What does this research mean for the field?

The reproducibility package for the Prioris Evidence-Graded Knowledge Graph enables consistent evaluation and reproduction of research findings across the series. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

The aim is to provide a comprehensive reproducibility package for the Prioris research series.

March 17, 20260 citationsOpen Access

Reproducibility Package for the Prioris Evidence-Graded Knowledge Graph: Code, Data, and Configuration Artifacts

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RMRogier Meulenaar

Key Points

The aim is to provide a comprehensive reproducibility package for the Prioris research series.
Documented the reproducibility package including Dockerfile and configuration artifacts.
Classified reproducibility by artifact types: deterministic, stochastic, and analytical.
Provided evaluation scripts and reproduction commands for artifacts.
Developed a detailed reproduction matrix for all papers in the series.
Outlined methods to classify and evaluate reproducibility based on artifact types.

Abstract

Paper 16 in the Prioris research series. Documents the reproducibility package including Dockerfile, configuration artifacts, evaluation scripts, and reproduction matrix for all papers in the series. Classifies reproducibility by artifact type (deterministic, stochastic, analytical) and provides evaluator commands. Part of the Evidence-Graded Knowledge Graphs research programme (Paper 0: 10.5281/zenodo.19024611).

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Reproducibility Package for the Prioris Evidence-Graded Knowledge Graph: Code, Data, and Configuration Artifacts

Key Points

Abstract

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