Merge pull request #412 from dgarijo/main

Synchronizing projects and some reports training materials

Author: dgarijo

pages/rs_quality/fair_rs.md pages/fair_rs.mdpages/rs_quality/fair_rs.md renamed to pages/fair_rs.md

@@ -8,8 +8,7 @@ page_id: fair_rs
 
 FAIR stands for Findable, Accessible, Interoperable, and Reusable and comprises a set of principles designed to
 increase the visibility and usefulness of your research to others.
-The FAIR data principles, first published [in 2016][fair-data-principles], are widely known and applied today.
-Similar [FAIR principles for software][fair-principles-research-software] have now been defined too. In general, they mean:
+The FAIR data principles, first published in 2016 [^1], are widely known and applied today, including scientific workflows [^2], or [machine learning projects][fair4ml]. Similar FAIR principles for software [^3][^4] have now been defined too. In general, they mean:
 
 - **Findable** - software and its associated metadata must be easy to discover by humans and machines.
 - **Accessible** - in order to reuse software, the software and its metadata must be retrievable by standard protocols, free and legally usable.
@@ -168,8 +167,10 @@ Here are some tools that can check your software and provide an assessment of it
 
 - [FAIRsoft evaluator][fair-rs-evaluator]
 - [FAIR software test][fair-rs-test]
-- [FAIR Software Checklist][fair-rs-checklist] - self-assessment tool developed by the Australian Research Data Commons (ARDC) and the Netherlands eScience Center (NeSC)
+- [FAIR Software Checklist][fair-rs-checklist] - self-assessment tool developed by the Australian Research Data Commons (ARDC) and the Netherlands eScience Center
 - [`How FAIR is your software` - command line tool to evaluate a software repository's compliance with the FAIR principles][howfairis]
+- [CODECHECK][codecheck] - An approach for independent execution of computations underlying research articles.
+
 
 ### Summary
 
@@ -193,26 +194,41 @@ The table below provides a summary of how different tools and practices help wit
 | Unique persistent identifiers                                                                        | x        | x          |               |          |
 
 
+## Training materials
+- The [FAIR Cookbook][fair-cookbook] contains general reusable recipes for FAIR assessment.
+- [10 easy things to make your research software FAIR](https://doi.org/10.5281/zenodo.3409968)
+- Common metrics for Research Software [^5] that may used to assess each of the FAIR4RS principles.
+- [A cookie software project template with FAIR metadata](https://github.com/Materials-Data-Science-and-Informatics/fair-python-cookiecutter)
+- [Carpentries course on tools and practices for FAIR Research Software](https://carpentries-incubator.github.io/fair-research-software/)
 
