Merge pull request #42 from Brilator/suggestion-arc-representation

Suggestion arc representation

src/pages/details/arc-representation.md

@@ -5,14 +5,12 @@ pubDate: 2024-09-15
 description: 'A short description of the ARC representation.'
 author: 'Heinrich Lukas Weil'
 image:
-    url: 'https://docs.astro.build/assets/rose.webp'
-    alt: 'The Astro logo on a dark background with a pink glow.'
-tags: ["RO-Crate", "FAIR digital object","JSON-LD", XLSX, CWL]
+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) 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)](/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 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.
+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
 
@@ -27,8 +25,8 @@ The **ARC RO-Crate** is an extension of the RO-Crate framework. It follows the s
 ### ARC Scaffold
 
 The **ARC Scaffold** offers a file system-based representation of the ARC. Datasets are organized into folders, categorized by their type, and include accompanying metadata files. Experimental data and process descriptions are accompanied by metadata in tabular **XLSX** format, following the ISA-XLSX standard. Datasets containing workflows and run descriptions are paired with metadata in **YAML** format, adhering to the Common Workflow Language (CWL) specification. 
-This representation is designed for use by researchers, experimenters, and data stewards, as its folder-based structure and familiar **XLSX** metadata format align closely with traditional scientific documentation workflows. The ARC Scaffold is ideal for those involved in hands-on data management, offering an intuitive, human-readable approach to RDM while maintaining compliance with FAIR principles.
+This representation is designed for use by researchers, experimenters, and data stewards, as its folder-based structure and familiar **XLSX** metadata format align closely with traditional scientific documentation workflows. The ARC Scaffold is ideal for those involved in hands-on RDM, offering an intuitive, human-readable approach to RDM while maintaining compliance with FAIR principles.
 
 ### Flexibility for Different Use Cases
 
-ARC's versatility ensures that both experts and non-experts can benefit from a tailored approach to data management. Whether working with the highly structured, machine-friendly ARC RO-Crate or the more user-centered ARC Scaffold, the core data model remains consistent. This alignment enables seamless collaboration and data exchange across platforms, user preferences, and research domains.
+ARC's versatility ensures that both experts and non-experts can benefit from a tailored approach to RDM. Whether working with the highly structured, machine-friendly ARC RO-Crate or the more user-centered ARC Scaffold, the core data model remains consistent. This alignment enables seamless collaboration and data exchange across platforms, user preferences, and research domains.

src/pages/dictionary/fair.md

@@ -0,0 +1,17 @@
+---
+layout: ../../layouts/MarkdownLayout.astro
+title: 'FAIR Principles'
+pubDate: 2024-09-17
+description: 'Findable – Accessible - Interoperable - Reusable'
+author: Dominik Brilhaus
+tags: ["FAIR", "RDM"]
+keywords: ['fair', 'FAIR']
+url: 'fair'
+---
+
+Findable – Accessible – Interoperable - Reusable
+
+## Sources and further information
+
+- [The FAIR Guiding Principles for scientific data management and stewardship](https://doi.org/10.1038/sdata.2016.18)
+- [FAIR Principles at GO FAIR](https://www.go-fair.org/fair-principles/)