These delicately nuanced early reproductions were made using a collotype printing method, which uses light-sensitive gelatin colloid coated plates and photographic negatives to create fine detail. They were presented to Stanford University as a gift from David Starr Jordan, which is noted on a small commemorative plaque tucked in the box. "Before the Meiji Restoration of 1868, the pictures were inspected by the successive Shoguns on the occasion of their periodical visits to the Temples at Nikko, but no other persons were as a matter of fact permitted to view them." The pictures are now considered national treasures. See the fully digitized items online.
Digital Library Blog
Geo4LibCamp is a hands-on meeting to bring together those building repository and associated services for geospatial data to share best practices, solve common problems, and address technical issues. We met at Stanford University for the second Geo4LibCamp unconference from January 30 until February 3, 2017. Nearly 50 attendees from 30 institutions participated in the main three day event, and about 20 attendees for the two day post-conference working sessions. The institutions were primarily academic research libraries -- Alberta, Arizona State, California State, Chicago, Colorado School of Mines, Colorado State, Colorado at Boulder, Connecticut State Library, Cornell, Data Curation Experts, Mapzen, Michigan, Minnesota, Moss Landing Marine Labs, Nebraska at Lincoln, New York U, Northwestern, Notre Dame, Princeton, Purdue, Rice, Stanford, UC Berkeley, UC Davis, UC Riverside, UC Santa Barbara, UC Santa Cruz, UCLA, Wisconsin – Milwaukee, and Yale.
The AV Artifact Atlas has been one of the Stanford Media Preservation Lab's longest running projects (for background on what it is, see this short 2013 post), but recently it has been moved to GitHub. Update your links!
AVAA site: https://bavc.github.io/avaa/
Link to GitHub repository: https://github.com/bavc/avaa
As always, contributors are most welcome, and hopefully the site's new home on GitHub will encourage engagement. Please help us:
- Edit content
- Add new content
Objects from the David Rumsey Map Collection are featured in Atlas Obscura's Map Monday for January 30, 2017, features maps from John Emslie and James Reynolds.From Atlas Obscura's feature: "Have you ever wondered what the tallest active volcano is? Or wanted to compare the height of mountain peaks and the lengths of rivers around the world?
It should come as little surprise that Stanford is playing a large role in the rapid progress towards fully autonomous vehicles. Research data and video recorded by John Kegelman, Lene Harbott, Chris Gerdes and others in the Dynamic Design Lab are now deposited and streamable from the SDR. These data are useful in a variety of ways, such as to inform self-driving cars that can respond to changing conditions like an expert driver handling a race car on a track.
The ArcLight project team would like to provide a brief update regarding our progress on the design process and and timeline for further work. ArcLight is intended be a Blacklight-based environment that supports discovery and digital delivery of information in archives. The project team is using a community-oriented, collaborative design process for ArcLight to engage more institutions earlier in the process.
During Hydra Connect 2016 in Boston this October, we had several discussions around geospatial repository services. There was a half-day workshop and presentation on GeoConcerns -- part of the Hydra Geospatial Data Modeling Working Group chaired by Eliot Jordan; a panel discussion on sharing geospatial metadata; and a meeting of the Hydra Geospatial Interest Group.
For nearly four years, the Stanford Digital Repository (SDR) has been home to the research outputs of scientists and scholars from across Stanford’s campus. But while those data files, videos, source code, microscopy images, survey results, maps and more have been discoverable and accessible through the Libraries’ online catalog, SearchWorks, it has been hard to get an overview of all the available data. Until now.