-[fair-principles-research-software]: https://www.nature.com/articles/s41597-022-01710-x
-[fair-data-principles]: https://www.nature.com/articles/sdata201618
-[zenodo]: https://zenodo.org/
-[software-registries]: https://github.com/NLeSC/awesome-research-software-registries
-[github]: https://github.com
+
+## References
+[^1]: Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, Blomberg N, Boiten JW, da Silva Santos LB, Bourne PE, Bouwman J. The FAIR Guiding Principles for scientific data management and stewardship. Scientific data. 2016 Mar 15;3(1):1-9. [https://doi.org/10.1038/sdata.2016.18](https://doi.org/10.1038/sdata.2016.18)
+[^2]: Wilkinson SR, Aloqalaa M, Belhajjame K, Crusoe MR, de Paula Kinoshita B, Gadelha L, Garijo D, Gustafsson OJ, Juty N, Kanwal S, Khan FZ. Applying the FAIR principles to Computational Workflows. Scientific Data. 2025 Feb 24;12(1):328. [https://doi.org/10.1038/s41597-025-04451-9](https://doi.org/10.1038/s41597-025-04451-9)
+[^3]: Barker M, Chue Hong NP, Katz DS, Lamprecht AL, Martinez-Ortiz C, Psomopoulos F, Harrow J, Castro LJ, Gruenpeter M, Martinez PA, Honeyman T. Introducing the FAIR Principles for research software. Scientific Data. 2022 Oct 14;9(1):622. [https://doi.org/10.1038/s41597-022-01710-x](https://doi.org/10.1038/s41597-022-01710-x)
+[^4]: Chue Hong, N. P., Katz, D. S., Barker, M., Lamprecht, A.-L., Martinez, C., Psomopoulos, F. E., Harrow, J., Castro, L. J., Gruenpeter, M., Martinez, P. A., Honeyman, T., Struck, A., Lee, A., Loewe, A., van Werkhoven, B., Jones, C., Garijo, D., Plomp, E., Genova, F., … RDA FAIR4RS WG. (2022). FAIR Principles for Research Software (FAIR4RS Principles) (1.0). Zenodo. [https://doi.org/10.15497/RDA00068](https://doi.org/10.15497/RDA00068)
+[^5]: Chue Hong, N., Breitmoser, E., Antonioletti, M., Davidson, J., Garijo, D., Gonzalez-Beltran, A., Gruenpeter, M., Huber, R., Jonquet, C., Priddy, M., Shepeherdson, J., Verburg, M., & Wood, C. (2025). D5.2 - Metrics for automated FAIR software assessment in a disciplinary context (1.1). Zenodo. [https://doi.org/10.5281/zenodo.15535629](https://doi.org/10.5281/zenodo.15535629)
+
+[awesome-rs-registries]: https://github.com/NLeSC/awesome-research-software-registries
 [biotools]: https://bio.tools
-[pypi]: https://pypi.org/
+[cff]: https://citation-file-format.github.io/
+[choosealicense]: https://choosealicense.com/
+[codecheck]: https://codecheck.org.uk/project/
+[codemeta]: (https://codemeta.github.io/)
 [cran]: https://cran.r-project.org/web/packages/
-[gitlab]: https://about.gitlab.com/
-[awesome-rs-registries]: https://github.com/NLeSC/awesome-research-software-registries
+[fair-cookbook]: https://faircookbook.elixir-europe.org/content/home.html
 [fair-rs-evaluator]: https://openebench.bsc.es/observatory/Evaluation
 [fair-rs-test]: https://github.com/marioa/fair-test?tab=readme-ov-file
 [fair-rs-checklist]: https://fairsoftwarechecklist.net
-[codemeta]: (https://codemeta.github.io/)
-[rsmd-g1]: https://fair-impact.github.io/RSMD-guidelines/1.General/
-[software-heritage]: https://www.softwareheritage.org/
-[swhid]: https://docs.softwareheritage.org/devel/swh-model/persistent-identifiers.html
+[fair4ml]: https://www.rd-alliance.org/groups/fair-machine-learning-fair4ml-ig/activity/
 [figshare]: https://figshare.com/
+[github]: https://github.com
+[gitlab]: https://about.gitlab.com/
 [howfairis]: https://github.com/fair-software/howfairis/
-[cff]: https://citation-file-format.github.io/
 [opensource-licence-guide]: https://opensource.guide/legal/#which-open-source-license-is-appropriate-for-my-project
-[choosealicense]: https://choosealicense.com/
+[rsmd-g1]: https://fair-impact.github.io/RSMD-guidelines/1.General/
+[swhid]: https://docs.softwareheritage.org/devel/swh-model/persistent-identifiers.html
+[pypi]: https://pypi.org/
+[software-heritage]: https://www.softwareheritage.org/
+[software-registries]: https://github.com/NLeSC/awesome-research-software-registries
+[zenodo]: https://zenodo.org/

pages/research_clusters_and_infrastructures/envri.md

@@ -8,5 +8,8 @@ European Environmental Research Infrastructures (ENVRIs) at the ESFRI level serv
 
 ## Services
 ### ENVRI-HUB
-The ENVRI-Hub is designed as a federated system to harmonise subdomain- or RI-specific access platforms and offers a user-centred platform that provides seamless access to environmental data and services across multiple European Research Infrastructures (RIs), addressing key challenges in data discovery, access, composition, processing, and usability. Its modular, service-oriented architecture integrates data catalogues, knowledge bases, analytical tools, and training resources, enabling interdisciplinary research and informed policy-making. To enhance ENVRI-Hub to the next level, ENVRI-Hub Next provides improved access to environmental data and services by incorporating next-generation digital solutions and expanding its user base.
+The [ENVRI-Hub](https://envri-hub.envri.eu/) is designed as a federated system to harmonise subdomain- or RI-specific access platforms and offers a user-centred platform that provides seamless access to environmental data and services across multiple European Research Infrastructures (RIs), addressing key challenges in data discovery, access, composition, processing, and usability. Its modular, service-oriented architecture integrates data catalogues, knowledge bases, analytical tools, and training resources, enabling interdisciplinary research and informed policy-making. To enhance ENVRI-Hub to the next level, ENVRI-Hub Next provides improved access to environmental data and services by incorporating next-generation digital solutions and expanding its user base.
+
+### ENVRI-KB
+The [ENVRI-KB](https://search.envri.eu/) is a knowledge base designed to store and search for all the information available in the ENVRI cluster.
 

