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-
- Type:
- Document
- Description/Abstract:
- README for dataset available through the collection, Examining the Substance of Bone through a Meta-Analysis of Academic Texts.
- Creator/Author:
- McCabe, Erin E.
- Submitter:
- Erin E. McCabe
- Date Uploaded:
- 11/10/2020
- Date Modified:
- 11/10/2020
- License:
- Attribution 4.0 International
-
- Type:
- Generic Work
- Description/Abstract:
- A presentation from the Society of Ohio Archivists 2020 meeting. The University of Akron University Archives and the University of Cincinnati Libraries will present and analyze challenges faced by institutions looking to create, implement and improve their digital preservation program. Armed with the NDSA Levels of Digital Preservation and the Digital Preservation Capability Maturity Model (DPCMM), both institutions discuss strategies to tackle common issues such as minimal staffing, limited resources, procrastination, and legacy digital content. Each institution will also discuss strategies used to handle unique challenges faced in crafting their individual digital preservation policies. Presentation recording available: https://youtu.be/czemLLqXNh8
- Creator/Author:
- Van Mil, James; Orcutt, Zoe; Hayes, Brittany, and Gao, Sidney
- Submitter:
- James Van Mil
- Date Uploaded:
- 11/09/2020
- Date Modified:
- 11/10/2020
- Date Created:
- 2020-06-16
- License:
- All rights reserved
-
- Type:
- Generic Work
- Description/Abstract:
- A presentation at the joint Upper Midwest Digital Collections Conference and Minnesota Digital Library Annual Meeting in 2020. The diversity of a digital collection is often assessed by considering the diversity of its content. In order for collections to be truly inclusive, however, they need to emphasize usability alongside broad representation. The University of Cincinnati Libraries discusses how diversity and accessibility are intersectional considerations of digital collections, and introduces newly implemented workflows and standards designed to create accessible, inclusive digital collections that broaden usability for all. Presentation recording available (Starts at 14 minutes, 30 seconds): https://youtu.be/srIPaD7RvYo
- Creator/Author:
- Van Mil, James and Gao, Sidney
- Submitter:
- James Van Mil
- Date Uploaded:
- 11/09/2020
- Date Modified:
- 11/09/2020
- Date Created:
- 2020-11-05
- License:
- All rights reserved
-
- Type:
- Generic Work
- Description/Abstract:
- The files in this work represent the presentations and workshop content from the 5th UC Data Day held 2020-10-23. The theme was “World Changing Data: How Digital Data Will Change Our Future”. The Keynote speaker was Glenn Ricart, of US Ignite - "Smart Runs on Data" Interactive Panel featuring: Michael Dunaway (moderator) - Whitney Gaskins (Asst Dean, CEAS - Incl Excellence & Comm Engagmnt) - Zvi Biener (Assoc Professor, A&S Philosophy) - Prashant Khare (Asst Professor, CEAS - Aerospace Eng & Eng Mechanics)- Sam Anand (Professor, CEAS - Mechanical Eng) - Achala Vagal (Professor Clinical - GEO, COM Radiology Neuroradiology) Power Sessions: George Turner - Indiana University - High-Performance Computing at UC Erin McCabe - University of Cincinnati - Text Mining, Natural Language Processing & AI link to slides - https://bit.ly/dataday_slides link to code - https://bit.ly/dataday_code Videos of the day can be found on the UC Libraries STRC1 youtube channel - https://www.youtube.com/c/STRC1/videos
- Creator/Author:
- Koshoffer, Amy
- Submitter:
- Amy Koshoffer
- Date Uploaded:
- 11/03/2020
- Date Modified:
- 12/04/2020
- Date Created:
- 2020-10-23
- License:
- Attribution-NonCommercial-ShareAlike 4.0 International
-
- Type:
- Document
- Description/Abstract:
- Monthly newsletter for Fire and EMS.
