Shenandoah Valley Region (SVR) household neighborhood network database. The database contains 3 networks for the SVR region -- houses within 1 mile, 3 miles, 4 miles network.

The number and duration of contacts between people in a synthetic population of the United States, stratified by CDC age groups and county of residence for each of the contacts.

This file is being shared here to demostrate the file publishing capabilities of the RDE.

Data Documentation and Metadata session from the 2015 Virginia Data Management Bootcamp. Introduces non-structural (data dictionaries, read me files, code books) and structured ways (XML schemas) to document research data.

This is the 3D documentation data for the Sunnyside/Duke Tract House, Charlottesville, Virginia; original structure founding date ca. 1780s; The data was collected (2022-03-04, 2022-03-11) and processed by students of ARH5600 : 3D Cultural Heritage Informatics, Spring 2022; data collected with FARO Focus 3D lasers scanners - (1) S120, (2) X130; data processed with FARO Scene v. 2021; LINKS TO DATASETS ARE FORTHCOMING - contact Will Rourk for more information at will@virginia.edu. Please credit the University of Virginia Library upon use of this data

Data for Science Advances article adx6367, May 2025

3D data of a pony truss bridge removed from its location in Albemarle County, Virginia by VDOT; scanned on site at the VDOT center across from Charlottesville Airport at 3995 Hunterstand Ct; subject was documented using (2) FARO Focus X130 laser scanners; scanning was performed by students of ARH5600 Spring 2019 semester; Please credit the University of Virginia Library upon use of this data

Data centers are among the fastest-growing loads on the U.S. electrical grid. Virginia, the world's largest data center market, is an ideal testbed for analyzing energy and infrastructure impacts. However, researchers and policymakers lack open, consistent facility-level data for effective regional planning and impact analysis. Existing datasets are often inaccurate, outdated, or too expensive for open use. This work introduces an open multi-attribute dataset of 382 data center facilities in Virginia, constructed using \DC (Data Center Satellite-based ENergy and Spatial Estimation), a modular pipeline combining remote sensing, computer vision, machine learning, and statistical models. Each record provides 18 facility attributes: spatial footprint and geometry, construction year, IT whitespace and built-out power capacity, three distinct 24-hour power profiles, and contextual proximity to electrical, transportation, water, and residential infrastructure. Spatial detections achieve Pearson $r > 0.99$ against two independent facility registries; temporal construction year estimates achieve 86.4\% within-one-bin accuracy. The pipeline supports routine re-execution enabling longitudinal dataset updates. The dataset supports energy systems modeling, grid planning, and policy analysis at multiple scales.

This data was collected by students of ARH 5600 : 3D Cultural Heritage Informatics in the Spring semester of 2021. Data files can be downloaded at the following location at Information about the files associated with this dataset can be found in the Read Me file below. Please credit the University of Virginia Library upon use of this data

Ever need to help a researcher share and archive their research data? Would you know how to advise them on managing their data so it can be easily shared and re-used? This workshop will cover best practices for collecting and organizing research data related to the goal of data preservation and sharing. We will focus on best practices and tips for collecting data, including file naming, documentation/metadata, quality control, and versioning, as well as access and control/security, backup and storage, and licensing. We will discuss the library’s role in data management, and the opportunities and challenges around supporting data sharing efforts. Through case studies we will explore a typical research data scenario and propose solutions and services by the library and institutional partners. Finally, we discuss methods to stay up to date with data management related topics.

The repository contains two R code files: data preprocessing and model/prediction/evaluation files.

3D dataset documentation of the underside of the Southern Railway overpass on Emmett Street, Charlottesville, Va, within the grounds of the University of Virginia; this was in connection with VDOT and Facilities Management and was an assigned fieldwork task for ARH5600 : 3D Cultural Heritage Informatics, Fall 2022; student assistants include Junyi Wu and Kelly O'Meara, both graduate students with UVA Architecture; scanned with FARO Focus 3D laser scanners and processed with FARO Scene v.2022;

Fralin 3D ; Laser scan data of greek vase from the Fralin Museum - Skyphos ; Creaform Zscanner 700 CX ; 3D mesh data

Fralin 3D ; Laser scan data of greek vase from the Fralin Museum - oinochoe ; Creaform Zscanner 700 CX ; 3D mesh data

Contains materials for a work in progress - "A Humanist's Cookbook for Natural Language Processing in Python." View the book here (or by starting in the toc Notebook in this upload).

Fralin 3D ; Laser scan data of greek vase from the Fralin Museum - Squat Lekythos, South Italy ; Creaform Zscanner 700 CX ; 3D mesh data

Replication Data for "PM2.5 Disparities in the United States"

The design is for 15 star manipulative. 5 large blue stars, 5 medium green stars, 5 small yellow stars. All stars have holes in the center and can be stacked on one of two base boards. The design is based the book How to Catch a Star by Oliver Jeffers. The book provides the context for the math word problems that will be asked. The manipulative is tactile so students can use objects to think with. This manipulative is targeted to 3 and 4 year olds. It is designed to teach one-to-one correspondence up to 15, patterning, math vocabulary, and addition and subtraction. The goal was to create a manipulative with different colors and sizes that could be used to teach students to count, create patterns, to learn math vocabulary (big, small, compare, different, attribute), and to explore addition and subtraction word problems.

Supplemental material for manuscript titled "Obesity is associated with hyperandrogenemia in a nationally-representative sample of U.S. girls aged 6-18 years" by Su Hee Kim, Aaron F. Pannone, Mark D DeBoer, Christopher R. McCartney, Christine M. Burt Solorzano

3D dataset for bucranium Neoclassical architectural detail from the Pavilion I parlor, Academical Village, University of Virginia; data acquired using a Creaform ZScanner 700 CX color laser scanner and VX Elements v.6 data acquisition software