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On this page
  • Gun Violence Data Hub (Beta): Data Library
  • Analyzing the Data Citation Corpus on Redivis
  • Datapages for interactive data sharing using Quarto
  • Simplifying sharing of national voting data with Redivis
  • Redivis: A Scalable Web Platform for Business Research
  • FAIR Enough: Building an Academic Data Ecosystem to Make Real-World Data Available for Translational Research
  • Data Analysis and Machine Learning Workflows on Redivis
  • Running ML and AI Models on Redivis
  • Expanding Data Horizons with Redivis
  • EIDC in the Classroom: Teaching with the Environment

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  1. Additional Resources

Events and press

Last updated 26 days ago

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Gun Violence Data Hub (Beta): Data Library

The Trace

The Gun Violence Data Hub is working to become the most comprehensive gun violence data resource in the United States. Built on Redivis infrastructure, it is a data library that provides visualizations and entry points for further analysis.

Analyzing the Data Citation Corpus on Redivis

Make Data Count.

Redivis is featured on the Make Data Count blog, where Stanford's Director of Open Scholarship Strategy Zach Chandler uses Redivis to explore and analyze data citations.

Datapages for interactive data sharing using Quarto

Mika Braginsky | Stanford

Mika Braginsky built an interactive data dashboard that uses the Redivis platform as a backend for hosting the underlying data.

Simplifying sharing of national voting data with Redivis

Redivis CEO Ian Mathews co-presented with Graham Straus from UCLA about the way UCLA Library has worked to curate and distribute the L2 Voter File dataset in an accessible, secure format. Redivis allowed us at UCLA to compile 3.4 terabytes of national voting data into a single table that undergraduates, graduates, and faculty can access and easily work with in a secure environment.

Redivis: A Scalable Web Platform for Business Research

Redivis CEO Ian Mathews co-presented with Alex Storer from Stanford GSB Library about their paper written on the use case administering data for business school researchers.

FAIR Enough: Building an Academic Data Ecosystem to Make Real-World Data Available for Translational Research

Data Analysis and Machine Learning Workflows on Redivis

Redivis CEO Ian Mathews presented the Redivis platform as a tool for data discovery and analysis, with a small exploration of ML workflows.

Learn how to utilize Redivis, a data platform used to store and query data on the PHS Data Portal, for every stage of your analytical workflow. This presentation will showcase common methodologies in working with large claims datasets, including scalable cohort generation and analytical workflows in R, Python, Stata and SAS. The session will conclude with an exploration of using modern ML techniques to classify patient notes and other unstructured data.

Running ML and AI Models on Redivis

This training includes a walkthrough on how to get started coding ML and AI workflows.

Expanding Data Horizons with Redivis

EIDC in the Classroom: Teaching with the Environment

| FORCE11 '24 Conference

| PEARC 2024 Conference

| Journal of Clinical and Translational Sciences

| Workshop

| Workshop

Redivis CEO Ian Mathews co-presented with Alex Storer from the Stanford GSB's (DARC) group about running ML and AI Models on Redivis.

|  Workshop

The shared how they are using Redivis to offer datasets and data hosting across campus.

|  Workshop

The (MDI) in Georgetown's McCourt School of Public Policy harnesses modern data and computing power to produce cutting edge social science, computer science, and data science research that improves public policy decision making.

The group within MDI hosted an event to talk about their mission and the resources they'd built using Redivis to accomplish it.

UCLA Library
Stanford Graduate School of Business
Stanford Center for Population Health Sciences
Stanford Center for Population Health Sciences
Stanford Graduate School of Business Library
Data, Analytics, and Research Computing
Carnegie Mellon Libraries
Carnegie Mellon Libraries
Georgetown Environmental Impact Data Collaborative
Massive Data Institute
Environmental Impact Data Collaborative
The Data LibraryThe Gun Violence Data Hub
Analyzing the Data Citation Corpus on Redivis - Make Data Count.Make Data Count
Datapages – datapages
Datapages is built by and at Stanford University
Mika Braginsky
Mike Frank
Simplifying sharing of national voting data with RedivisZenodo
Mathews, I., & Straus, G. (2024, August 1). Simplifying sharing of national voting data with Redivis. Zenodo.
https://doi.org/10.5281/zenodo.13181256
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Redivis: A Scalable Web Platform for Business Research | Practice and Experience in Advanced Research Computing 2024: Human Powered ComputingACM Conferences
PEARC '24: Practice and Experience in Advanced Research Computing 2024: Human Powered Computing Article No.: 58, Pages 1 - 4
Chu I, Miller R, Mathews I, Vala A, Sept L, O’Hara R, and Rehkopf DH. FAIR enough: Building an academic data ecosystem to make real-world data available for translational research. Journal of Clinical and Translational Science 8: e92, 1–9. doi: 10.1017/ cts.2024.530
Link to slides
https://doi.org/10.1145/3626203.3670604
FAIR enough: Building an academic data ecosystem to make real-world data available for translational research | Journal of Clinical and Translational Science | Cambridge CoreCambridge Core
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Training & WorkshopsResearch Hub
Expanding Data Horizons with Redivis | CMU Libraries
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