IFLA SCITECH Webinar: Text and Data Mining Work at Virginia Tech University Libraries
Virginia Tech University Libraries have been providing Text and Data Mining (TDM) support within the recent years in multiple ways. TDM work has incorporated many individuals from faculty, students, and librarians, Through a panel of experts, this webinar will describe how TDM work and awareness was established in Virginia Tech’s University Libraries, how students were involved, and how faculty have been involved. The panel discussion will include projects related to the analysis of open access articles in health science, how to identify unique language descriptors from whiskey reviews, implementing TDM in digital humanities, and how the establishment of a committee supports TDM related activities within the library.
Sponsored by IFLA Science & Technology Libraries Section
Dr. Anne M. Brown is an Assistant Professor in Research and Informatics, University Libraries, Virginia Tech and an affiliate faculty member in the Department of Biochemistry and Academy of Integrated Science. She collaborates and assists researchers and students (grad and undergrad) involving the integration of computational thinking and discipline-specific computational tools into their research or classroom. She consults on varying levels of data analysis, data publishing, and data visualization.
C. Cozette Comer is the Evidence Synthesis Services Coordinator at the University Libraries at Virginia Tech. She partners on and provides support and educational opportunities for evidence synthesis methods such as systematic reviews and meta-analyses. In 2019, Cozette led the reestablishment of the Text and Data Mining Groups at the Libraries as a means to learn more about ways to leverage TDM approaches for evidence synthesis.
Dr. Chreston Miller is currently an assistant professor and the Data and Informatics Consultant within Data Services of the University Libraries at Virginia Tech. He provides consulting services for researchers at Virginia Tech centered around data-related challenges. His focus has been in Machine Learning/Deep Learning but supports a wide array of data-related areas such as data wrangling and data sensemaking. Dr. Miller’s current research interests are Applied Machine Learning, specifically Natural Language Processing, Human Behavior Analysis, and Human-Centered Computing.
Nathaniel D. Porter is the Data Education Coordinator and Social Science Data Consultant in the Virginia Tech University Libraries and Sociology department. His research is focused on best practices for non-traditional data and experiential learning with data.
Michael J. Stamper is the Data Visualization Designer and Consultant for the Digital Arts at Virginia Tech Libraries. He advises and supports administrators, faculty, students, and the general public with their data visualization and information design wants and needs. He helps to lead users through design processes, define and refine requirements for projects, and performs user research on projects if time allows. He specializes in creating effective and insightful designs that communicate what audiences need to know. He also specializes in user interface (UI) design, user interaction (IxD) and user experience design (UX). He is an advocate for bringing more aspects of Design Thinking into projects, all the while integrating aspects from the visual arts, graphic and interaction design, and the sciences to creating more effective, meaningful, and insightful visualizations and experiences with scientific research.