A combined slide deck of the short reports from Interest and Working Groups at Hydra Connect 2015. Archivists Interest Group Digital Preservation Interest Group Geospatial Interest Group Hydra GIS Data Modeling Working Group Metadata Working Group Page Turner Interest/Working Group Service Management Interest Group User Experience Interest Group Web Presence Interest Group
This will be a half-day, hands-on workshop covering data modeling primarily in RDF. We hope to bring a diverse group of Hydra community members together to learn, discuss, and build out examples that will inform Hydra community best practices for data modeling. This modeling work will be taught in the context of helping Hydra and Fedora development, metadata, and interoperability efforts. We will discuss how model uses a number of standards, and demo the different ways to represent models. We will compare and contract data modeling with metadata standards/profiles. We will walk through modeling efforts around PCDM and its place in our work and community - this workshop will not focus on PCDM alone (this is not a PCDM or RDF workshop). We want this workshop to bring together, develop and engage a larger corps of data modelers in the Hydrasphere. and A workshop delivered at Hydra Connect 2016, described thus
A presentation given at Connect 2017 described thus and With so many Samvera metadataists managing similar objects and collections, can we get a handle on the metadata we have and what we share with the community? This session will introduce the idea behind the Documentation Project from the Samvera Metadata Interest Group and will consider what we're saying about our objects, how we're expressing it, and how best to move this work forward to provide suitable context for what we do or don't want our MAPS to look like as we document our work within Samvera.
A presentation given at Connect 2017 described thus, it’s not fun to have an ingest fail overnight and spend the morning tracking down why. Programmatically testing and validating digital object metadata prior to ingest helps us avoid these failures. The metadata itself is managed by Git and stored in GitHub, Several years ago UCSB incorporated Git/GitHub and JIRA into our metadata management and batch ingest workflows. Since then we’ve looked at repurposing other development tools to provide lightweight and automated solutions to problems we often face. One is that we rely primarily on batch ingests when adding content to our Samvera repository. As a result it’s especially important for the metadata to be error-free, and this allows us to run automated checks against any changes using Jenkins and some custom libraries we’ve written for validating CSV and MODS metadata. In this session, we will provide an overall of our current ingest preparation workflow and the tools we are using, and will discuss some of the benefits that have come out of this collaborative effort.