This is a preprint of the "Traceability of samples and data in multi-organizational environments with the Common Provenance Framework" and its supplementary materials. Abstract of the paper: "Reproducibility issues are widely reported in science. As a response, scientific communities have called for enhanced provenance information documenting the complete research life cycle, from biological or environmental material acquisition to translating research results into practice. In this work, we present the Common Provenance Framework (CPF), a domain-agnostic, integrative framework for provenance in multi-organizational environments, with the aim to advance quality assessment of research outputs. Based on formulated requirements, the framework consists of a unified terminology, a multi-organizational provenance architecture, a non-repudiation policy, a PROV-based data model (Common Provenance Model), and a reference implementation. The CPF enables querying of provenance that is generated and managed independently by different organizations, while providing mechanisms to preserve confidentiality and trustworthiness of information. The CPF serves as an open foundation for the ISO 23494 provenance standard series, and is relevant to various international initiatives."Working repository for code and experiments is available here: https://gitlab.ics.muni.cz/422328/dbprov.
Rudolf Wittner (Wed,) studied this question.