Minimal anonymized data set for replication of study findings

We created an interactive dashboard that allows a clinician or researcher to easily compare their patient’s or research participants patient-reported, physical function, or strength data to the age-, sex-, and graft-specific reference values published by Kuenze et al. Instructions: The user can enter the sex, age, and graft source of their patient as well as the patient’s data for any or all the patient-reported, physical function, or strength measures included in this study into to corresponding boxes which are outlined in red. After doing so, the values in the “Overall”, “Sex”, “Age”, Age/Sex”, and "Graft" columns will automatically update to reflect the decile in which the patient falls for the overall sample, the sample of patients of the same sex or age group, and the sample of patients in their sex and age group. Reference Value Tables: We have also included detailed descriptive information for each patient-reported, physical function, or strength measure within the overall sample (Tab 2) and separated by biologic sex (Tab 3), age group (Tab 4), biologic sex in each age group (Tab 5), and graft source (Tab 6).

39,264 IDs for tweets related to the Charlottesville KKK rally on July 8, 2017. These tweet IDs matched a search for 'Charlottesville KKK OR #charlottesvilleKKK OR #blocKKK or #blocKKKparty'. These tweet IDs were collected with the twarc command line tool from Documenting the Now. Using twarc's hydrate command, researchers can retrieve the full content of those tweets—with additional metadata provided by Twitter's API—provided the tweets still exist.

Datasets and code for the Social Impact Data Commons Broadband data area.

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.

We examined naming authority and author name clustering in academic works. Specifically, we focused on a collection of reports from the University of Virginia’s Computer Science Department. Our research yielded a test list of names and a resulting file that correctly groups names referring to the same author, to the best of our knowledge

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 Coming soon. Contact Will Rourk will@virginia.edu for more info 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

This repository contains the dataset and code for the manuscript: Zimmet AM, Sullivan BA, Moorman JR, Lake DE, & Ratcliffe SJ. Trajectories of the heart rate characteristics index, a physiomarker of sepsis in premature infants, predict Neonatal ICU mortality. JRSM Cardiovascular Disease 2020. https://doi.org/10.1177/2048004020945142. ABSTRACT OBJECTIVE: Trajectories of physiomarkers over time can be useful to define phenotypes of disease progression and as predictors of clinical outcomes. The aim of this study was to identify phenotypes of the time course of late-onset sepsis in premature infants in Neonatal Intensive Care Units. METHODS: We examined the trajectories of a validated continuous physiomarker, abnormal heart rate characteristics, using functional data analysis and clustering techniques. PARTICIPANTS: We analyzed continuous heart rate characteristics data from 2989 very low birth weight infants (<1500 grams) from nine NICUs from 2004-2010. RESULT: Despite the relative homogeneity of the patients, we found extreme variability in the physiomarker trajectories. We identified phenotypes that were indicative of seven and 30 day mortality beyond that predicted by individual heart rate characteristics values or baseline demographic information. CONCLUSION: Time courses of a heart rate characteristics physiomarker reveal snapshots of illness patterns, some of which were more deadly than others. SOURCE OF ORIGINAL DATASET The dataset was originally collected for the following trial of a display of the Heart Rate Characteristics Index (using the HeRO Monitor made by Medical Predictive Science Corporation): Moorman JR, Carlo WA, Kattwinkel J, et al. Mortality Reduction by Heart Rate Characteristic Monitoring in Very Low Birth Weight Neonates: A Randomized Trial. J Pediatr 2011; 159: 900-906.e1. Culture result information was curated originally for the following manuscript: Weitkamp, J., Aschner, J.L., Carlo, W.A. et al. Meningitis, urinary tract, and bloodstream infections in very low birth weight infants enrolled in a heart rate characteristics monitoring trial. Pediatr Res 87, 1226–1230 (2020). https://doi.org/10.1038/s41390-019-0701-4

The Fraction Orange is a sphere partitioned into two hemispheres; one hemisphere is further partitioned into fourths, eighths, and sixteenths of the whole; the other hemisphere is further partitioned into sixths and eighteenths. The Fraction Orange manipulative is a particularly useful tool for exploring the measurement meaning of division. It’s also useful for teaching fractions through multiple representations, like drawings of partitioned wholes and symbols of the form.

Virginia Standards of Learning Test Scores collected by the Virginia Department of Education (VDOE)

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.

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.

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

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 the 3D documentation data for the St John Rosenwald School, Cobham, Albemarle County, Virginia; building construction date 1922; The data was collected by students of ARH5600 : 3D Cultural Heritage Informatics, Spring 2022; 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 Cobham Community in an effort to preserve the building and community culture; for more information regarding the preservation of this school building please visit the community website at https://www.stjohnfamilylife.org/history.html 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

scan data of The Aviator by Gutzon Borglum, data collected with a FARO Focus 3D 120 scanner

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.

Datasets and code for the Social Impact Data Commons Financial Well Being data area.

All documents and the associated metadata that have been published by the project so far, primarily as early access records. Early Access documents are first versions. They are raw transcriptions that have been proofread once and published, with the goal offering public access as soon as possible to Julian Bond's voluminous works. Early Access documents may contain errors. Over time, the editors will verify all transcriptions, add annotations, and replace Early Access versions with final versions collected in one complete Julian Bond Papers Digital Edition. Our staff is indebted to the many other projects who have established the Early Access process, including Founders Online and the Jane Addams Papers.

Datasets and code for the Social Impact Data Commons Demographics data area.