EXFOR-NSR PDF database: a system for nuclear knowledge preservation and data curation

TL;DR

This paper introduces a comprehensive PDF-based database system for nuclear data and bibliographic preservation, enhancing data verification, evaluation, and enabling machine learning applications in nuclear science.

Contribution

It presents a novel relational database system storing complete nuclear data publications as PDFs and BLOBs, improving data accessibility and verification processes.

Findings

Enhanced nuclear data verification and evaluation.

Facilitated machine learning applications in nuclear data analysis.

Broadened scope of nuclear databases to include full publications.

Abstract

Current needs of nuclear science and technology include complete, well-documented, and easily verifiable nuclear data. The complete data records require supporting nuclear bibliography, presently stored in dedicated libraries, in addition, to actual data. Experimental nuclear reaction data (EXFOR) and Nuclear Science References (NSR) databases contain compilations based on primary (journals) and secondary (conference proceedings, theses, preprints, etc.) publications, and data received from authors via private communications. The secondary library materials and private communications often represent a bottleneck for nuclear data verification, compilation, evaluation, and dissemination activities. To address this issue, bibliographic materials were scanned into PDF (Portable Document Format) files and uploaded in a relational database. The traditional scope of nuclear databases that includes meta-data and numbers derived from data in specialized formats was broadened to accommodate the large volumes of original nuclear data publications. The complete PDF publication files were stored in a relational database as Binary Large OBjects (BLOB). This unique collection of nuclear data compilations and supporting publications generate many opportunities for machine learning applications.