This paper examines the implementation of the PREMIS Data Dictionary for Preservation Metadata in the context of a pilot project aimed at developing a scalable, shared digital preservation solution for multiple Government cultural institutions in New South Wales, Australia. It provides a case study exploring the challenges and decisions made in the creation of a Common Submission Information Package (SIP) Specification, particularly regarding the creation and use of preservation metadata by Producers versus digital preservation systems. It highlights the need for guidance on implementing PREMIS in SIPs and suggests potential areas for further documentation.

This paper presents the various reasons and decisions taken through the years that have resulted in the Royal Danish Library bit preserving metadata in a standardized way, and using web archive standards and technologies as part of the preservation. Furthermore, the paper will explain how this can contribute to exit plans, disaster plans as well as supporting analysis, search and reporting. The web archive standards included is the WARC package format and the Persistent Web IDentifier (PWID). The web archive technologies will be the SOLR index and possibly tools like SolrWayback. Furthermore, the paper will summaries the challenges leading to the decisions, as well as explain the standards and data models used for the bit preserved metadata.

Digital preservation infrastructures often prioritize the stability of content and metadata. In taxonomy, species names are formed according to the Articles listed in the International Code of Zoological Nomenclature. The reasons for these changes are rarely recorded in detail or made machine-readable. This paper examines this preservation gap. Here, we cover issues in the Code by looking at approaches to recording nomenclatural changes related to the Kakapō Strigops habroptila. As a potential solution, we present Codex Mutabilis, a digital journal with a publication model that documents ICZN-mandated name changes with full textual justification, persistent identifiers, and archival infrastructure. We argue that this model offers a blueprint for preserving interpretive metadata in the sciences.