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This presentation aims to outline strategic initiatives that promote data stewardship and computing efficiency.

June 10, 2026Open Access

TDCC-NES Projects: SS-NES, CLOUD-NES, and ECO-SCALE

Key Points

This presentation aims to outline strategic initiatives that promote data stewardship and computing efficiency.
Evaluated and developed best practices for software management across its lifecycle.
Promoted cloud-native tools for data processing and access.
Established frameworks for energy-efficient computing and training networks.
Developed tools like the SMP Decision Tree and Code Auditor to enhance research software quality.
Created a community-driven platform for cloud-optimized data processing.
Formed a community of practice and training networks for large-scale energy-efficient computing.

Abstract

This presentation outlines the strategic vision, deliverables, and collaboration frameworks of three initiatives funded by the Thematic Digital Competence Centre for Natural and Engineering Sciences (TDCC-NES): SS-NES, CLOUD-NES, and ECO-SCALE. Collectively, these projects support researchers and research support staff across the Netherlands by providing the tools, infrastructure, and training necessary to elevate data stewardship and computing workflows. SS-NES: "Best Practices for Sustainable Software" focuses on improving research software quality throughout its entire life cycle, i.e. Planning, Initiation, Development, Publishing, and Sharing (https://ss-nes.github.io). Key tools developed include: SMP Decision Tree: An interactive online service built with `docassemble` to easily generate machine- and human-friendly Software Management Plans (SMPs) (https://smp.research.software). Meta Template: A standardization tool working with `copier` to build language-, institution-, and discipline-specific research software templates (https://github.com/SS-NES/meta-template). Code Auditor: A command-line package designed to extract metadata and audit codebase compliance against reference research software best practices (https://github.com/SS-NES/code-auditor). CLOUD-NES: "Facilitating Cloud-native Data Access and Processing for Natural and Engineering Sciences" promotes the adoption of cloud-native tools and optimized formats (https://cloudnes.org). It features a community-driven data processing platform for self-exploration, clear benchmarking frameworks for cloud-optimized data, and specialized training frameworks for datasets. ECO-SCALE: "Building Skills for Large-Scale and Energy-Efficient Scientific Computing in the NES" addresses green computing and large-scale computing challenges. It aims to establish a self-sustaining Energy-Efficiency Community of Practice (CoP), build a Large-scale Computing Training Network (LCTN) to coordinate High-Performance Computing (HPC) training nationally, and create an open, community-driven knowledge base. A central objective of this presentation is to invite active participation from local DCCs to maximize the institutional impact of these projects. Opportunities for institutional collaboration include: Joint Training Sessions: Hosting workshops for local researchers and research support staff on navigating the SMP tool, building custom institutional templates, generating cloud-optimized datasets, and monitoring the energy consumption of computing workflows. Dataset & Workflow Benchmarking: Co-identifying community datasets and computational workflows that would benefit from cloud-optimized transformations to provide empirical pros and cons versus traditional data layouts. Community Co-Development: Contributing localized expertise to open knowledge bases and participating in the co-design of training materials.

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