- Creator/Author:
- Bennett, Lawrence
- Submitter:
- Lawrence Bennett
- Date Uploaded:
- 11/02/2020
- Date Modified:
- 05/05/2026
- Date Created:
- 2020-11
- License:
- Attribution 4.0 International
-
- Type:
- Dataset
- Description/Abstract:
- The data sets were derived from coronavirus related scientific literature using the CORD-19 dataset released by the Allen Institute of Artificial Intelligence as of July 14, 2020, using the Elasticsearch engine hosted by the Digital Scholarship Center (DSC). Through indexing the full-text and the metadata of the article corpus, the research team generated a full-corpus model and 7 different models corresponding to key viral outbreaks from the past several decades' coronaviruses (SARS-CoV, MERS-CoV, and SARS- CoV-2) and non-coronaviruses (HIV, Zika, H1N1, and Ebola). The targeted subsets of the articles used two or more occurrences of virus-specific keywords drawn from conventions established by the World Health Organization.
- Creator/Author:
- Koshoffer, Amy; Wu, Danny; Latessa, Jenny; Kannayyagar, Suraj; Luken, Sally; McCabe, Erin; Edgerton, Ezra; Washington, Dorcas; Lee, James; Powers, Margaret, and Hagedorn, Philip
- Submitter:
- Amy Koshoffer
- Date Uploaded:
- 10/30/2020
- Date Modified:
- 11/05/2020
- Date Created:
- 2020-07
- License:
- CC0 1.0 Universal
-
- Type:
- Dataset
- Description/Abstract:
- The data sets were derived from coronavirus related scientific literature using the CORD-19 dataset released by the Allen Institute of Artificial Intelligence as of July 14, 2020, using the Elasticsearch engine hosted by the Digital Scholarship Center (DSC). Through indexing the full-text and the metadata of the article corpus, the research team generated a full-corpus model and 7 different models corresponding to key viral outbreaks from the past several decades' coronaviruses (SARS-CoV, MERS-CoV, and SARS- CoV-2) and non-coronaviruses (HIV, Zika, H1N1, and Ebola). The targeted subsets of the articles used two or more occurrences of virus-specific keywords drawn from conventions established by the World Health Organization.
- Creator/Author:
- Koshoffer, Amy; Hagedorn, Philip ; Latessa, Jenny; Lee, James; Power, Margaret; Luken, Sally; McCabe, Erin; Wu. Danny; Washington, Dorcas; Kannayyagar, Suraj, and Edgerton, Ezra
- Submitter:
- Amy Koshoffer
- Date Uploaded:
- 10/29/2020
- Date Modified:
- 11/05/2020
- Date Created:
- 2020-07
- License:
- CC0 1.0 Universal
-
- Type:
- Dataset
- Description/Abstract:
- The data sets were derived from coronavirus related scientific literature using the CORD-19 dataset released by the Allen Institute of Artificial Intelligence as of July 14, 2020, using the Elasticsearch engine hosted by the Digital Scholarship Center (DSC). Through indexing the full-text and the metadata of the article corpus, the research team generated a full-corpus model and 7 different models corresponding to key viral outbreaks from the past several decades' coronaviruses (SARS-CoV, MERS-CoV, and SARS- CoV-2) and non-coronaviruses (HIV, Zika, H1N1, and Ebola). The targeted subsets of the articles used two or more occurrences of virus-specific keywords drawn from conventions established by the World Health Organization.
- Creator/Author:
- Koshoffer, Amy; Wu, Danny; Latessa, Jenny; Lee, James; Luken, Sally; McCabe, Erin; Edgerton, Ezra; Washington, Dorcas; Kannayyagar, Suraj, and Powers, Margaret
- Submitter:
- Amy Koshoffer
- Date Uploaded:
- 10/29/2020
- Date Modified:
- 11/05/2020
- Date Created:
- 2020-07
- License:
- CC0 1.0 Universal
-
Patricia Novillo-Corvalán, Modernism and Latin America: Transnational Networks of Literary Exchanges
- Type:
- Article
- Description/Abstract:
- -
- Creator/Author:
- Rioseco, Marcelo
- Submitter:
- Jeffrey Loveland
- Date Uploaded:
- 10/29/2020
- Date Created:
- 2018
- License:
- Attribution-NonCommercial-NoDerivs 4.0 International
-
- Type:
- Article
- Description/Abstract:
- -
- Creator/Author:
- Ríos Cordero, Hugo
- Submitter:
- Jeffrey Loveland
- Date Uploaded:
- 10/29/2020
- Date Created:
- 2018
- License:
- Attribution-NonCommercial-NoDerivs 4.0 International