Merge pull request #322 from rsirvent/main

COMPSs use case small fixes

docs/pages/use_cases/COMPSs.md

@@ -1,7 +1,7 @@
 ---
 page_id: COMPSs
 title: COMPSs
-description: COMPSs recording of Workflow Provenance for governance and reproducibility of computational experiments
+description: The COMPSs programming model is able to record Workflow Provenance in RO-Crate format, for governance and reproducibility of computational experiments
 url: https://compss.bsc.es/
 image: COMPSs.png
 domains: [informatics] # should match item(s) in pages/domains
@@ -27,17 +27,17 @@ roles: [information_architect, researcher, software_developer] # should match it
 
 # COMPSs
 
-[![COMPSs logo](/assets/img/COMPSs.png)](https://compss.bsc.es/)
+[![COMPSs logo](../../assets/img/COMPSs.png)](https://compss.bsc.es/)
 
-[COMPSs](https://compss.bsc.es/) COMP Superscalar (COMPSs) is a task-based programming model which aims to ease the development of applications for distributed infrastructures, such as large High-Performance Clusters (HPC), Clouds and Container managed clusters. PyCOMPSs is the Python binding of COMPSs.
+COMP Superscalar ([COMPSs](https://compss.bsc.es/)) is a task-based programming model which aims to ease the development of applications for distributed infrastructures, such as large High-Performance Clusters (HPC), Clouds and Container managed clusters. PyCOMPSs is the Python binding of COMPSs.
 
 COMPSs provides a programming interface for the development of the applications in Python/Java/C/C++, a runtime system that exploits the inherent parallelism of applications at execution time, and a rich ecosystem for the operation monitoring, performance evaluation and integration with Jupyter/Jupyterlab.
 
 The COMPSs runtime includes the capacity of automatically recording details of the application’s execution as metadata, also known as [Workflow Provenance](https://compss-doc.readthedocs.io/en/stable/Sections/05_Tools/04_Workflow_Provenance.html). The metadata is recorded in RO-Crate format, following [Workflow RO-Crate](https://w3id.org/workflowhub/workflow-ro-crate/1.0) and [Workflow Run Crate](https://w3id.org/ro/wfrun/workflow/0.4) profiles. With workflow provenance, you are able to share not only your workflow application (i.e. the source code) but also your workflow run (i.e. the datasets used as inputs, and the outputs generated as results). 
 
 Provenance information can be useful for a number of things, including Governance, Reproducibility, Replicability, Traceability, or Knowledge Extraction, among others. In our case, we have initially targeted workflow provenance recording to enable users to publish research results obtained with COMPSs as artifacts that can be cited in scientific publications with their corresponding DOI, by using [WorkflowHub](https://workflowhub.eu/).
 
-![COMPSs with RO-Crate](/assets/img/COMPSs-screenshot.png)
+![COMPSs with RO-Crate](../../assets/img/COMPSs-screenshot.png)
 
 ## Examples of COMPSs RO-Crates
 
@@ -60,3 +60,9 @@ _IEEE/ACM Workshop on Workflows in Support of Large-Scale Science (WORKS)_ (1-9)
 <https://doi.org/10.1109/WORKS56498.2022.00006>  
 [[preprint](https://upcommons.upc.edu/handle/2117/384589)]
 
+Leo, S., Crusoe, M. R., Rodríguez-Navas, L., Sirvent, R., Kanitz, A., De Geest, P., ... & Soiland-Reyes, S. (2023):
+** Recording provenance of workflow runs with RO-Crate**.
+_arXiv preprint arXiv:2312.07852._
+<https://doi.org/10.48550/arXiv.2312.07852>  
+
+