fix more of dem paths

astro.config.mjs

@@ -16,7 +16,7 @@ import sitemap from '@astrojs/sitemap';
 // https://astro.build/config
 export default defineConfig({
   integrations: [tailwind(), mdx(), icon(), pagefind(), sitemap()],
-  site: 'https://arc-rdm.org/',
+  site: 'https://arc-rdm.org', // https://docs.astro.build/en/guides/deploy/github/#using-github-pages-with-a-custom-domain
   // base: '/arc-website/', // will kill pagefind integration without trailing slash
   markdown: {
     remarkPlugins: [remarkDirective, remarkReplaceLinks(), remarkReplaceTooltips(), remarkAsides()],

src/components/Navbar.astro

@@ -68,7 +68,7 @@ const isHome = Astro.url.pathname === URLS.INTERNAL_HOME
           </label>
         </div>
         <a class="btn btn-ghost text-xl" href={URLS.INTERNAL_HOME} >
-          <img src="/arc-website/favicon.svg" alt="logo" class="h-8 w-8" />
+          <img src="/favicon.svg" alt="logo" class="h-8 w-8" />
         </a>
       </div>
       { isHome &&
@@ -83,7 +83,7 @@ const isHome = Astro.url.pathname === URLS.INTERNAL_HOME
           <img
             id="github-logo"
             class="p-2"
-            src="/arc-website/github-mark.svg">
+            src="/github-mark.svg">
           </img>
         </a>
         <ThemeController />
@@ -104,11 +104,11 @@ const isHome = Astro.url.pathname === URLS.INTERNAL_HOME
 <style>
   /* Light mode: Show light-mode.svg */
 html[data-theme="light"] #github-logo {
-  content: url('/arc-website/github-mark.svg');
+  content: url('/github-mark.svg');
 }
 
 /* Dark mode: Show dark-mode.svg */
 html[data-theme="dark"] #github-logo {
-  content: url('/arc-website/github-mark-white.svg');
+  content: url('/github-mark-white.svg');
 }
 </style>

src/pages/details/arc-data-hub.md

@@ -14,7 +14,7 @@ The **ARC Data Hub** concept applies the software development principles of _Con
 ARCs can be continuously validated, built, and deployed much like software.
 By using CI/CD for a set of subsequently defined tasks, many collaborative cloud platforms such as GitLab, GitHub, or Bitbucket can be used to build an ARC Data Hub.
 
-![ARC Data Hub leverages CI/CD capabilities to build, deploy, and validate ARCs](/arc-website/arc-data-hub-overview.png)
+![ARC Data Hub leverages CI/CD capabilities to build, deploy, and validate ARCs](/arc-data-hub-overview.png)
 
 ## Continuous Deployment
 
@@ -23,7 +23,7 @@ CD can be used to continuously deploy ARC artifacts such as metadata export form
 ARC Data Hubs use CD to build and deploy the [ARC-RO-Crate metadata]({{INTERNAL_DEV_REPRESENTATION_RO_CRATE}}) of each commit to a central package registry.
 This way, both [representations of the ARC]({{INTERNAL_DEV_REPRESENTATION}}) are always in sync and accessible, deploying both a user-centric and a machine-readable view on the ARC.
 
-![ARC Data Hubs use CD to build and deploy the ARC-RO-Crate metadata](/arc-website/ci-cd-arc-application.png)
+![ARC Data Hubs use CD to build and deploy the ARC-RO-Crate metadata](/ci-cd-arc-application.png)
 
 ## Continuous Integration
 
@@ -32,7 +32,7 @@ ARC Data Hubs can run a user-selected set of validation packages on each commit
 
 Furthermore, the validation package output can be used to continuously inform the user about the current state of the ARC, for example by creating badges on the ARC page, much like the widely known `build and test` badges in software development.
 
-## Continuous Quality Control (CQC)
+## Continuous Quality Control
 
 Continuous Quality Control (CQC) is a combination of CI and CD that integrates external services depending on the result of ARC validation.
 Successful validation can trigger downstream applications, either automatically or manually via _CQC Hooks_.
@@ -43,4 +43,4 @@ Beyond its core functionality as an ARC Data Hub, it incorporates **CQC** within
 CQC also supports submissions to various endpoint repositories, provided the corresponding validation package and downstream submission application are available.
 This flexible system ensures that ARC submissions meet the necessary standards for different repositories, enabling seamless integration and data sharing across platforms.
 
-![cqc can be used to submit relevant parts of an ARC to endpoint repositories](/arc-website/ci-cd-cqc.png)
+![cqc can be used to submit relevant parts of an ARC to endpoint repositories](/ci-cd-cqc.png)

src/pages/details/arc-data-model.md

@@ -9,17 +9,17 @@ tags: ["RO-Crate", "FAIR Digital Object", "JSON-LD"]
 
 ARC is an implementation of a FAIR Digital Object (FDO). ARC utilizes RO-Crate with Schema.org and Bioschemas objects as its foundation, and further enhancing it with additional metadata and structure. An RO-Crate serves as a research object, composed of a collection of research elements and data, enabling detailed descriptions of these collections. Research elements in this context include samples, measurement data, and other research outputs.
 
