Link Roundup October 2020

Cameron Cook

This week we’re celebrating International Open Access Week! This year’s theme is “Open with Purpose: Taking Action to Build Structural Equity and Inclusion.” Checkout the UW-Madison Open Access Week page for a full schedule of all the events and actions we have planned this week!

Check out this first part of a series calling for the use of a Black feminist data analytical framework:  A Review of COVID-19 Intersectional Data Decision-Making: A Call for Black Feminist Data Analytics, Part 1, by Kim Gallon, Director and Co-Founder of COVID Black

Open Access Week: Towards a Multilingual Approach

The theme for this year’s International Open Access Week is “Open with Purpose: Taking Action to Build Structural Equity and Inclusion.” This is a time to reflect on how “the systems and spaces of the present are often built upon legacies of historic injustice” and to “examine who these spaces and systems are designed for, who is missing, who is excluded by the business models we use, and whose interests are prioritized.” (The 2020 Open Access Advisory Committee) In the spirit of this year’s theme, and with the intent of using a truly international lens, it’s important to highlight the need to incorporate multilingual approaches to the tools we use, the norms we adopt, and the research we undertake or publish. Below are a few suggested readings that can help you get started on understanding the structural barriers to multilingualism and how to overcome them. 


An Interview with the Wisconsin Census Research Data Center (WiscRDC)

We spoke with Robert Osley-Thomas, Census Administrator at the WiscRDC, to learn more about the WiscRDC and how they support researchers. 

Can you tell us a little bit about the WiscRDC? Its history, purpose, and services?

The Wisconsin Census Research Data Center (WiscRDC) provides Wisconsin researchers the opportunity to perform statistical analysis on non-public Census microdata in a secure computing environment. Through the WiscRDC controlled environment, researchers with approved projects are able to analyze censuses and surveys from the U.S. Census Bureau, health data from the National Center for Health Statistics (NCHS) and the Agency for Healthcare Research and Quality (AHRQ), and a growing collection of other data resources from across the federal government, including the Bureau of Labor Statistics, Bureaus of Economic Analysis. 


Quality Assurance in Research

In research contexts, quality assurance (QA) refers to strategies and policies for ensuring that data integrity, quality, and reliability are maintained at every stage of the project. This includes strategies for preventing errors from entering the datasets, taking precautions before data is collected, and establishing procedures while data is used in a study.