Building a FAIR-aligned data-processing pipeline for investigating research artifact availability in high-energy physics studies

In the current thesis project, a FAIR-aligned data-processing pipeline was developed to extract and classify Data Availability Statements (DAS) and Code Availability Statements (CAS) in high-energy physics scienti c publi cations. The pipeline was designed as a reusable tool organized around ve modules handling ingestion of publications, conversion to text format, ex traction, normalization and classi cation of availability statements. In total, 17,185 documents (n = 8,511 for 2024, n = 8,674 for 2025) were processed. Out of these, 17,076 were scienti c studies analyzed to verify the inclusion of availability statements and classify their content. Results showed that 63.5% of the publications analyzed included a DAS section, while only 31.1% in cluded a CAS section. Nonetheless, year-speci c results showed a marked increase in the inclusion of both DAS and CAS sections in 2025 publications, suggesting possible adaptation to newly introduced open science policies. Classi cation results showed that a majority of studies declared no data and no code associated with the manuscript. When looking at studies that clearly reported associated data or code, a majority of studies declared that such artifacts were only available upon request. Despite this, year di erences in category shares showed an increase in studies reporting both data (+15.8 pp) and code (+16.2 pp) as openly accessible in 2025 publications, accom panied by a decrease in studies reporting these artifacts as only available upon request. This might suggest a general increase in open availability of research artifacts in 2025 compared to 2024. Furthermore, data exploration revealed possible ambiguities around what is considered the proper subject of DAS and CAS sections. For code in particular, authors seem to report availability and usage of di erent types of software artifacts in these sections. This led to the development of a taxonomy di erentiating author-produced code from external software tools in order to adequately classify CAS sec tions. Methodological and policy-related implications of these ndings are discussed. The thesis describes the development of a FAIR-aligned data-processing pipeline for verifying the presence and classifying the content of Data Availability Statements and Code Availailibility Statements in high-energy physics publications. Additionally, the thesis reports analytical results for 2024 and 2025 publications funded and openly published by the Sponsoring Consortium for Open Access Publishing in Particle Physics (SCOAP3).