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

This is the 3D documentation data for the Pine Grove Rosenwald School, Cumberland County, Virginia; The data was collected by students of ARH5600 : 3D Cultural Heritage Informatics, Fall 2021; data collected with FARO Focus 3D lasers scanners - (1) S120, (2) X130; project in collaboration with former Facilities Management Architectural History Projects Director, Jody Lahendron and the Pine Grove Community in an effort to preserve the building and community culture; one of the earliest Rosenwald Schools, built in 1917; Virginia Dept of Historic Resources listing https://www.dhr.virginia.gov/historic-registers/024-5082/ - VLR Listing Date 12/12/2019, NRHP Listing Date 02/25/2020, NRHP Reference Number MP100005010; community website at https://www.ammdpinegroveproject.com/; Data files can be downloaded below: Coming soon. Contact Will Rourk will@virginia.edu for more info Please credit the University of Virginia Library upon use of this data

3D dataset for the Dunbar Rosenwald School building located in the New Fork community of Fluvanna County, Virginia; data collected and processed by UVA Architecture class ARH3500/7500 : 3D Cultural Heritage Informatics during the Spring 2025 semester; main data registration performed by Victoria Bitrick, undergraduate student in the Program for Historic Preservation in Architectural History at UVA, directed by Andy Johnston PhD; the Dunbar Rosenwald School is owned, managed and directed by Carmen Smith of New Fork, Fluvanna County;

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.

The dataset includes GeoTIFF raster layers representing the predicted probability of each ordinal class. Files are named using a standardized convention that encodes the WASH component and ordinal class name.

R scripts for the data organization, filtering, and analysis of my Doctoral dissertation work focused on the association of Social Determinants of Health and return to sport and long-term outcomes in individuals after anterior cruciate ligament reconstruction (ACLR). There are a total of 9 R scripts across 3 manuscripts. The 'filter' scripts are for data management and filtering to create sub-datasets from the master dataset while the analyses scripts (BLR and LGM) are for the statistical analyses related to each sub-dataset.

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

William Faulkner's pipe; scanned on 2017-01-17 by Will Rourk, Baxter Craven, Molly Schwartzburg; scanned with Creaform Zscanner 700CX; data acquired using Creaform VXElements, processed with 3D Systems Geomagic, Autodesk 3D Studio Max, 3D printed with Stratasys Mojo

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

The data in this set concerns certain books published no later than 1870 and held in the circulating collections of 14 college and university libraries in Virginia and North Carolina. It was collected by University of Virginia student research assistants as part of the project "Book Traces: Civil War Era Readers and Their Books in Virginia Libraries." They surveyed the books on site at the holding libraries, looking for handwritten marginalia and other artefactual traces of the books' historical readers. The data set includes a spreadsheet (in TSV format) of data about the books and representative photos of the marginalia found in them.

This is data from the student rooms in the Academical Village, University of Virginia, east colonnade between Pavilions VIII and X; the pitched roof, constructed ca. 1830s was removed to be replaced by a modern flat roof; the original Thomas Jefferson era serrated roof was revealed during the demolition process and recorded; the roof was recorded using FARO Focus 3D laser scanners; data was processed with FARO Scene v. 2022; data collected with the help of Shaheen Alikhan; data collected 17 June 2022; Data files can be downloaded at the following location: Coming soon. Contact Will Rourk will@virginia.edu for more info 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 is a collection of 3D scan data of artifacts from Thomas Jefferson's Monticello in collaboration with the archaeologists, architectural historians and curators of the Thomas Jefferson Foundation of Monticello and the University of Virginia Library. Please contact Will Rourk for more information regarding this dataset. Please reference and credit the University of Virginia Library and the Thomas Jefferson Foundation at Monticello when making use of this data.

Fralin 3d ; This item is one in a series of 4 collection items from the Fralin Museum that were 3D scanned and 3D printed for the Spring 2017 Exhibit "Collect, Care, Conserve, Curate: The Life of the Art Object"

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;

Supplementary data for Anna Blazier's dissertation entitled "Antimicrobial target discovery with metabolic network models"

The Make to Learn solenoid can be used to explore principles of electricity and magnetism. This solenoid can be used with the Linear Motor in the Engineering Section.

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

These songs from "The Public Domain Song Anthology" are made available here as individual PDFs, XML, and Sibelius files. The introduction to the anthology is also included as a PDF.