Our first cohort of the rOpenSci Champions Program has now completed the second phase of the program by developing their project and carrying out outreach activities. In this article, we share each Champion’s project, their achievements and their outreach activities. Champions’ Projects In their applications Champions choose to develop a new package or to participate in the review process as authors or reviewers.

By Michelle Barker, Leyla Jael Castro, Bernadette Fritzsch, Daniel S. Katz, Carlos Martinez-Ortiz, Anna Niehues, Alexander Struck, Qian Zhang [This blog past has been cross-posted by the Software Sustainability Institute, Netherlands eScience Center, and others.] The FAIR for Research Software (FAIR4RS) Principles aim to promote and encourage the findability, accessibility, interoperability, and reusability (FAIR) of research software.

A few years ago an internal initiative on software quality launched at the Research and Development Department. There is always room for improvements and some guidance can help implement best practices for better workflows and for better code. The very first stop on our ride was at Joel`s Test for better code, published 24 years ago. It is time for a review — again. Do you use source control? Who doesn’t? Can you make a build in one step?

What’s the best way to make a movie file from microscopy data? Maybe you need to generate a movie for the supplementary info for a paper, or insert one into your electronic lab notebook, or to show in a talk. The problem is that the requirements for each of those is different. This situation is compounded by the fact that there are so many options to make movie files and not much guidance on what is the best method.

An Overview of Constructing a Knowledge Graph Author · Qingqin Fang ( ORCID: 0009–0003–5348–4264) 1. Introduction 1.1 What is a Knowledge Graph Knowledge Graphs are structured semantic knowledge bases used to rapidly describe concepts and their relationships in the physical world.

Unlocking the Future of AI: The Transformative Journey of Large Language Models Author · Vaibhav Khobragade ( ORCID: 0009–0009–8807–5982) Introduction Human language development is innate and evolves throughout life. Machines lack this ability to evolve without advanced AI algorithms.

Using intelligence to use artificial Intelligence: A deep dive into Prompt Engineering Author Dhruv Gupta (ORCID: 0009–0004–7109–5403 ) Introduction Large Language Models (LLMs) have become the new normal in the field of Natural Language Processing (NLP). With their improved performance and generative power, people around the world are relying on it for

Boosting Performance for Knowledge Graphs with Neo4j APOC Library Author Wenyi Pi (ORCID: 0009–0002–2884–2771) Introduction A knowledge graph (graph database) captures information about main entities in a domain and the relationships between them. It was an augmented feature store for connected data which gave access to compute, access and operationalise structure features.

Understanding Knowledge Networks From A Graph Perspective Author: Amanda Kau (ORCID: 0009–0004–4949–9284 ) Since 2020, over ten million scholarly articles have been published annually. To put that into perspective, say all ten million articles were released on the first day of the year.

Latest findings in multiple research directions for tackling reasoning and common sense challenges Author: Xuzeng He ( ORCID: 0009–0005–7317–7426) Knowledge Graphs, such as Wikidata, contain rich relational information between entities and have been widely used as a structured format for storing and representing relational information.