Matching Items (55)
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Description

Developed a business product with a team of CS students.

ContributorsSchneider, Kaitlin (Co-author) / Perri, Cole (Co-author) / Hernandez, Maximilliano (Co-author) / Call, Andy (Thesis director) / Hunt, Neil (Committee member) / School of Accountancy (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Developed a business product with a team of CS Students

ContributorsHernandez, Maximilliano (Co-author) / Schneider, Kaitlin (Co-author) / Perri, Cole (Co-author) / Call, Andy (Thesis director) / Hunt, Neil (Committee member) / School of Accountancy (Contributor) / School of Sustainability (Contributor) / Department of Information Systems (Contributor) / Department of Management and Entrepreneurship (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Developed a business product with a team of CS students.

ContributorsPerri, Cole Thomas (Co-author) / Hernandez, Maximilliano (Co-author) / Schneider, Kaitlin (Co-author) / Call, Andy (Thesis director) / Hunt, Neil (Committee member) / School of Accountancy (Contributor) / Watts College of Public Service & Community Solut (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

A two-part presentation from the ASU Library and Knowledge Enterprise Research Data Management Office. Presented at the 2023 Rocky Mountain Advanced Computing Consortium (RMACC).

Session 1: Data management planning is an integral step in the research data life cycle. Large amounts of data and lengthy code accompanying supercomputing runs are no

A two-part presentation from the ASU Library and Knowledge Enterprise Research Data Management Office. Presented at the 2023 Rocky Mountain Advanced Computing Consortium (RMACC).

Session 1: Data management planning is an integral step in the research data life cycle. Large amounts of data and lengthy code accompanying supercomputing runs are no exception. Planning before analysis will benefit research and the researcher by providing a clear strategy for collecting, storing, analyzing, and sharing the data at the end of the research cycle. Supercomputing can require significant storage beyond scratch space, but researchers typically need to be informed of what tools are appropriate and available. Framed within the planning phase of the life cycle, this presentation presents ASU’s Storage Selector as a quick and easy tool to find the most appropriate storage resources provided by the university to help researchers choose a proper storage and management solution for their research data at the right time in their project. We will also explore the DMP Tool, developed by the California Digital Library, which provides a resource-rich platform for writing data management plans, including institutional-specific guidance, feedback request, and public plans that can be used as guides.

Session 2: This presentation overviews the ongoing working relationship between the ASU Library Open Science and Scholarly Communication division, Research Data Management Office, and Research Computing. We will explore these teams’ interdisciplinary relationships and interdependence as the institution increasingly supports open science practices and initiatives. We will include case studies regarding the decision-making process, data-sharing decisions, and opportunities and challenges when transferring research data from a high-performance computing environment to the ASU Research Data Repository. Finally, we will share lessons learned as we intentionally shepherd research data from active project management and storage to final publication and preservation.

ContributorsHarp, Matthew (Author) / Claypool, Kathryn (Author)
Created2023-05-17
Description

(Preprint.) Today's college and university learning landscapes are dynamic and
characterized by increased student demand for highly flexible and self-paced online learning opportunities. Recent fiscal conditions in higher education make learning landscape development more challenging due to finite resources and competing priorities. Similarly, academic libraries are experiencing substantial budget and staff

(Preprint.) Today's college and university learning landscapes are dynamic and
characterized by increased student demand for highly flexible and self-paced online learning opportunities. Recent fiscal conditions in higher education make learning landscape development more challenging due to finite resources and competing priorities. Similarly, academic libraries are experiencing substantial budget and staff reductions. Despite these trends, academic libraries are in a strong position to contribute to surrounding learning landscapes by expanding student online learning opportunities and promoting the critical use of information. Evolving learning technologies available for free or at low cost provide higher education and libraries with the tools to respond to this fluid environment.

ContributorsKammerlocher, Lisa (Author) / Couture, Julianne (Author) / Sparks, Olivia (Author) / Harp, Matthew (Author) / Allgood, Tammy (Author)
Created2011
Description

Library One Search (Summon) Usability at ASU

ContributorsAllgood, Tammy (Author) / Kush, Jordyn (Author)
Created2015-11-06
Description

Conference Proceedings

ContributorsAllgood, Tammy (Author) / Gallegos, Bee (Author) / Grondin, Karen (Author)
Created2007-05-04
Description

Invited presenter for ALA Annual Conference, 2008.

ContributorsAllgood, Tammy (Author) / Duarte, Marisa (Author)
Created2008-06-20
DescriptionMarketing library resources, services and personnel to information-overloaded university students can be a challenge. Learn how Arizona State University Libraries produces the fun and informative Library Minute video series, how it’s used by instructors, and how it’s received by students.
ContributorsPerry, Anali Maughan (Author) / Harp, Matthew (Author)
Created2010-10-12