RSQkit Contentathon: Collaborative Development and Integration of Research Software Quality Resources (software sustainability)

• Giacomo Peru (University of Edinburgh)

Room: SR A+B The Research Software Quality toolkit (RSQkit, https://everse.software/RSQKit/) is a knowledge hub developed within the EVERSE project (https://everse.software/) that aims to become a permanent, community-driven resource for research software quality expertise. This interactive workshop provides hands-on experience with collaborative content development, where participants will have a chance to contribute their expert knowledge and will be given recognition for their contribution. Through guided exercises, participants will experience the complete contribution cycle - from content creation through peer review to proper attribution of their work. Contributions will be formally recognized and credited, ensuring participants receive acknowledgment for their expertise and input. Attendees will work in small groups to develop and refine content covering key aspects of research software quality, including: - Technical best practices - FAIR principles - Sustainability guidelines - Software management approaches - Metadata standards The workshop focuses on enhancing research software quality through collaborative knowledge sharing, providing participants with practical experience in developing, reviewing, and integrating community-driven content. Key Details: - Duration: 2 hours - Location: Karlsruhe Institute of Technology (KIT) - Start Time: 10:00 AM Expected Outcomes: - Practical contributions to the RSQkit - Experience in collaborative documentation development - Formal recognition of individual contributions

HPC Carpentry Community Meetup (high-performance computing (HPC))

• Toby Hodges (The Carpentries)
• Marc-Andre Hermanns (RWTH Aachen University)

Room: Seminarroom 006 This meet-up is for anyone teaching HPC skills, and anyone who is interested in community-led training. [HPC Carpentry](https://www.hpc-carpentry.org/) is an open source community of RSEs, facility operators, developers, and others, who want to empower researchers through better, more inclusive training in HPC skills. The project is currently in incubation to join [The Carpentries](https://carpentries.org/) as a new lesson program. The HPC Carpentry project's mission is to provide interactive, hands-on instructional material focused around HPC in an inclusive and accessible model, where feedback from learners and instructors is used to continuously improve the material and the learner experience. Open to newcomers, existing HPC Carpentry community members, and anyone else interested in the project, this event is an opportunity for people who want to increase HPC competencies. The goals of the session will include - Providing a welcoming space for existing instructors to connect and share their experience and perspectives, - Connecting with potential instructors and workshop hosts and providing them with more information about the project and how our training is delivered, and - Better informing project coordinators about the training needs, and opportunities where we can contribute, at institutions across Germany, to help guide the project going forward. No prior knowledge of or affiliation to HPC Carpentry or The Carpentries is needed to be able to participate in this session, but some experience of or insight into the teaching of high-performance computing, especially to novices, would be beneficial.

An introduction to Machine-actionable Software Management Plans (software management plans)

• Leyla Jael Castro (ZB MED Information Centre for Life Sciences)

Room: Seminarroom 104 The concept of software management plans (SMPs) is similar to Data management plans (DMPs) but focusing on the research software lifecycle aligned to the FAIR for research software (FAIR4RS). DMPs consist of a series of questions and answers to outline how data will be handled during and after a research project. Similarly, an SMP helps us outline some important elements to handle and share our research software, resulting in the production of more reproducible and reusable software. An SMP questionnaire covers research and technical information including, for instance, aspects about licenses, releases, and public availability. A machine-actionability layer can be added to SMPs turning them into maSMPs. This refers to a semantically structured description (i.e., metadata) of the research software and its lifecycle. The ELIXIR SMP, proposed by the Software Best Practices focus group in ELIXIR Europe, aims at a low barrier entrance so both research software engineers and researchers who code ban benefit from it. We have collaborated with them to add a machine-actionable layer based on schema.org, and thus compatible with Codemeta. We provide types and profiles (i.e., usage recommendations on top of schema.org and our own types) to describe SMP, including source code and releases. We have aligned our maSMP to the SMP created by the eScience Center in the Netherlands and the one created by the Max Planck Digital Libraries. We have also analyzed its compatibility wrt the Research Software Metadata guidelines proposed by EOSC. In this short tutorial, we will briefly introduce the FAIR4RS principles and discuss how they relate to software metadata. We will then show some sources of software metadata and practical steps to support FAIR4RS. Afterwards, we will introduce SMPs including differences wrt project planning and project management. We will then present our approach to maSMPs, including a practical approach to get the corresponding metadata. Resources - FAIR4RS https://doi.org/10.15497/RDA00068 and https://doi.org/10.1038/s41597-022-01710-x - ELIXIR SMP https://doi.org/10.37044/osf.io/k8znb - maSMP metadata schema https://doi.org/10.5281/zenodo.7806638 - maSMP profiles https://doi.org/10.5281/zenodo.10582120 - An example of maSMP in action https://doi.org/10.37044/osf.io/t94g8 - maSMP project pages https://zbmed-semtec.github.io/maSMPs/ Funding The first version of the maSMP was funded by the European Union’s Horizon 2020 Research and Innovation programme under grant agreement No 101017536, part of the Research Data Alliance and European Open Science Cloud Future call 2022. The alignment to the EOSC RSMD guidelines was part of the FAIR-Impact support action calls funded by the European Commission, grant “FAIR-IMPACT – Expanding FAIR Solutions across EOSC” number 101057344. The maSMP project is part of NFDI4DataScience consortium funded by the German Research Foundation (DFG), project number 460234259.

