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Feb
16
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The theme for Day 4 of “Love Your Data Week” is “Finding the Right Data”. There’s a lot of open national health data out there– Data.gov’s health portal, and the “Data and Tools” tab on the main page of the National Center for Health Statistics are good sources (also this list of open access data… Read More »
Posted in: Data Science, News From NNLM PNR
Feb
15
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Welcome to day three of Love Your Data Week 2017! Today’s topic is Good Data Examples. What makes data “good” or “well managed?” The Fair Data Principles: Findability, Accessibility, Interoperability, and Reusability are a good place to start. Published by Mark Wilkinson and his colleagues in 2016, these principles “put specific emphasis on enhancing the… Read More »
Posted in: Data Science, News From NNLM PNR
Feb
14
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Welcome to Love Your Data Week 2017! This “5-day international event to help researchers take better care of their data” has participants from all over the United States and also abroad, with everyone posting and tweeting about data (best practices, resources, etc.). The PNR will be posting on our Facebook and Twitter pages, as well… Read More »
Posted in: Data Science, News From NNLM PNR
Jan
18
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The Inland Northwest Health Science Libraries group, in collaboration with libraries at Washington State University, Eastern Washington University, Gonzaga University and area hospitals is bringing the Association of College and Research Libraries workshop, Building Your Research Data Management Toolkit to Gonzaga University in Spokane on Monday, April 10th, 2017. Research data management (RDM) has emerged… Read More »
Posted in: Data Science, News from Network Members, News From NNLM PNR, Training & Education
Dec
30
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The University of Washington eScience Institute, in collaboration with Urban@UW and Microsoft, is excited to announce the 2017 Data Science for Social Good (DSSG) summer program. The program brings together data and domain scientists to work on focused, collaborative projects that are designed to impact public policy for social benefit. Modeled after similar programs… Read More »
Posted in: Data Science, Training & Education