Merge pull request #69 from nfdi4plants/small-edits

small typos / styling

src/pages/details/data-management-principle.md

@@ -2,61 +2,62 @@
 layout: ../../layouts/MarkdownLayout.astro
 title: 'Data Management Principle '
 pubDate: 2024-09-13
-description: 'A short summary for ARC related tools and services.'
+description: 'An introduction to the ARC data management principle.'
 author: 'Timo Mühlhaus'
 image:
     url: 'https://docs.astro.build/assets/rose.webp'
     alt: 'The Astro logo on a dark background with a pink glow.'
 tags: ["documentation", "services", "community"]
 ---
-### Data Management Principle
 
-The ARC is a comprehensive framework designed for organizing, documenting, and managing research data. 
-It serves as a focal point for collaboration, data exchange, and the creation of FAIR (Findable, Accessible, Interoperable, Reusable) Digital Objects across various research domains. 
+## Data Management Principle
+
+The ARC is a comprehensive framework designed for organizing, documenting, and managing research data.
+It serves as a focal point for collaboration, data exchange, and the creation of FAIR (Findable, Accessible, Interoperable, Reusable) Digital Objects across various research domains.
 By adopting the ARC, researchers can seamlessly engage with the evolving Research Data Management (RDM) ecosystem, without facing barriers or limitations.
 
 ![ARC enables researchers](/arc-enables-researcher.png)
 
-### Core Features and Benefits
+## Core Features and Benefits
 
-ARC implements widely accepted RDM standards, ensuring compatibility with technology-specific endpoints, domain-specific databases, search engines, and publication platforms with minimal extra effort. 
+ARC implements widely accepted RDM standards, ensuring compatibility with technology-specific endpoints, domain-specific databases, search engines, and publication platforms with minimal extra effort.
 Its practical approach blends efficient data organization and documentation, making it easier to publish research data that can be transparently referenced in one or more accompanying journal publications.
 
 ![Classical publication will reference FDOs as data publications](/data-publication-referenced.png)
 
-The fundamental principle of ARC is to be **FAIR by design**. 
+The fundamental principle of ARC is to be **FAIR by design**.
 It promotes a continuous increase in FAIRness through incremental updates and community contributions, making it an evolving system that can grow with the needs of researchers.
 
-ARC’s collaborative nature, combined with its project management features and extensive software support, fosters effective communication and distributed contributions within research teams. 
+ARC’s collaborative nature, combined with its project management features and extensive software support, fosters effective communication and distributed contributions within research teams.
 This makes ARC not only a data management tool but also a powerful platform for collaborative research.
 
-### Documentation and Organization
+## Documentation and Organization
 
-The ARC follows a process-centered documentation approach, focusing on how data is generated. 
-This approach allows for an implicit identity description, saving time by utilizing one overarching concept instead of multiple, technology-specific or experiment-specific systems. 
+The ARC follows a process-centered documentation approach, focusing on how data is generated.
+This approach allows for an implicit identity description, saving time by utilizing one overarching concept instead of multiple, technology-specific or experiment-specific systems.
 All data and metadata can be documented using simple tables, a format familiar to most researchers due to its frequent use in daily activities.
 
 The organizational structure of ARC goes beyond making data findable and accessible; it ensures **immediate machine actionability and AI-readiness**, essential for modern research environments. 
 The flexible framework also allows for customization, enabling researchers to adapt or extend the core structure to meet their individual needs.
 
-### Separation for Reusability
+## Separation for Reusability
 
-One of ARC’s key principles is the **separation of (meta)data for reusability**. 
-By treating metadata as distinct, reusable entities, the framework makes it easy to aggregate data later while avoiding the difficulties of separating intertwined information. 
+One of ARC’s key principles is the **separation of (meta)data for reusability**.
+By treating metadata as distinct, reusable entities, the framework makes it easy to aggregate data later while avoiding the difficulties of separating intertwined information.
 This approach ensures a high level of clarity and organization, supporting long-term reuse and integration across multiple research projects.
 
 ![Descriptor files provide context for the data files](/everything-file.png)
 
-In the user-facing representation, ARC allows everything to be stored as individual files, making it possible to layer metadata and data incrementally. 
+In the user-facing representation, ARC allows everything to be stored as individual files, making it possible to layer metadata and data incrementally.
 Metadata files attached to data can, in turn, be decorated and enriched with further metadata, allowing for continuous improvement and contextualization.
 