pages/research_clusters_and_infrastructures/ls-ri.md

@@ -6,5 +6,9 @@ type: research_cluster_or_infrastructure
 
 [European Life Science Research Infrastructures (LS-RI)](https://lifescience-ri.eu/home.html) such as [ELIXIR](https://elixir-europe.org/) are serving excellent life sciences research in Europe by providing needed access to 
 world-class facilities, samples, instruments, services, and data. The European LS-RIs were established to overcome a technology gap and to allow access 
-to much-needed technologies in modern research approaches. They have the mission to support cutting-edge science by offering access to the latest technologies, 
-comprehensive resource collections and technical expertise. 
+to much-needed technologies in modern research approaches. They have the mission to support cutting-edge science by offering access to the latest technologies, comprehensive resource collections and technical expertise. An example is the [ELIXIR STEERS](https://elixir-europe.org/about-us/how-funded/eu-projects/steers) project, which aims to provide software and workflows to life scientists, maximising productivity in research, and minimising consequent energy usage.
+
+## Services
+
+### Training catalogue
+The [TeSS Life Sciences Training Catalogue](https://tess.elixir-europe.org/) is a platform that was developed to provide a one-stop shop for trainers and trainees to discover online information and content, including training materials, events and interactive tutorials. While its scope is wider than research software, training materials on the best practices mentioned in the RSQKit may also be found.

pages/research_software/quality.md

@@ -40,11 +40,16 @@ A truly high-quality, reproducible research software package will typically sati
 So, FAIR - the “openness & reusability” slice of software quality - is essential for reproducibility, but most impactful 
 when combined with all the other [quality practices](rs_quality) like testing, version control, and robust design. 
 
-Read in more detail what [the FAIR principles](fair_rs) encompass.
+
+Read in more detail what [the FAIR principles for research software](/fair_rs) encompass.
 
 ## Formal Quality Dimensions & Indicators
 
-The project is working on formally defining a number of research software quality [dimensions](https://everse.software/indicators/website/dimensions.html)
-and their associated [indicators](https://everse.software/indicators/website/indicators.html) (which are to be used to assess the quality of software).
+The project is working on formally defining a number of research software quality [dimensions](https://w3id.org/everse/i/dimensions/)
+and their associated [indicators](https://w3id.org/everse/i/indicators) (which are to be used to assess the quality of software), based on existing work in the literature [^1] and [ISO standards for software and data quality](https://iso25000.com/index.php/en/).
+
+## References
+
+[^1] David, M., Colom, M., Garijo, D., Castro, L. J., Louvet, V., Ronchieri, E., Torquati, M., del Caño, L., Cerlane, L., Van den Bossche, M., Campos, I., & Di Cosmo, R. (2024). Ensure Software Quality (1.0.0). Zenodo. [https://doi.org/10.5281/zenodo.10723608](https://doi.org/10.5281/zenodo.10723608)
 
 [fair-rs]: https://www.nature.com/articles/s41597-022-01710-x

pages/rs_quality.md

@@ -15,11 +15,11 @@ and their sustainability.
 
 ## Quality Dimensions & Indicators
 
-EVERSE project is working to formally define a number of [research software quality dimensions](https://everse.software/indicators/website/dimensions.html) 
-along with a [formal schema](https://github.com/EVERSE-ResearchSoftware/schemas/tree/main) to be used in machine readable metadata 
+EVERSE project is working to formally define a number of [research software quality dimensions](https://w3id.org/everse/i/dimensions) 
+along with a [formal schema](https://w3id.org/everse/rsqd) to be used in machine readable metadata 
 embedded in various resources.
 
-Each of the quality dimensions will be an umbrella for a number of [quality indicators](https://everse.software/indicators/website/indicators.html), 
+Each of the quality dimensions will be an umbrella for a number of [quality indicators](https://w3id.org/everse/i/indicators), 
 representing a specific software quality aspect that can be measured.
 
 Current research software quality dimensions are described below. This is still work in progress - we expect indicators 

pages/your_tasks/ci_cd.md

@@ -79,6 +79,7 @@ also provide CI/CD processes and services built around code repositories - e.g.
   - {% tool "kubernetes" %} - for orchestration, enabling deployment, scaling and management of containerised applications.
 - Monitoring - tools like Prometheus, Grafana, and New Relic are used for real-time monitoring in production to ensure system health.
 - Infrastructure as Code (IaC) - tools like {% tool "terraform" %}, {% tool "vagrant" %} or {% tool "ansible" %} automate infrastructure provisioning and configuration, ensuring consistency across environments.
+ 
 
 [task_automation_github_actions]: ./task_automation_github_actions
 [task_automation_gitlab_ci_cd]: ./task_automation_gitlab_ci_cd

pages/your_tasks/documenting_software.md

@@ -138,6 +138,7 @@ while fostering respect among developers.
 - List of all authors and contributors to the software.
 - Pointers to various other documentation about your software.
 
