This document is a supplement to the University of Cincinnati's Power Session workshop presented at Data Day 2019 by Richard Johansen and Mark Chalmers. The goal of this document is to reproduce the step-by-step instructions of the Power Session which demonstrated how to create interactive maps of social vulnerability at the county level. Familiarity with GitHub, R and RStudio environments are highly recommended, but not required to follow this tutorial. For a more in-depth explanation as to how the data was retrieved, cleaned, and manipulated, please refer to the full R script called Mapping_Social_Vulnerability.R located in the Scripts folder of the GitHub repository.
A conversation between two friends who are not musicians and whose personal histories could hardly be more different. Through a series of conversations we explored those journeys, compared and contrasted our stories, and discussed just why this music affects us so deeply. We discussed specific musicians in terms of whether we liked, did not like, or were indifferent to their music, and why we either agreed or not. In these conversations we posed various questions to each other, hoping to discover and articulate certain essences that we might share. One thing we agreed upon up front is that we are neither musicians nor music critics. In fact, we’re not convinced that the field of music criticism is even a valid endeavor. Music description and personal reaction, however, is another matter. In our conversations we tried to describe our reactions to specific musicians and “schools” of music, without labeling the music as “good” or “lousy”. You will see that this doesn’t prevent us from disagreeing and disagreeing in spirited fashion, while always trying to focus on why our personal reaction is what it is.
This document details our process for creating a service catalog for UC Libraries Research and Data Services and our efforts towards offering data science services. In this document, we identify our gaps in knowledge and expertise while making recommendations for filling these gaps.
This document is a workshop workbook for EndNote X8, a citation and reference management software product. The workbook provides descriptions and exercises for most of the major features of EndNote, including program customization, importing & exporting data, organization and management of data, full text recovery & management, cite-while-you-write utility and EndNote Online.
The University of Cincinnati (UC) Libraries' Informationist program and Research & Data Services (RDS) unit provide an extensive program of support for the research community. RDS is a highly-integrated unit of UC Libraries, staffed by informationists in the health sciences, sciences, engineering and social sciences and librarians, specialist staff, and student consultants. Our activities infuse across the institution, including the main campus and the Academic Health Center campus, and we oversee innovative spaces that respond to the particular needs of research communities, including informatics, geospatial analysis and data visualization. Since the fall 2015 CNI presentation on the UC Informationists ("New Roles, New Collaborations: Developing an Informationist Program to Support University Research"), we have greatly expanded our partnerships, services and educational offerings. We are now active in data and statistical consulting, collaborations on bioinformatics education, impactful community engagements (e.g., UC Data Day), and deep partnerships with the UC IT unit on initiatives such as the Data & Computational Science Series. At present, we are pursuing a new and challenging vision to realign our work in order to enable the institution's agendas for data science and innovation. We will discuss our experience with scalable growth and other successes in Research & Data Services and our assessment of a future in data science.
This data set describes the Mann-Whitney U test statistical analysis of the completeness profile for data sets in four institutional repositories. It is a derivative data set from the master data set entitled "Metadata of data sets from four institutional repositories" https://scholar.uc.edu/show/pn89d657h
This data set measures the number of keywords associated with data sets in four institutional repositories. It is a derivative data set from the master data set entitled "Metadata of data sets from four institutional repositories" https://scholar.uc.edu/show/pn89d657h