-### Getting Started
+## Getting Started
 
 To facilitate adoption, tools like **ARCitect** offer a user-friendly interface for creating and managing an ARC. 
 ARCitect streamlines organization and documentation with an intuitive interface, and video tutorials provide step-by-step guidance on how to get started with modern research documentation using ARC. 
 While these tools make the process easier, ARC is designed to avoid any tool lock-in. Everything can be done manually or using alternative tools available within the ARC community.
 
-### Open Source and Community-Driven
+## Open Source and Community-Driven
 
 ARC is an **open-source**, community-driven initiative that invites researchers to contribute and shape the future of RDM according to the evolving needs of the research community. 
 This openness ensures that the framework remains adaptable, relevant, and focused on solving real-world challenges in research data management.

src/pages/details/documentation-principle.md

@@ -2,7 +2,7 @@
 layout: ../../layouts/MarkdownLayout.astro
 title: 'Documentation and Annotation'
 pubDate: 2024-09-13
-description: 'A introduction to the ARC documentation and annotation principles.'
+description: 'An introduction to the ARC documentation and annotation principles.'
 author: 'Timo Mühlhaus'
 image:
     url: 'https://docs.astro.build/assets/rose.webp'

src/pages/details/exchange-and-publication.md

@@ -13,17 +13,17 @@ tags: ["community", "exchange", "publication", "collaboration"]
 ### ARCs for Data Publication, Exchange, and Collaboration
 
 The ARC framework provides an efficient system for managing research data publication, exchange, and collaboration, supporting researchers in adhering to **FAIR principles** (Findable, Accessible, Interoperable, and Reusable). 
-In this context, it’s important to clarify that **FAIR** does not necessarily mean open access. 
+In this context, it is important to clarify that **FAIR** does not necessarily mean open access. 
 Accessibility in FAIR refers to the technical ability to access data, which can still be password-protected or restricted, as long as standard protocols are used.
 
-### Data Publication and Its Importance
+### Data Publication and its Importance
 
-The coomon vision in RDM is that, data publication should be a standard component of journal publications, with each journal article referencing the corresponding data publication. This practice offers several advantages to researchers, including:
+The common vision in RDM is that, data publication should be a standard component of journal publications, with each journal article referencing the corresponding data publication. This practice offers several advantages to researchers, including:
 
 - **Increased citations**: Data that is openly shared and referenced increases visibility and is more likely to be cited.
 - **Faster publication process**: Well-documented and published data can streamline the review process, making it easier to evaluate research.
 - **Enhanced collaboration**: Open science practices, including data sharing, foster transparency and collaboration across research fields.
-- **Publishable negative results**: Data publication enables the sharing of negative or null results, which are often overlooked in traditional journals but are valuable to the scientific community.
+- **Publishable negative results**: Data publication enables the sharing of negative or null results, which are often overlooked in traditional journals, but are valuable to the scientific community.
 - **Reduced redundant efforts**: Publishing data prevents duplication of experiments, saving time and resources.
 
 Data publications are ideally published as **ARC Fair Digital Objects**, using platforms that generate **DOIs** (Digital Object Identifiers) to permanently connect the data to a specific citation. 
@@ -34,7 +34,7 @@ One example is the **Invenio** platform, which is used by NFDI4Plants’ **DataP
 
 ### Data Publication and Quality
 
-Data publication platforms like ARC Data Hub can incorporate **automatic validation** processes, indicated by different quality badges, to ensure the quality of published data. 
+Data publication platforms like **ARC Data Hub** can incorporate **automatic validation** processes, indicated by different quality badges, to ensure the quality of published data. 
 This simplifies the process for researchers and reviewers, reducing the workload while improving trust in the data. 
 
 Moreover, when an ARC-powered data hub is connected to platforms like Invenio, it enables a **community-driven peer review process**, much like traditional journal reviews, to ensure that the published data meets the necessary standards. 
@@ -50,7 +50,7 @@ The ARC framework is well-suited to support collaborative research by providing
 - **Collaborative research platform**: ARCs provide a solid foundation for building collaborative research platforms, enabling seamless sharing of data between researchers. 
 The ability to separate and merge different components of the ARC ensures that collaboration remains smooth and conflict-free.
 
-![ARC collaborative plattform](/collaboration-arc-data-hub.png)
+![ARC collaborative platform](/collaboration-arc-data-hub.png)
 
 By using ARCs, researchers can easily collaborate on experiments, share data, and contribute to larger research projects, all while maintaining high standards of organization, documentation, and FAIRness. 
 The ARC framework offers a robust and flexible tool for improving data management, quality, and collaboration in the modern scientific landscape.