Publications
Find publications supported by the Science Data Management Branch here.
Filter Total Items: 20
Community for Data Integration 2017 annual report
The Community for Data Integration (CDI) is a group that helps members grow their expertise on all aspects of working with scientific data. The CDI’s activities advance data and information integration capabilities in the U.S. Geological Survey and in the wider Earth and biological sciences. This annual report describes the presentations, activities, collaboration areas, workshop, and other CDI-sp
Authors
Leslie Hsu, Madison L. Langseth
U.S. Geological Survey Community for Data Integration 2017 Workshop Proceedings
Executive SummaryThe U.S. Geological Survey (USGS) Community for Data Integration (CDI) Workshop was held May 16–19, 2017 at the Denver Federal Center. There were 183 in-person attendees and 35 virtual attendees over four days. The theme of the workshop was “Enabling Integrated Science,” with the purpose of bringing together the community to discuss current topics, shared challenges, and steps for
Authors
Leslie Hsu, Vivian B. Hutchison, Madison L. Langseth, Benjamin Wheeler
The evolution, approval and implementation of the U.S. Geological Survey Science Data Lifecycle Model
This paper details how the United States Geological Survey (USGS) Community for Data Integration (CDI) Data Management Working Group developed a Science Data Lifecycle Model, and the role the Model plays in shaping agency-wide policies. Starting with an extensive literature review of existing data Lifecycle models, representatives from various backgrounds in USGS attended a two-day meeting where t
Authors
John Faundeen, Vivian B. Hutchison
Community for Data Integration 2016 annual report
The Community for Data Integration (CDI) represents a dynamic community of practice focused on advancing science data and information management and integration capabilities across the U.S. Geological Survey and the CDI community. This annual report describes the various presentations, activities, and outcomes of the CDI monthly forums, working groups, virtual training series, and other CDI-sponso
Authors
Madison L. Langseth, Leslie Hsu, Jon Amberg, Norman Bliss, Andrew R. Bock, Rachel T. Bolus, R. Sky Bristol, Katherine J. Chase, Theresa M. Crimmins, Paul S. Earle, Richard Erickson, A. Lance Everette, Jeff T. Falgout, John Faundeen, Michael N. Fienen, Rusty Griffin, Michelle R. Guy, Kevin D. Henry, Nancy J. Hoebelheinrich, Randall J. Hunt, Vivian B. Hutchison, Drew A. Ignizio, Dana M. Infante, Catherine Jarnevich, Jeanne M. Jones, Tim Kern, Scott Leibowitz, Francis L. Lightsom, R. Lee Marsh, S. Grace McCalla, Marcia McNiff, Jeffrey T. Morisette, John C. Nelson, Tamar Norkin, Todd M. Preston, Alyssa Rosemartin, Roy Sando, Jason T. Sherba, Richard P. Signell, Benjamin M. Sleeter, Eric T. Sundquist, Colin B. Talbert, Roland J. Viger, Jake F. Weltzin, Sharon Waltman, Marc Weber, Daniel J. Wieferich, Brad Williams, Lisamarie Windham-Myers
Community for Data Integration 2015 annual report
The Community for Data Integration (CDI) continued to experience success in fiscal year 2015. The CDI community members have been sharing, learning, and collaborating through monthly forums, workshops, working groups, and funded projects. In fiscal year 2015, CDI coordinated 10 monthly forums with 16 different speakers from the U.S. Geological Survey and external partners; funded 11 collaborative
Authors
Madison L. Langseth, Michelle Y. Chang, Jennifer Carlino, J. Ryan Bellmore, Daniella D. Birch, Joshua Bradley, R. Sky Bristol, Daniel D. Buscombe, Jeffrey J. Duda, Anthony L. Everette, Tabitha A. Graves, Michelle M. Greenwood, David L. Govoni, Heather S. Henkel, Vivian B. Hutchison, Brenda K. Jones, Tim Kern, Jennifer Lacey, Rynn M. Lamb, Frances L. Lightsom, John L. Long, Ra'ad A. Saleh, Stan W. Smith, Christopher E. Soulard, Roland J. Viger, Jonathan A. Warrick, Katherine E. Wesenberg, Daniel J. Wieferich, Luke A. Winslow
Community for Data Integration 2014 annual report
The U.S. Geological Survey (USGS) researches Earth science to help address complex issues affecting society and the environment. In 2006, the USGS held the first Scientific Information Management Workshop to bring together staff from across the organization to discuss the data and information management issues affecting the integration and delivery of Earth science research and investigate the use
Authors
Madison L. Langseth, Michelle Y. Chang, Jennifer Carlino, Daniella D. Birch, Joshua Bradley, R. Sky Bristol, Craig Conzelmann, Robert H. Diehl, Paul S. Earle, Laura E. Ellison, Anthony L. Everette, Pamela L. Fuller, Janice M. Gordon, David L. Govoni, Michelle R. Guy, Heather S. Henkel, Vivian B. Hutchison, Tim Kern, Frances L. Lightsom, Joseph W. Long, Ryan Longhenry, Todd M. Preston, Stan W. Smith, Roland J. Viger, Katherine Wesenberg, Eric C. Wood
Community for Data Integration 2013 Annual Report
The U.S. Geological Survey (USGS) conducts earth science to help address complex issues affecting society and the environment. In 2006, the USGS held the first Scientific Information Management Workshop to bring together staff from across the organization to discuss the data and information management issues affecting the integration and delivery of earth science research and investigate the use o
Authors
Michelle Y. Chang, Jennifer Carlino, Christopher Barnes, David L. Blodgett, Andrew R. Bock, Anthony L. Everette, Gregory L. Fernette, Lorraine E. Flint, Janice M. Gordon, David L. Govoni, Lauren E. Hay, Heather S. Henkel, Megan Hines, Sally L. Holl, Collin G. Homer, Vivian B. Hutchison, Drew A. Ignizio, Tim J. Kern, Frances L. Lightsom, Steven L. Markstrom, Michael S. O'Donnell, Jacquelyn L. Schei, Lorna A. Schmid, Kathryn M. Schoephoester, Peter N. Schweitzer, Susan K. Skagen, Daniel J. Sullivan, Colin Talbert, Meredith Pavlick Warren
The United States Geological Survey Science Data Lifecycle Model
U.S. Geological Survey (USGS) data represent corporate assets with potential value beyond any immediate research use, and therefore need to be accounted for and properly managed throughout their lifecycle. Recognizing these motives, a USGS team developed a Science Data Lifecycle Model (SDLM) as a high-level view of data—from conception through preservation and sharing—to illustrate how data manage
Authors
John Faundeen, Thomas E. Burley, Jennifer A. Carlino, David L. Govoni, Heather S. Henkel, Sally L. Holl, Vivian B. Hutchison, Elizabeth Martín, Ellyn T. Montgomery, Cassandra Ladino, Steven Tessler, Lisa S. Zolly