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  • Iterations of the RDS Unit_2012-2022

    Document thumbnail: Iterations of the RDS Unit_2012-2022
    Type:
    Document
    Description/Abstract:
    This document is supplemental materials for the book chapter "Playing in the Same Sandbox: Collaborations on Data Management, Research Technologies, and Research Computing" in the book Cases on Establishing Effective Collaborations in Academic Libraries authored by Amy Koshoffer and Amy Latessa
    Creator/Author:
    Koshoffer, Amy
    Submitter:
    Amy Koshoffer
    Date Uploaded:
    04/18/2022
    Date Modified:
    04/18/2022
    Date Created:
    2022-04-18
    License:
    Attribution-NonCommercial-ShareAlike 4.0 International

  • Open Research: Making Harmful Habits History

    Media thumbnail: Open Research: Making Harmful Habits History
    Type:
    Media
    Description/Abstract:
    This webinar was a part of the Data and Computation Science Series. It occurred on March 4, 2021, at 2:00 pm EST. Presenter Bio for Ashley Farley: Over the past decade, Ashley has worked in both academic and public libraries, focusing on digital inclusion and facilitating access to scholarly content. She completed her Masters's in Library and Information Sciences through the University of Washington’s Information School. Ashley is a Program Officer of Knowledge and Research Services at the Bill and Melinda Gates Foundation. In this capacity, she leads the foundation’s Open Access Policy’s implementation and associated initiatives. This includes leading the work of Gates Open Research, a transparent and revolutionary publishing platform. Other core activities involve supporting the strategic and operational aspects of the foundation’s library. This work has sparked a passion for open access, believing that freely accessible knowledge has the power to improve and save lives.” Title of Presentation: Open Research: Making Harmful Habits History
    Creator/Author:
    Farley, Ashley
    Submitter:
    Amy Koshoffer
    Date Uploaded:
    03/05/2021
    Date Modified:
    03/09/2021
    Date Created:
    2021-03-04
    License:
    Attribution 4.0 International

  • UC Data Day 2020 Presentations

    Generic Work thumbnail: UC Data Day 2020 Presentations
    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

  • COVID 19 literature NLP models – Viral outbreak topic tuning

    Dataset thumbnail: COVID 19 literature NLP models – Viral outbreak topic tuning
    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

  • COVID 19 literature NLP models – Viral outbreak models formatted

    Dataset thumbnail: COVID 19 literature NLP models – Viral outbreak models formatted
    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

  • COVID 19 literature NLP models - Viral outbreak model centrality files

    Dataset thumbnail: COVID 19 literature NLP models - Viral outbreak model centrality files
    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

  • Authors' contribution document for JFD Article "Gaming the System : Impediments to Promotion and Women’s Pathways from Associate to Full Professor and from Associate Senior to Senior Librarian

    Document thumbnail: Authors' contribution document for JFD Article "Gaming the System : Impediments to Promotion and Women’s Pathways from Associate to Full Professor and from Associate Senior to Senior Librarian
    Type:
    Document
    Description/Abstract:
    This document is the authors' contribution to the article Journal of Faculty Development - Special Section on the Advancement of Women in Higher Education - Gaming the System: Impediments to Promotion and Women’s Pathways from Associate to Full Professor and from Associate Senior to Senior Librarian
    Creator/Author:
    Koshoffer, Amy; Bessett, Danielle; Castiello, Katherine Jones; Weinstein, Valerie; Sadre-Orafai, Stephanie; Peplow, Amber, and Jenkins, Laura Dudley
    Submitter:
    Amy Koshoffer
    Date Uploaded:
    10/21/2020
    Date Modified:
    12/14/2020
    Date Created:
    2020-10-21
    License:
    All rights reserved

  • Promoting your Research and Research Impact

    Media thumbnail: Promoting your Research and Research Impact
    Type:
    Media
    Description/Abstract:
    This webinar was a part of the Data and Computation Science Series and one of five webinars focused on the Publishing Lifecycle of Data. It occurred on August 24, 2020, at 2:00 pm EDT. Presenter Bios: Sheila Rabun is the ORCID US Community Specialist at LYRASIS, providing dedicated support for institutions adopting ORCID (including University of Cincinnati). Sheila has a background in academic libraries, with a focus on digital workflows, research support, and advocating for interoperability in academia and scholarly communication workflows. Learn more about Sheila at  https://orcid.org/0000-0002-1196-6279 Melissa Jacquart is an Assistant Professor in the Philosophy Department at the University of Cincinnati and Associate Director for the Center for Public Engagement with Science. Her research focuses on epistemological issues in the philosophy of science, specifically on the use of models and computer simulations in astrophysics. Her research also examines the role philosophy can play in general public understanding of science, and in science education. She also works on ethics & values in science, science policy, feminist philosophy, and educational best practices. Prior to Cincinnati, she was a postdoctoral fellow at the University of Pennsylvania and the Carnegie Observatories. She has also worked for the National Science Foundation Directorate of Social, Behavioral, and Economic Sciences. She received her PhD, MA in Philosophy from The University of Western Ontario (Canada) and has a BS in Astronomy-Physics, Physics, and Philosophy from The University of Wisconsin-Madison.
    Creator/Author:
    Shelia Rabun; Melissa ; Mark Chalmers, and Rebecca Olson
    Submitter:
    Amy Koshoffer
    Date Uploaded:
    08/25/2020
    Date Modified:
    08/25/2020
    Date Created:
    2020-08-24
    License:
    Attribution-NonCommercial-ShareAlike 4.0 International