A short introduction to Nextflow: Bring your data science pipelines to the next level (computational reproducibility)

• Marie Lataretu
• Paul Wolk (Robert Koch-Institut)

Room: Seminarroom 006 Analysing data typically consists of several steps with dedicated tools, chained one after another. In theory, all this can be achieved with well-written scripts. However, workflow managers help developers increase the reproducibility of their pipelines and results by providing features for workflow and data provenance, portability, readability, and fast prototyping. Nextflow is a reproducible, versatile and powerful workflow management system designed to simplify the development and execution of data-driven computational pipelines. It is predominantly used in bioinformatics, but its flexibility makes it suitable for other scientific domains and data science. It’s designed to be environment-agnostic, meaning that workflows can be executed across a variety of computing platforms, including high performance clusters and cloud services, without modification. It comes with close integration with software containers (e.g., Docker, Singularity) and Conda and Spack environments. Nextflow has an active community, including nf-core: a community-driven movement that aims to establish best practices, tools, and guidelines for developing, testing, and curating Nextflow pipelines. The nf-test test framework enables you to test all components of your data science pipeline, from end-to-end testing of the entire pipeline to specific tests of processes or custom functions. In this workshop, we will briefly introduce Nextflow and valuable nf-core resources: We will cover the fundamental components of a Nextflow script and work on a small hands-on example workflow. Our goal is to lay the foundation with Nextflow, empowering you to optimize your pipeline development and enhance the efficiency and scalability of your scientific research. ---- Training material and prerequisites: - Bring your own laptop 😊 - Basic knowledge how to work on a terminal - It is highly recommended to use [Gitpod](https://training.nextflow.io/envsetup/01_setup/) - If this is not option for you, please checkout the [Environment Setup](https://training.nextflow.io/envsetup/02_local/) - Training material: [Hello Nexflow](https://training.nextflow.io/hello_nextflow/) ----

Aspects of Usability in RSE (RSE education)

• Leen Lambers (BTU Cottbus-Senftenberg)
• Jan Bernoth (Universität Potsdam)

Room: Seminarroom 006 Research software developers are usually very familiar with the functional requirements of the software they are developing, as it is often closely linked to their research discipline. Quality requirements are often less well understood due to a lack of background in computer science [1]. Usability is one of these quality requirements that may be critical for the research software to support its underlying research goal. The aim of this workshop is therefore to study and foster exchange on aspects of usability in RSE. These aspects may vary, e.g. from learnability over operability to inclusivity (see ISO/IEC 25010 for further aspects). To steer the discussion, we want to encourage the participants to bring their own projects, so we can work together to specifically answer the following questions:: Who are the users of the RSE project based on the research goal? Which aspects of usability play an important role in the RSE project for these users? What does each of these usability aspects require to be fulfilled in the RSE project? How do these usability aspects influence the research goal that the RSE project contributes to? Is the usability aspect currently fulfilled within the RSE project and why (or why not)? We conclude the discussion by summarizing which usability aspects are important in the selected RSE projects, and how research software engineers could be supported with practical software engineering methods to take these usability aspects into account. Also participants interested in aspects of usability that do not bring their own RSE project are welcome to join the discussion. Wiese, I.; Polato, I.; Pinto, G.: Naming the Pain in Developing Scientific Software. IEEE Software 4/37, pp. 75–82, 2020.

