24 x 7 (to 3:30)

Since its public launch in the fall of 2011, DuraCloud has been adopted by various organizations in order to meet a wide range of preservation and access use cases and digital content storage needs. When making the decision of whether or not to subscribe to DuraCloud and move content into the cloud, these organizations had to weigh the advantages, disadvantages, and risks of using the cloud versus building and supporting a local solution. The “DuraCloud for Dummies” 24x7 presentation will walk through the highlights of both the decision making process of choosing to move to the cloud as well as how to use the DuraCloud service (all to the tune of Should I Stay or Should I Go by the Clash).

DataONE is a distributed network of data repositories. Each individual repository is considered a Member Node within the network. Member Nodes make their data available to the network's Coordinating Nodes. Coordinating Nodes provide network-wide services, including centralized search and replication of content between Member Nodes. The division of effort between Member Nodes and Coordinating nodes provides for a robust and highly scalable network. This talk gives an overview of the process for, and benefits of, integrating a repository with the DataONE network.

At the University of Notre Dame Hesburgh Libraries we make extensive use of Hydra, in particular Active Fedora. Our applications invariably interact with Rails, Solr, CanCan, CAS, Fedora Commons, and just about everything else – or as we like to call it “Lots of Moving Parts”. And for what? So we can store files on a file system for both access and long term preservation.

With all these moving parts, we need to ensure that what we think and say is being written is actually written and retrieved properly…especially when any of the moving parts are updated.

Datastar is an open-source, semantic-web-based platform supporting the description, discovery, access, curation, and reuse of research datasets. Datastar extends the ability of the VIVO researcher profiling system to represent relationships among researchers, grants, and publications to capture the scholarly context around research datasets and to highlight dataset citations. Datastar can be run either as a standalone dataset registry or as an extension to an institutional instance of VIVO. The Datastar project was initially funded in 2007 by NSF, and more recently in 2011 by the U.S. Institute of Museum and Library Services. In this presentation, we will report on the more recent work, which has involved both working with researchers to create a set of Data Curation Profiles to understand researchers’ needs and preferences with respect to documentation, sharing, dissemination, and reuse of datasets; and applying those profiles to the development of the Datastar application. Datastar promotes open access and easy discoverability of research datasets; it promotes reproducible research through interlinking research datasets with the full research context of researchers, publications, and grants; and it complements the capabilities of open institutional and disciplinary repositories as part of the overall research ecosystem.