-![ARC RO Crate](/arc-website/arc-ro-crate.png)
+![ARC RO Crate](/arc-ro-crate.png)
 
 ARC extends the basic RO-Crate concept by incorporating detailed descriptions of the processes that lead to the generation of data. This enhancement allows the data model to represent a complete process graph, encompassing experimental procedures, simulations, analyses, and the interconnections and provenance among them.
 In this model, research elements are the nodes of the process graph, while the connections between them, defined as lab processes, are represented by edges. To allow for unambiguous inclusion of data entities into the process graph, Data Fragment Selectors, defined by [W3C]({{W3C}}), can be used.
 Each process can be further specified and annotated with explanatory and descriptive metadata using lists of PropertyValues, enhancing its clarity and traceability.
 
-![ARC ISA CWL](/arc-website/ARC-isa-cwl-decorations.png)
+![ARC ISA CWL](/ARC-isa-cwl-decorations.png)
 
 To specialize ARC for biological data, the widely recognized ISA model (Investigation, Study, Assay) is employed, alongside the abstract Common Workflow Language (CWL) for workflows. The ISA model and CWL provide additional layers of metadata and structure, allowing for more precise definitions of processes and data. Dataset objects within ARC can implement either ISA or CWL interface object definitions, ensuring compatibility and standardization across various biological datasets and workflows.
 
-![ARC RO Crate Profiles](/arc-website/arc-ro-crate-profiles.png)
+![ARC RO Crate Profiles](/arc-ro-crate-profiles.png)
 
 This approach elevates ARC from merely documenting research objects to providing a full, interconnected representation of the research process, from data generation to analysis, making it a powerful tool for tracing and reproducing scientific investigations.
 

src/pages/details/arc-representation.md

@@ -8,15 +8,15 @@ image:
 tags: ["RO-Crate", "FAIR Digital Object", "JSON-LD", "XLSX", "CWL"]
 ---
 
-The ARC is a flexible and comprehensive research data management (RDM) framework. It not only facilitates FAIR (Findable, Accessible, Interoperable, Reusable) documentation, storage, and collaboration but also empowers researchers to create their own [FAIR Digital Objects (FDOs)](/arc-website/details/arc-fdo) using a broad set of tools and services, all without being locked into a specific platform or toolset.
+The ARC is a flexible and comprehensive research data management (RDM) framework. It not only facilitates FAIR (Findable, Accessible, Interoperable, Reusable) documentation, storage, and collaboration but also empowers researchers to create their own [FAIR Digital Objects (FDOs)](/details/arc-fdo) using a broad set of tools and services, all without being locked into a specific platform or toolset.
 
 The ARC data model encompasses the necessary entities to document the full research cycle effectively. However, this model can be expressed in various formats, each offering distinct advantages. These different representations enhance accessibility and usability for a variety of users and workflows. Currently, two ARC representations have been specified, and while the unified **ARC Scaffold** is highly encouraged to maintain consistency across user perspectives, domain-specific adaptations are also possible to suit particular needs.
 
 ### Two Sides of the Same Coin
 
 The two main ARC representations are the **ARC RO-Crate** and the **ARC Scaffold**. Both adhere to the same underlying data model, making conversion between them straightforward and requiring no complex mapping. This seamless transition ensures frictionless collaboration, even between users who prefer different representations. Think of the ARC RO-Crate as a more machine-friendly, compiled version of the ARC Scaffold, which is geared toward human input and interaction.
 
-![ARC RO Crate](/arc-website/ro-crate-vs-scaffold.png)
+![ARC RO Crate](/ro-crate-vs-scaffold.png)
 
 ### ARC RO-Crate
 

src/pages/details/developer-toolstack.md

@@ -27,7 +27,7 @@ Depending on your programming language, ARCtrl can be found via different packag
 
 ### Handling representations
 
-The ARCtrl library supports a wide set of base operations for working with different [ARC representations](/arc-website/details/arc-representation). ARCtrl can parse ISA metadata files in XLSX format and CWL files in YAML format, resulting in a full parsing of the ARC Scaffold representation. On the other hand, the full scaffold data model can also be transformed to the RO-Crate metadata model and parsed as such. Through this, transition between the two representations is merely a few function calls away. In addition to the RO-Crate and the Scaffold representation, ARCtrl also supports parsing the experimental metadata to ISA-JSON, providing an additional entry and exit point.
+The ARCtrl library supports a wide set of base operations for working with different [ARC representations](/details/arc-representation). ARCtrl can parse ISA metadata files in XLSX format and CWL files in YAML format, resulting in a full parsing of the ARC Scaffold representation. On the other hand, the full scaffold data model can also be transformed to the RO-Crate metadata model and parsed as such. Through this, transition between the two representations is merely a few function calls away. In addition to the RO-Crate and the Scaffold representation, ARCtrl also supports parsing the experimental metadata to ISA-JSON, providing an additional entry and exit point.
 
 ### ARC manipulation
 
@@ -43,7 +43,7 @@ The library guarantees to behave consistently across the different programming e
 
 For this, the source code is written in FSharp. From there it is being compiled to Common Intermediate Language for usage in .NET, and transpiled to Javascript and Python source code using the [Fable compiler](https://github.com/fable-compiler/Fable). As file access can be vastly diverging between different frameworks, especially for javascript, a contract layer was established. This way, every implementation of ARCtrl can decide for itself, how to handle file-system access.
 
-![ARCtrl layers](/arc-website/ARCtrl-layers.png)
+![ARCtrl layers](/ARCtrl-layers.png)
 
 To test the functioning of all of this, especially the cross-compatibility, a comprehensive set of well over 1000 tests was established, which is also being transpiled and run in javascript and python.