Hands-on semantic data management with LinkAhead: Increased data findability and reusability (research data management)

• Alexander Schlemmer (IndiScale GmbH, Göttingen)
• Florian Spreckelsen (IndiScale GmbH, Göttingen)

Room: Seminarroom 104 In this hands-on workshop, we introduce the open source software LinkAhead, which promotes agility in semantic data management: LinkAhead is a semantic research data management system, facilitating enhanced data findability and reusability through data embedding into context. Its flexible data model (the data structure can be changed without migration of existing data) allows to leverage existing standard ontologies, promoting transparency, interoperability and collaboration across diverse research domains. Data management is essential for the storing, searching, retrieving and analyzing of data sets along with their contextual connections, ensuring their usability for current and future users. Effective data management not only ensures the reuse of valuable data by current and future users but also enhances its discoverability ("Where can I find the training data for sensor X from setup Y?") and utility through contextual embedding ("What were the experimental settings for data collection in project P, and what were the associated challenges?"). Thus data management solutions like LinkAhead support preparing FAIR open data, enable data collaboration and knowledge exchange. This workshop consists of a short live demonstration of the LinkAhead Python client, and participants are encouraged to follow along on their own machines. A Jupyter notebook will be made available online before the session. Workshop participants (researchers, research software engineers) will learn these LinkAhead skills: - Understand, create and edit data models - Semantic queries, also for linked data sets - Add and retrieve data ## Recommended prerequisites for participation: **Basic Python knowledge** **Jupyter Notebook with these Python libraries:** pip install linkahead caosadvancedtools **Test beforehand with:** import linkahead linkahead.configure_connection( url="https://demo.indiscale.com", username="admin", password="caosdb", password_method="plain") linkahead.Info() This should output a short info string like this: "Connection to LinkAhead with 84 Records."

How to improve the visibility and added value of RSE(s) in NFDI (best practices for research software development)

• Jan Bernoth (Universität Potsdam)
• Bernd Flemisch (University of Stuttgart)
• Linnaea Söhn (Academy of Sciences and Literature | Mainz)
• Corinna Seiwerth (Friedrich-Alexander-Universität Erlangen-Nürnberg)
• Florian Thiery (CAA e.V.)
• Jan Linxweiler (Technische Universität Braunschweig)

Room: Audimax A Research Software Engineering is fundamental to the German National Research Data Infrastructure (NFDI). Following that, a "deRSE Arbeitskreis NFDI" serves as a connection point for RSEs in the NFDI inside deRSE e.V. Within the NFDI e.V., several "sections" are dealing with overarching topics, e.g., the "Sektion Common Infrastructures" with its working groups on Data Integration (DI), Electronic Lab Notebooks (ELN) or Research Software Engineering (RSE). Within this session, we as the WG RSE in the Section Common Infrastructures, will give an impulsive talk on research data and software management in domain-specific NFDI consortia, base4NFDI, and other sections. Following that, we invite NFDI-involved RSEs to join a “Stand-Up-Science” part to briefly present their RSE challenges and solutions in spontaneous or not-so-spontaneous lightning talks (max 7-10 minutes) or short insights into research software such as code, architecture, etc. Questions to answer could be: 1. Name / last academic degree / Affiliation / current task 2. What are your connections to the NFDI? (existing or possible) 3. What was the last thing I coded/worked on 4. Which research data did I last reuse? 5. Which research software did I last reuse? 6. Favourite git command 7. Give a reason why you were told that the software/data could not be published 8. What advice (best/good practice) would you give to a new RSE? If you want to present something, please use the survey at [https://umfragenup.uni-potsdam.de/nfdi-rse/](https://umfragenup.uni-potsdam.de/nfdi-rse/). All the aspects mentioned will be part of a joint paper on the “RSE in NFDI” topic.

MATLAB Tools for Sustainable Research Software Development (RSE education)

• Mihaela Jarema (MathWorks (Academia Group))

Room: Seminarroom 006 Sustainability in research software is crucial to ensure others can understand, reproduce, and build upon your work effectively, potentially extending its functionality with new algorithms and its applications to new domains. In this tutorial, you will learn about tools you can leverage in the MATLAB ecosystem to effectively enhance the maintainability and reusability of your research software. In this session designed for Research Software Engineers (RSEs) who are already familiar with clean code principles, you will deepen your understanding and practically implement these practices within the MATLAB environment. You will explore a range of tools and features that facilitate sustainable software development. Key topics include: • **Code Refactoring Tools:** Leveraging built-in functionalities to refactor and enhance code readability. • **Testing Frameworks:** Implementing tests using MATLAB testing frameworks to ensure robust, error-free code and using Continuous Integration (CI) for automatic testing. • **MATLAB Project Management:** Utilizing project files and dependencies to organize and manage development environments effectively. • **Version Control Integration:** Seamlessly integrating MATLAB with popular version control systems like Git for collaborative development and code tracking. **Who Should Attend:** This tutorial is designed for RSEs, researchers, and developers with a foundational understanding of clean code who wish to enhance their MATLAB skills for sustainable software development.