A newly designed banner with a graphic of mascot Bucky Badger’s face hangs between the columns of Bascom Hall at the University of Wisconsin-Madison during autumn on Oct. 27, 2014. In the foreground is the Abraham Lincoln statue and pedestrians walking across Bascom Hill. (Photo by Jeff Miller/UW-Madison)
If your time as a researcher or student at UW-Madison is coming to an end, good luck with your new opportunities! As you make the shift, it’s important to begin the process of off-boarding – taking all the necessary steps to ensure a seamless transition when formally separating from the university.
This is especially important when it comes to your research data. Off-boarding requires a careful assessment of all the data, accounts, and tools you have used while at UW-Madison and an understanding of policies on transitioning your research data to your collaborators, departments, or new institutions.
To help, we have put together this brief guide. But remember, many labs, departments, and colleges have their own off-boarding procedures, so it’s best to inquire there for more specific guidance. UW-Madison has also gathered some role-specific resources to get started.
UW-Madison’s American Family Insurance Data Science Institute has posted a collection of COVID-19 resources that demonstrate the contributions data science can make to better understanding the virus. These resources include projections for the virus’ spread and treatment, visualizations, research datasets and code bases, as well as stories about how data scientists are helping the efforts to combat the virus.
Semantic Scholar has made the COVID-19 Open Research Dataset (CORD-19) accessible online for download and analysis. Access to the data provides researchers with an opportunity to apply the newest methods of analysis to the data to aid in understanding the virus. The dataset was prepared through a partnership between leading researchers and the Allen Institute for AI.
In their series called Chart Chat, Tableau has shared a discussion of COVID-19 data visualizations. It covers the history of pandemic visualizations, different iterations of what flattening the curve might look like, and how to use data responsibly in visualizations.
Open access publisher, Frontiers, has developed a portal that connects researchers studying the COVID-19 virus to sources of funding. In addition to listing open funding calls, the portal features a dashboard that presents essential information about funding requirements, deadlines, and organizations, all of which streamlines the search for funding for researchers. You can also find resources for COVID-19 research funding, general funding, and tools to help throughout the award lifecycle from UW Madison’s Research and Sponsored Programs.
To help during the COVID-19 related campus closure, DoIT shares technology for working remotely and technology for learning remotely.
Happy New Year’s! The start of a new year and a new semester are as good a time as ever to evaluate your data management practices. Here are some reminders about data management best practices, groups on campus who can help you with managing your data, and some upcoming opportunities for you to sharpen your skills.
What Is Kaggle?
Kaggle is an online community of data scientists and machine learners, owned by Google. Kaggle began in 2017 as a site that offered machine learning competitions, and has since expanded into a public data sharing platform, as well as a host for machine learning educational services.
From September 3-5, the Workshop on Open Citations was held in Bologna: researchers, scholarly publishers, funders, policy makers, and advocates for open citations gathered to present new tools and practices for the creation, management, and reuse of citation data, and to participate in a hackathon.
Information from DMPTool
Research Data Services is excited to share that DMPTool released version 3 on February 27, 2018! For those unfamiliar with DMPTool – it is a tool that can help you understand the data management plan (DMP) requirements from federal funders, write your own DMP, and share your DMP with others.
DMPTool noted that the new version includes the following updates –
To access DMPTool with your UW-Madison NetID, visit DMPTool and click “Sign In” on the upper-right hand corner of your screen. From the drop down menu that appears, select option 1, “Your Institution”. Type “Wisconsin” into the text box that appears and select “University of Wisconsin-Madison” from the options and select “Go”. From there the NetID process should appear as usual.
RDS team will be updating the DMPTool with more UW-Madison specific help in the future, so be sure to keep an eye on the blog for that announcement! Until then, if you have any questions about DMPTool, feel free to contact us!
Written by Chiu-chuang Lu Chou; Information adapted from OpenICPSR
OpenICPSR is a self-serving data repository for researchers who need to deposit their social and behavioral science research data for public access compliance. Researchers can share up to 2 GB data in OpenICPSR for free. Researchers prepare all data and documentation files necessary to allow their data collection be read and interpreted independently. They also prepare metadata to allow their data be searched and discovered in ICPSR catalog and major search engines. A DOI and a data citation will be provided to the depositor after data are published.
Depositors will receive data download reports from OpenICPSR. All OpenICPSR data is governed by the Attribution 4.0 Creative Commons License. Server-side encryption is used to encrypt all files uploaded to OpenICPSR. Data deposited in self-deposit package are distributed and preserved as-is, exactly as they arrive without the standard curation and preservation features available to professional curation package.
OpenICPSR offers Professional Curation Package to researchers, who like to utilize ICPSR’s curation services including full metadata generation and a bibliography search, statistical package conversion, and user support. The cost of professional curation is based on the number of variables and complexity of the data. To learn more about OpenICPSR, please visit their website