The paper introduces an end‑to‑end pipeline that harvests, validates, and models links between scholarly articles and their source code from journals such as JOSS, SoftwareX, and IPOL, as well as SIGMOD ARI reproducibility reports. It produces a curated set of 4,397 DOI‑repository pairs and defines two Wikidata‑based application profiles—one for articles and one for software—aligned with schema.org and CodeMeta. Using these profiles, the authors created 4,182 new Wikidata software items linked to their papers, while only 82 repositories were previously represented, and they demonstrate compatibility with the COAR Notify protocol for future live enrichment.
By Camillo Carlo Pellizzari di San Girolamo, Francesco Tosoni
arXiv:2609.16498v1 Announce Type: cross
Abstract: Research data repositories are essential infrastructure for scientific inquiry and for ensuring that datasets follow FAIR (Findable, Accessible, Inte...
By Daniel Ebanks, Devika Jain
Research data repositories are essential infrastructure for scientific inquiry and for ensuring that datasets follow FAIR (Findable, Accessible, Interoperable, and Reusable) principles. However, repos...
The paper introduces CodeGraph, an open‑taxonomy knowledge graph that semantically annotates source code by extracting entities such as algorithms, paradigms, design patterns, and application domains from millions of files. Using a specialized large language model and a three‑stage Wikidata linking process, the authors ground these entities in Wikidata and construct a graph with about 158 million nodes and 1 billion typed edges across 14 programming languages. A quality‑assurance protocol combining human evaluation and an LLM‑as‑a‑judge filter quantifies annotation precision.
By Federico Pennino, Andrea Gurioli, Stefano Zacchiroli, Maurizio Gabbrielli, Paolo Ferragina
The paper reports on building a research-software catalog using a coding agent, starting from a three‑day hackathon prototype and moving to public deployment. It details the engineering work needed—adversarial review, data‑quality checks, browser validation, and publication safeguards—to ensure reliable operation, noting that silent failures were more problematic than crashes. The authors then examine applying these lessons to a larger, human‑curated portal (MateriApps) that combines curated metadata, external documentation, vector search, and local language‑model generation, finding that explicit validation, monitoring, and repeated review remain essential for AI‑assisted software portals.
By Kazuyoshi Yoshimi, Satoshi Terasaki, Gotai Yamada
arXiv:2606. 30304v1 Announce Type: cross Abstract: This paper presents preliminary findings from a UKRI-funded Metascience project comparing three LLM-based approaches, GPT-4o, Mistral, and a bespoke algorithm, DSIT-Taxonomies, for extracting and classifying research entities from funding proposals.
By Xingran Ruan, Angelo Salatino, Rosa Filgueira, Kara Moraw, Alexandru Marcoci, Gemma Derrick, Sarah Callaghan