,6 @@ export default {
       app.use(await import("@eox/esa-ui/components/header.js"));
       app.use(await import("@eox/esa-ui/components/cookies.js"));
     }
+    app.component('FeatureCard', FeatureCard)
   }
 };

pages/Community and Best Practices/Code Data and Workflow Quality.md

@@ -1,5 +1,10 @@
+---
+order: 2
+---
 # Code, Data and Workflow Quality
-
+:::warning 🛠️ Page Under Development
+Content is being actively developed and updated for this page. EarthCODE's documentation is a living document and will be continuously updated with detailed reviews.
+:::
 ## Applying and maintaining FAIR Principles
 
 The checklist below provides practical guidance for applying the FAIR principles in EarthCODE projects.

pages/Community and Best Practices/FAIR and Open Science.md

@@ -1,5 +1,22 @@
+---
+order: 1
+---
 # FAIR and Open Science
 
+## Why FAIR?
+
+Modern Earth system science faces complex challenges that demand collaborative, transparent, and reproducible approaches. At the heart of this transformation is the convergence of **FAIR principles** (Findability, Accessibility, Interoperability, and Reusability) and Open Science - which create unprecedented opportunities for scalable, cross-sector research and decision-making.
+
+ESA's strategic objective is to **foster the development of a culture and practice of openness in EO science, applications and industry, and of a sustainable open innovation ecosystem**.
+
+![Open Science](/img/terms/open-science-esa.png)
+
+Adopting FAIR principles at scale for data and workflows in Earth Observation is essential for implementing this vision as it enables scientists to (1) Access and process satellite and in-situ data (in collaborative cloud environments such as EarthCODE Platforms), (2) Develop and publish reusable code and workflows, (3) Validate outputs and share reproducible results, and (4) Collaborate across institutional, disciplinary, and national boundaries. Openness enhances transparency and trust in research results, facilitates collaboration between different institutions and disciplines, and significantly reduces duplication of efforts.
+
+Moreover, FAIR and Open Science practices improve data quality and longevity, allowing researchers to build upon existing knowledge and to more effectively address complex global challenges such as climate change, biodiversity loss, and sustainable development.
+
+Adopting FAIR and Open Science practices also provides direct personal benefits to researchers. It enhances the visibility and citation of their work, fosters potential new collaborations, and expands professional networks. Moreover, by making research outputs clearly documented and easily accessible, researchers save time in their daily workflows, simplify data management tasks, and improve their ability to build upon prior work—including their own.
+
 ## Open Science: A Collaborative and Transparent Approach
 Open Science is a movement that promotes transparency, accessibility, and collaboration in scientific research. According to [UNESCO Recommendation on Open Science](https://www.unesco.org/en/open-science/about?hub=686), Open Science encompasses open access to scientific knowledge, open data, open-source software, open workflows and broader participation in research processes.
 
@@ -27,7 +44,7 @@ FAIR is not just about data; **software**, **models**, and **workflows** must al
 - **FAIR metadata** for software and workflows, ensuring clear documentation of inputs, outputs, dependencies, and provenance.
 - **Persistent identifiers (PIDs)** for datasets, algorithms, and workflows to support traceability and reuse.
 - **Interoperable formats and standards**, such as netCDF, Zarr, and STAC for data, or CWL (Common Workflow Language) for workflow portability, OGC API - Processes for standardized execution, and openEO for cloud-based EO data processing, ensuring compatibility across platforms.
-- **Accessible computing environments**, such as the [cloud-based processing platforms available in EarthCODE](https://esa-earthcode.github.io/documentation/Technical%20Documentation/Working%20With%20Platforms%20and%20Sponsorship/), which allow users to execute EO workflows.
+- **Accessible computing environments**, such as the [cloud-based processing platforms available in EarthCODE](https://nor-discover.org/), which allow users to execute EO workflows.
 
 **FAIR does not imply that data or software must be open** by default, but rather that they are well-described, structured, and reusable under appropriate conditions. By applying FAIR principles to both data and processing, the EO community can enhance scientific transparency, improve cross-disciplinary collaboration, and enable scalable, automated analysis—key for addressing global challenges like climate change, disaster response, and biodiversity conservation.
 
@@ -77,9 +94,29 @@ The FAIR principles provide high-level guidance for ensuring that data, software
 By explicitly declaring its choices, the EarthCODE community ensures that its approach to FAIR is transparent, actionable, and aligned with best practices in Earth Observation data management and processing.
 This structured implementation enhances data discoverability, interoperability, and reuse while maintaining technical rigor and community consensus.
 
+## Open Science: A Collaborative and Transparent Approach
+Open Science is a movement that promotes transparency, accessibility, and collaboration in scientific research. According to [UNESCO Recommendation on Open Science](https://www.unesco.org/en/open-science/about?hub=686), Open Science encompasses open access to scientific knowledge, open data, open-source software, open workflows and broader participation in research processes.
+
+## Collaboration Tips
+A fundamental aspect of Open Science is **sharing while doing**, rather than treating data and publications as an afterthought. The earlier Open Science principles are incorporated into research workflows, the easier they are to implement. This approach enables:
+
+- **Early data sharing**, fostering collaboration and enabling reproducibility.
+- **Transparent methodologies**, making research processes more robust and verifiable.
+- **Open access to publications and resources**, ensuring that knowledge is freely available to the broader community.
+
+By integrating Open Science with FAIR principles, the EO community can maximize the impact of research, enhance data accessibility, and facilitate cross-domain innovation.
+
+
+
+### Collaboration in EarthCODE
+
+Guidance for setting up user permissions, managing team workflows, and collaborating with other researchers within the EarthCODE environment.
+
+
 ### References
 
-- Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). [DOI: 10.1038/sdata.2016.18](https://doi.org/10.1038/sdata.2016.18)
-- FAIR Data Maturity Model Working Group. (2020). FAIR Data Maturity Model. Specification and Guidelines (1.0). Zenodo. [DOI: 10.15497/rda00050](https://doi.org/10.15497/rda00050)
-- Annika Jacobsen, Ricardo de Miranda Azevedo, Nick Juty, Dominique Batista, Simon Coles, Ronald Cornet, Mélanie Courtot, Mercè Crosas, Michel Dumontier, Chris T. Evelo, Carole Goble, Giancarlo Guizzardi, Karsten Kryger Hansen, Ali Hasnain, Kristina Hettne, Jaap Heringa, Rob W.W. Hooft, Melanie Imming, Keith G. Jeffery, Rajaram Kaliyaperumal, Martijn G. Kersloot, Christine R. Kirkpatrick, Tobias Kuhn, Ignasi Labastida, Barbara Magagna, Peter McQuilton, Natalie Meyers, Annalisa Montesanti, Mirjam van Reisen, Philippe Rocca-Serra, Robert Pergl, Susanna-Assunta Sansone, Luiz Olavo Bonino da Silva Santos, Juliane Schneider, George Strawn, Mark Thompson, Andra Waagmeester, Tobias Weigel, Mark D. Wilkinson, Egon L. Willighagen, Peter Wittenburg, Marco Roos, Barend Mons, Erik Schultes; FAIR Principles: Interpretations and Implementation Considerations. Data Intelligence 2020; 2 (1-2): 10–29. [DOI: 10.1162/dint_r_00024](https://doi.org/10.1162/dint_r_00024)
+*- Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. *Scientific Data*, 3, Article 160018. [https://doi.org/10.1038/sdata.2016.18](https://doi.org/10.1038/sdata.2016.18)*
+
+*- FAIR Data Maturity Model Working Group. (2020). FAIR Data Maturity Model: Specification and Guidelines (Version 1.0). *Zenodo*. [https://doi.org/10.15497/rda00050](https://doi.org/10.15497/rda00050)*
 
+*- Jacobsen, A., de Miranda Azevedo, R., Juty, N., Batista, D., Coles, S., Cornet, R., Courtot, M., Crosas, M., Dumontier, M., Evelo, C. T., Goble, C., Guizzardi, G., Hansen, K. K., Hasnain, A., Hettne, K., Heringa, J., Hooft, R. W. W., Imming, M., Jeffery, K. G., Kaliyaperumal, R., Kersloot, M. G., Kirkpatrick, C. R., Kuhn, T., Labastida, I., Magagna, B., McQuilton, P., Meyers, N., Montesanti, A., van Reisen, M., Rocca-Serra, P., Pergl, R., Sansone, S.-A., da Silva Santos, L. O. B., Schneider, J., Strawn, G., Thompson, M., Waagmeester, A., Weigel, T., Wilkinson, M. D., Willighagen, E. L., Wittenburg, P., Roos, M., Mons, B., & Schultes, E. (2020). FAIR Principles: Interpretations and Implementation Considerations. *Data Intelligence*, 2(1–2), 10–29. [https://doi.org/10.1162/dint_r_00024](https://doi.org/10.1162/dint_r_00024)*

pages/Community and Best Practices/index.md

@@ -3,5 +3,11 @@ order: 4
 ---
 # Best practices
 
-- [Code, Data and Workflow Quality](./Code%20Data%20and%20Workflow%20Quality.md)
-- [FAIR and Open Science](./FAIR%20and%20Open%20Science.md)
+The EarthCODE ecosystem is designed to support FAIR and Open Science by default—but achieving that in practice depends on how you prepare and publish and manage your code, data, and workflows. This section introduces how EarthCODE implements FAIR principles and resources to help you follow best practices that make your research more findable, accessible, interoperable, and reusable.
+
+These guides show you how to structure your work in a way that's aligned with EarthCODE requirements and community standards. You’ll find practical advice on how to improve metadata, adopt version control, structure your documentation, and ensure that your outputs are truly FAIR.
+
+Explore the following guides:
+
+- [Code, Data and Workflow Quality](./Code%20Data%20and%20Workflow%20Quality.md): A practical walkthrough for preparing your research artefacts for publication and reuse.
+- [FAIR and Open Science](./FAIR%20and%20Open%20Science.md): An in-depth look at how to make your published results FAIR and how EarthCODE supports you in that journey.

pages/Community and Collaboration/Collaboration and Community/Collaborating Within a Project.md

@@ -0,0 +1,9 @@
+---
+order: 0
+---
+# Collaborating Within a Project
+:::warning 🛠️ Page Under Development
+Content is being actively developed and updated for this page. EarthCODE's documentation is a living document and will be continuously updated with detailed reviews.
+:::
+How to collaborate with other researchers within EarthCODE.
+

pages/Community and Collaboration/Collaboration and Community/Joining or Creating a Research Team.md

@@ -2,5 +2,8 @@
 order: 2
 ---
 # Sharing and Publishing Results
+:::warning 🛠️ Page Under Development
+Content is being actively developed and updated for this page. EarthCODE's documentation is a living document and will be continuously updated with detailed reviews.
+:::
 Instructions on how to share research outputs, including data, code, and documentation, and manage their publication through the Open Science Catalog.