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
All models and corresponding network visualizations are generated from documents in the CORD-19 dataset as of July 14, 2020. All annotations in red were added by the research team.
Note: These topic models are included here as additional reference and to append links to interactive versions on the Digital Scholarship Center’s machine learning platform for further exploration.
All models and corresponding network visualizations are generated from virus related documents in the CORD-19 dataset as of July 14, 2020. All annotations in red were added by the research team.
Note: Certain Non-Coronaviridae topic models are included in the text of this article and are included here only as additional reference and to append links to interactive versions on the Digital Scholarship Center’s machine learning platform for further exploration.
All models and corresponding network visualizations are generated from virus related documents in the CORD-19 dataset as of July, 2020. All annotations in red were added by the research team.
Note: Coronavirus topic models are included in the text of this article and are included here only as additional reference and to append links to interactive versions on the Digital Scholarship Center’s machine learning platform for further exploration.
These Centrality measurements were generated with NetworkX, a Python package for networks. The specific algorithms used for this paper are Betweenness Centrality (where Degree Centrality considers individual topics).
Complete Centrality Data for this research can be found at https://scholar.uc.edu/show/6t053h21x
This dataset contains quantitative and qualitative data about the archaeological remains of fish-salting and fulling workshops throughout the ancient Mediterranean world (Europe, North Africa, and Western Asia), primarily dating to the Roman period. The data provided the basis for the two case studies in the author's dissertation (Motz, C.F. 2021. "The Knowledge Networks of Workshop Construction in the Roman World." Ph.D. diss., University of Cincinnati).
The tables contained in this dataset were exported from the author's FileMaker database. Detailed information about the structure and contents of this dataset may be obtained by consulting Chapter 2 of the author's dissertation.
Data set and code for paper "Population extinction and metapopulation synchrony: a reassessment"
The data consists of Z-transformed correlations and ranks in population growth among treatment and experimental populations of the butterfly Parnassius smintheus before during and after experimental extinction.
A second file contains the number of pair-wise dispersal events for these populations during the same period.
R files used to run the analysis are also included.
Published in conjunction with the below manuscript, this database includes all the output files from a grid search across a design domain governing elastomeric tilted beams according to a Fourier series-based parameterization. For full details, please reference the text. For a description of this database's organization, please see "ReadMe.txt."
Yoo, D., Hertlein, N., Chen, V. W., Willey, C. L., Gillman, A., Juhl, A., Anand, S., Vemaganti, K., and Buskohl, P. R. (2021). "Bayesian Optimization of Equilibrium States in Elastomeric Beams." ASME. J. Mech. Des. 143(11): 111702. https://doi.org/10.1115/1.4050743
Data collected to identify use of special education vouchers in OH, GA and FLA and if information provided regarding loss of least restrictive environment civil rights.
