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layout: ../../layouts/MarkdownLayout.astro | ||
title: 'Publication and Exchange' | ||
pubDate: 2024-09-22 | ||
description: 'An overview about data publication and collaboration' | ||
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: ["community", "exchange", "publication", "collaboration"] | ||
--- | ||
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### ARCs for Data Publication, Exchange, and Collaboration | ||
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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. | ||
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. | ||
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### Data Publication and Its Importance | ||
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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: | ||
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- **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. | ||
- **Reduced redundant efforts**: Publishing data prevents duplication of experiments, saving time and resources. | ||
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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. | ||
These platforms ensure that data is stored for the long term, providing stable access and referenceability. | ||
One example is the **Invenio** platform, which is used by NFDI4Plants’ **DataPLANT** and connected to the ARC-powered **PLANTdataHUB**. | ||
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![Data Publication using INVENIO](/data-publication-using-invenio.png) | ||
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### Data Publication and Quality | ||
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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. | ||
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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. | ||
This provides an additional layer of validation, making the data more reliable and easier to reference. | ||
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### ARCs for Collaboration | ||
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In modern research, collaboration is essential, often involving teams with diverse roles and expertise. | ||
The ARC framework is well-suited to support collaborative research by providing multiple features that make data management and exchange more efficient: | ||
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- **Layered information**: ARC’s "everything is a file" approach allows for easy layering of additional information, making it simple to append metadata, corrections, or new results as the research evolves. | ||
- **High separability**: The ARC’s natural branching structure reduces the likelihood of merge conflicts when multiple researchers contribute to the same project. This is particularly useful when collaborating across different teams or institutions. | ||
- **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. | ||
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![ARC collaborative plattform](/collaboration-arc-data-hub.png) | ||
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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. |