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.
Art plays an important role in helping people make sense of complex data in new and exciting ways. Able to see the patterns in data, artists and scientists alike translate information into visual and aesthetic forms that increase awareness and make complicated issues and ideas easier to understand.
From January 21 through the month of February, an exhibit featuring artwork influenced by science, technology, or data science will be on display in the Hub Central Lobby at the Discovery Building (300 N. Orchard Street). The exhibit will be featured alongside a new permanent piece by nationally recognized artist Melanie Stimmell, depicting diversity within science.
The Data Science Research Bazaar is still open for registration—until January 2! It’s free for UW-Madison students, faculty, and staff. We have also extended the deadline for submissions to the art exhibit until December 20, and encourage members of the campus and the community to submit artwork!
The Research Bazaar is also sponsoring two Pre-Bazaar workshops where researchers can choose between Software Carpentry or Reproducible Research on Day 1 and R and Python workshops on Day 2.
A recent study out of Vanderbilt University suggests that peer reviewed articles with pre-prints may be associated with higher attention and citation scores. A different study out of the Alan Turing Institute indicates that the same may be true for research papers that make their data openly available.
The Banana Data Podcast, a data science focused podcast, is a fun and entertaining way to stay up to date on the latest trends, tools, and issues in the field.
WIRED explores machine learning and the potential – and limitations – of art created by AI.
The November 2019 issue of Spheres Journal for Digital Cultures is dedicated to artificial intelligence including articles on topics ranging from decolonizing data science to machine translation.
In October, the UW System Board of Regents approved a Data Science undergraduate major allowing students at UW Madison to gain expertise in a cutting edge field.
UW Madison DoIT put together this 3-2-1 guide for data backup strategies to help you ensure you never lose your data.
Art has an important role to play in helping the public make sense of complex data in new and exciting ways. Able to see the patterns in the data, artists and data scientists alike, translate information into visual and aesthetic forms that increase awareness and make complicated issues easier to understand. The planning committee for UW-Madison’s Data Science Research Bazaar seeks submissions for artwork influenced by data science or created by data scientists for display. We welcome submissions from both campus members and the public, and encourage submitters to think broadly on the intersections between data science and art.
Cross-posted from the Data Science Hub
The Data Science Hub is excited to invite you to participate in the inaugural Data Science Research Bazaar by submitting your ideas to present!
UW-Madison’s Data Science Research Bazaar is a practical, two-day, hands-on, unconference-style event for all members of the UW-Madison campus community who are interested in data science, from expert methodologists to novice learners just getting their feet wet with data science tools. Presenters from all disciplines, all UW-Madison affiliated individuals, and individuals from the surrounding Madison area are encouraged to apply. Help make the Research Bazaar a successful exchange of ideas and skills by participating and submitting your idea to present. The Research Bazaar is happening at the Discovery Building on January 24-25, 2020.
Proposals are due on November 15, 2019, unless otherwise noted in a specific call.
The Research Bazaar is seeking proposals for the following presentation formats and workshops:
The Research Bazaar is also seeking proposals for the following networking opportunities:
If you have any questions, please send an email to firstname.lastname@example.org.
A new book by Jeffrey Stanton from Syracuse University School of Information Studies, An Introduction to Data Science, is now available for free download.
The book–which uses R code to illustrate examples–begins with a clear definition of Data Science: Data Science refers to an emerging area of work concerned with the collection, preparation, analysis, visualization, management and preservation of large collections of information.