  • Publishing Data in Repositories

    Media thumbnail: Publishing Data in Repositories
    Type:
    Media
    Description/Abstract:
    This webinar was a part of the Data and Computation Science Series and one of five webinars focused on the Publishing Lifecycle of Data. It occurred on August 10, 2020, at 2:00 pm EDT. Presenter Bios: Lawrence Bennett, Fire & EMS Law,  https://doi.org/10.7945/yex7-xj45 Larry is an educator who has worked with Fire departments all over the nation. A noted educator, his textbook is used by professional groups and universities. Abigail Goben, MLS, is an Associate Professor, Data Management Librarian, and Research Data Policy Advisor at the University of Illinois at Chicago. She teaches Evidence-Based Practice for the College of Dentistry, in the Clinical Informatics program, and a graduate Data Management course. Her current research focuses on student privacy and learning analytics, efficacy of data education, and research data policy. She is a co-investigator for the IMLS funded Data Doubles project. She blogs at HedgehogLibrarian.com and can be found on Twitter as @hedgielib. Session Description: Publishing Data In Repositories - August 10th from 2-3pm The currency of academia has long been the article. However, with supplemental materials in so many formats, the nature of the scholarly output has changed dramatically. Additionally funders and journals are requiring that the evidence for the articles is also available. Repositories are an excellent venue for these additional forms of scholarly, particular the data. In this session, attendees will learn about the nature of changing publication outputs, how repositories can help provide the needed infrastructure to share data and other research outputs, and how to make a bigger impact with your scholarship through publishing in a repository.
    Creator/Author:
    Konecny, Mark; Goben, Abigail; Bennett, Lawrence, and Jason, Don
    Submitter:
    Amy Koshoffer
    Date Uploaded:
    08/19/2020
    Date Modified:
    08/24/2020
    Date Created:
    2020-08-10
    License:
    Attribution-NonCommercial-ShareAlike 4.0 International

  • Understanding Open Access and Open Data

    Media thumbnail: Understanding Open Access and Open Data
    Type:
    Media
    Description/Abstract:
    This webinar was a part of the Data and Computation Science Series and one of five webinars focused on the Publishing Lifecycle of Data. It occurred on July 27, 2020, at 2:00 pm EDT. Due to technical difficulties, the presentation starts at 8:47. The presenter was Claudio Aspesi, Senior Research Analyst. He joined Sanford C. Bernstein & Co., LLC, in 2004 covering European media stocks. Previously he was Global Senior Vice President of Strategy at EMI Music and was responsible for defining the company’s business model as the music industry entered the digital age. Before joining EMI Music in 2002, Mr. Aspesi was a member of the executive team at Airclic, an Internet infrastructure company, and prior to that a Principal at McKinsey and Co., working with many leading media and entertainment companies. Mr. Aspesi graduated with the highest honors from Universita Luigi Bocconi, Milan, with a Laurea in Economia Aziendale. Session Description - Open data and metadata - opportunities, risks, and possible actions Research data is at the core of what universities do. Its value to researchers is, of course, paramount - and open science offers significant benefits to the scientific community. But this data, and the attached metadata, are increasingly valuable for third parties as well. We will discuss how research data and metadata increasingly overlaps with all the other data produced by academic institutions, how it is becoming increasingly valuable outside the academic community, and how it could become even more valuable in the future. The collection, analysis, synthesis and preservation of data and metadata, however, pose significant issues as well; for example, data can and is being used to evaluate individuals (with the biases implicit in developing algorithms to analyze them). More broadly, the collection and analysis of data raises privacy and academic freedom concerns, and so does the lack of transparency and accountability of third party users. Ultimately, the deployment of data analytics and Artificial Intelligence tools should fit with the broader values of the academic community, such as equity and sustainability - whether it does so is controversial. In addition to the need to establish principles for the use of data analytics and Artificial Intelligence, there are also significant ethical questions that need to be addressed, and that pose significant challenges, and there are questions about how to ensure the long term preservation of data and metadata. We will close the presentation with a look at possible steps that the academic community ought to take to address all these issues. We hope that a discussion will follow, in order to address questions and issues, as well as to gather points of view from participants
    Creator/Author:
    Aspesi, Claudio
    Submitter:
    Amy Koshoffer
    Date Uploaded:
    07/28/2020
    Date Modified:
    07/28/2020
    Date Created:
    2020-07-27
    License:
    Attribution-NonCommercial-NoDerivs 4.0 International