Connections: Emergency preparedness for librarians and emergency management personnel (archive)
MetadataShow full item record
DescriptionA symposium hosted by the University of Maryland, Baltimore, Health Sciences and Human Services Library on November 18, 2010. Presenters included Rebecca Hamilton, Cindy Love, Amy L. Major, Richard Muth and Rowan.
SponsorsThis project has been funded in whole or in part with Federal funds from the National Library of Medicine, National Institutes of Health, Department of Health and Human Services, under Contract ND1-LM6-3502 with the University of Maryland, Baltimore, Health Sciences and Human Services Library.
Connections: Emergency preparedness for librarians and emergency management personnel
Identifier to cite or link to this itemhttp://hdl.handle.net/10713/4656
The following license files are associated with this item:
- Creative Commons
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc-nd/4.0/
Showing items related by title, author, creator and subject.
Connections: emergency preparedness for librarians and emergency management personnel in MarylandBerlanstein, Debra R.; Grier, Persko L., Jr.; Solomon, Meredith (2010-10)This poster describes a one-day event hosted by the University of Maryland Health Sciences and Human Services Library to bring together librarians from across Maryland with emergency planning personnel to share ideas, establish partnerships, and bring attention to how libraries and emergency agencies can work together in an emergency situation.
Emerging Approaches to Managing and Analyzing Large Data Sets for Longitude StudiesBell, Beverly (2014-07-17)Learning Objectives • Gain a better understanding of the challenges to leveraging data as well as providing pragmatic approaches to creating analytics capability to achieve better results • Provide recommendations on how to spark the ‘ah - ha’ moment about the power of analytics and remove barriers to adopting this technology • Share experiential practices for the management, utilization and adoption of large amounts of data