This week, Digitization Specialist Mike Adamo will move on from Duke Libraries after 14 years to assume a new position as Digital Imaging Coordinator at the Libraries of Virginia Tech University. Mike has contributed so much to our Digital Collections program during his tenure, providing years of uncompromising still imaging services, stewardship in times of change for the Digital Production Center, as well as leadership of and then years of service on our Digital Collections Implementation Team. He has also been the lead digitization specialist on some of our most well known digital collections like the Hugh Mangum photographs, James Karales photographs and William Gedney collection.
In addition, Mike has been a principal figure on our Multispectral Imaging Team and has been invaluable to our development of this service for the library. He established the setup and led all MSI imaging sessions; collaborated cross-departmentally with other members on the MSI Team to vet requests and develop workflows; and worked with vendors and other MSI practitioners to develop best practices, documentation, and a preservation plan and service model for MSI services at Duke Libraries. He’s also provided maintenance for our MSI equipment, researching options for additional equipment as our program grew.
We are grateful to Mike for his years of dedication to the job at to the field of cultural heritage digitization as well as for the instrumental role he’s played in developing MSI Services at DUL. We offer a huge thank you to Mike for his work and wish him well in his future position!
Post contributed by Giao Luong Baker and Erin Hammeke
In early 2017, Duke University Libraries launched a research data curation program designed to help researchers on campus ensure that their data are adequately prepared for both sharing and publication, and long term preservation and re-use. Why the focus on research data? Data generated by scholars in the course of their investigation are increasingly being recognized as outputs similar in importance to the scholarly publications they support. Open data sharing reinforces unfettered intellectual inquiry, fosters transparency, reproducibility and broader analysis, and permits the creation of new data sets when data from multiple sources are combined. For these reasons, a growing number of publishers and funding agencies like PLoS ONE and the National Science Foundation are requiring researchers to make openly available the data underlying the results of their research.
But data sharing can only be successful if the data have been properly documented and described. And they are only useful in the long term if steps have been taken to mitigate the risks of file format obsolescence and bit rot. To address these concerns, Duke’s data curation workflow will review a researcher’s data for appropriate documentation (such as README files or codebooks), solicit and refine Dublin Core metadata about the dataset, and make sure files are named and arranged in a way that facilitates secondary use. Additionally, the curation team can make suggestions about preferred file formats for long-term re-use and conduct a brief review for personally identifiable information. Once the data package has been reviewed, the curation team can then help researchers make their data available in Duke’s own Research Data Repository, where the data can be licensed and assigned a Digital Object Identifier, ensuring persistent access.
“The Data Curation Network (DCN) serves as the “human layer” in the data repository stack and seamlessly connects local data sets to expert data curators via a cross-institutional shared staffing model.”
New to Duke’s curation workflow is the ability to rely on the domain expertise of our colleagues at a few other research institutions. While our data curators here at Duke possess a wealth of knowledge about general research data-related best practices, and are especially well-versed in the vagaries of social sciences data, they may not always have the all the information they need to sufficiently assess the state of a dataset from a researcher. As an answer to this problem, the Data Curation Network, an Alfred P. Sloan Foundation-funded endeavor, has established a cross-institutional staffing model that distributes the domain expertise of each of its partner institutions. Should a curator at one institution encounter data of a kind with which they are unfamiliar, submission to the DCN opens up the possibility for enhanced curation from a network partner with the requisite knowledge.
Duke joins Cornell University, Dryad Digital Repository, Johns Hopkins University, University of Illinois, University of Michigan, University of Minnesota, and Pennsylvania State University in partnering to provide curatorial expertise to the DCN. As of January of this year, the project has moved out of pilot phase into production, and is actively moving data through the network. If a Duke researcher were to submit a dataset our curation team thought would benefit from further examination by a curator with domain knowledge, we will now reach out to the potential depositor to receive clearance to submit the data to the network. We’re very excited about this opportunity to provide this enhancement to our service!