+
 ## References
 1. [Lee B. D., Ten Simple Rules for documenting scientific software](https://doi.org/10.1371/journal.pcbi.1006561)
 2. [Wilson, G., Aruliah, D. A., Brown, C. T., Chue Hong, N. P., Davis, M., Guy, R. T., Haddock, S. H., Huff, K. D., Mitchell, I. M., Plumbley, M. D., Waugh, B., White, E. P., & Wilson, P.Best Practices for Scientific Computing](https://doi.org/10.1371/journal.pbio.1001745)

pages/your_tasks/languages_tools_infrastructures.md

@@ -119,5 +119,17 @@ Some interesting templates to consider for research software:
 
 Of course, the RSQkit itself also uses templates to create pages, like [the one used for this task page](https://github.com/EVERSE-ResearchSoftware/RSQKit/blob/main/pages/your_tasks/TEMPLATE_your_tasks.md)!
 
+## Training materials
+Below you can find introductory materials to the most commonly used programming languages used in Research Software:
+- Python: [Research Software Engineering with Python](https://alan-turing-institute.github.io/rse-course/html/index.html), [programming with Python](https://swcarpentry.github.io/python-novice-inflammation/index.html), [leveling up your Python](https://henryiii.github.io/level-up-your-python/notebooks/0%20Intro.html), [Python introduction for libraries](https://librarycarpentry.org/lc-python-intro/), [Python traps and pitfalls](https://gitlab.in2p3.fr/informatique-des-deux-infinis/pheniics/python-traps)
+- R: [Introduction to R](https://carpentries-lab.github.io/metagenomics-R/), [Software Carpentry: R for Reproducible Scientific Analysis](), [Software Carpentry: Programming with R](https://swcarpentry.github.io/r-novice-inflammation/), [Getting Used to R, RStudio, and R Markdown](https://rbasics.netlify.app/), [Modern Dive into R and the Tidyverse](https://moderndive.netlify.app/)
+- Julia: [Introduction to Julia](https://enccs.github.io/julia-intro/), [Julia for high-performance scientific computing](https://enccs.github.io/julia-for-hpc/), [Julia for high-performance data analytics](https://enccs.github.io/julia-for-hpda/), [Programming with Julia](https://carpentries-incubator.github.io/julia-novice/)
+- CMake: [hands-on workshop](https://enccs.github.io/cmake-workshop/)
+- Matlab: [Software Carpentry: Programming with MATLAB](https://swcarpentry.github.io/matlab-novice-inflammation/)
+- C++: [Modern Scientific C++](https://github.com/chavid/ModernScientificCpp)
+
+
+
+
 ## Credit
 The first version of this page was inspired by content in and discussions on the [Netherlands eScience Center Guide to software development](https://guide.esciencecenter.nl).

pages/your_tasks/licensing_software.md

@@ -151,6 +151,7 @@ In addition to the licenses above, Creative Commons also offers [CC0][cc0] - a p
 * {% tool "choosealicense" %} is a great tool to help you choose a license that is appropriate for your needs.
 * {% tool "spdx" %} (System Package Data Exchange - open standard project) provides a long list of [commonly used licenses][spdx-licences].
 * Check the [OpenSource guide](https://opensource.guide/legal/#which-open-source-license-is-appropriate-for-my-project) for guidelines on changing and editing licenses.
+* The [Software Licensing guidelines from CodeRefinery](https://coderefinery.github.io/social-coding/software-licensing/) provide additional insight
 
 ## How do I add a license to my code repository?
 

pages/your_tasks/packaging_releasing_software.md

@@ -153,6 +153,13 @@ This document specifically covers publishing Python packages to **{% tool "pypi"
       pip install --index-url https://gitlab.com/api/v4/projects/YOUR_PROJECT_ID/packages/pypi/simple my_python_package
       ``` 
 
+## Training materials
+
+- [How to package a Python project](https://py-pkgs.org/03-how-to-package-a-python) 
+- [Python Packaging (Carpentries)](https://carpentries-incubator.github.io/python_packaging/)
+- [Python 201 on Packaging](https://python-tutorial.dev/201/tutorial/packaging.html#packaging)
+- [Managing Academic Software development: Release management](https://southampton-rsg.github.io/swc-project-novice/04-features/index.html)
+
 ## References 
 
 * [PyPI - The Python Package Index](https://pypi.org/)