Digital repository development increasingly demands proficiency across multiple programming languages and frameworks, creating significant barriers for developers learning new technologies. While pair programming with experienced colleagues has traditionally facilitated this learning process, AI coding assistants offer a promising alternative. This presentation demonstrates practical applications of AI programming tools—specifically Cursor and GitHub Copilot—in developing digital repository solutions. Through live demonstrations, I will explore two real-world scenarios: implementing a search application using the Primo API and creating a Python-based preservation script for Hyrax repository content. The demonstration will showcase how AI assistants can accelerate development by providing real-time code generation, automated project structuring, and intelligent error-handling suggestions. This presentation offers insights into leveraging AI assistance to create more robust and maintainable repository systems by examining these tools' strengths and limitations. This approach reduces barriers to entry for new developers and enables faster implementation of digital repository features, ultimately contributing to more equitable access to digital resources.

The CERN Analysis Preservation (CAP) repository enables physicists at CERN to store and manage their analysis metadata. Supporting diverse experiments like CMS and LHCb, CAP faces the challenge of accommodating each experiment’s unique procedures and data requirements, which go beyond a one-size-fits-all schema. Initially, these schemas were manually designed in collaboration with each experiment, but this approach proved slow, inflexible, and a bottleneck for onboarding new experiments.

To address this, we developed an interactive form builder, allowing experiments to independently create, maintain, and edit their schemas through a user-friendly interface. Over time, this tool evolved into a robust solution, react-formule, with powerful customization options and a versatile feature set, making it a valuable asset beyond CAP.

Now open-sourced in alignment with CERN’s commitment to open science, react-formule offers a variety of field types, validation logic, and visual settings, along with new exciting AI-powered features that further simplify form creation.

This presentation will introduce CAP and give an overview of react-formule, its main features, how to use it and how to integrate it in your applications.

This project presents a fully automated, cost effective, and highly available statistical dashboard providing an overview of the current status of the CKAN-based data repository depositar (https://data.depositar.io/). The dashboard is built entirely with open-source tools such as D3.js, DataTables, and Bootstrap. In addition, the dashboard is automatically refreshed daily with the help of GitLab’s CI/CD pipelines. We utilize CKAN's Action API which exposes all of CKAN's core features. The CKAN APIs allow access to JSON-formatted lists of a CKAN instance's datasets, as well as the JSON representations of all the datasets and resources at the instance. This practice demonstrates how to automate data analytics and visualization without incurring heavy costs, offering an innovative approach to collecting status data and sharing repository insights.

The migration of Infoscience, EPFL’s institutional repository, to DSpace-CRIS required a custom Python-based pipeline to automate the ingestion of research outputs and datasets. Limitations in default DSpace-CRIS import tools, such as insufficient query controls, incomplete metadata mappings, and a lack of deduplication mechanisms, necessitated a tailored approach. 

The pipeline leverages the DSpace REST API to enable precise queries, metadata reconciliation, and robust deduplication. It incorporates fallback mechanisms, such as publisher-specific APIs, for full-text retrieval when standard tools like Unpaywall and CrossRef prove insufficient. Key challenges included reconciling authorship with EPFL directories, aligning metadata across diverse collections, and maintaining data consistency during imports. 

The developer track presentation will provide a visual breakdown of the pipeline’s architecture, highlight key challenges, and illustrate the solutions implemented. The presentation will complement this by delving deeper into the technical details and lessons learned. Both formats will offer practical insights for repository managers and developers seeking to automate data imports and optimize workflows in institutional repositories. 

Efficient debugging is crucial for maintaining the stability and performance of repository systems like DSpace. In this developer track presentation, we will showcase the systematic techniques employed to identify and resolve a challenging backend database issue in DSpace. The problem, initially revealed through automated UI tests, was traced back to unresponsive database connections. By leveraging advanced debugging tools and methods, we isolated the root cause and developed several fixes.