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Love Data Week Takes Place February 8–12

Data enthusiasts get ready! Love Data Week is quickly approaching and will be celebrated virtually February 8–12.

The Washington University Libraries, the Bernard Becker Medical Library, and the Institute for Informatics are teaming up to present 10 unique data-related workshops and lectures throughout the week. Join us for one, two, or all 10 of the events! Check out the schedule below and be sure to pre-register to reserve your spot.

Monday, February 8

Qualitative Coding in Atlas TI: 10­–11 am

Join us to learn more about content analysis and discuss its utility in sociological research. This lecture will describe data collection and analysis approaches—with emphasis on the coding process. Drawing from contemporary research, this talk will also address how qualitative data analysis software (e.g., AtlasTI) can aid researchers in identifying key patterns in texts.

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Introduction to Social Explorer: 1–3 pm

Social Explorer provides demographic data from the Census and other sources. Users can access, analyze, and visualize data in the easy-to-use platform. In this workshop, you will learn to access, use, and download data.

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Tuesday, February 9

Introduction to LabArchives for Researchers: 10–11 am

In this introduction to LabArchives, learn how to quickly and easily create an electronic lab notebook to manage your research data securely online.

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Basic Data Analysis Using Python: 1–3 pm

Python is a popular programming language for software development and data analysis. This workshop will introduce basic data analysis in Python and demonstrate the following: data import, exploration and manipulation in Python using the Pandas library, and data visualization in Python using the Matplotlib, Seaborn, and Plotly Express libraries. Hands-on exercises will be presented in the interactive web-based environment Jupyter Notebook.

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Wednesday, February 10

Bloomberg: Database Capabilities, Features, & Uses: 10–11 am

The Bloomberg Terminal brings together real-time data on every market, breaking news, in-depth research, powerful analytics, communications tools, and world-class execution capabilities. Join us to find out more about the tool described and see analysis in action.

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An Overview of the Federal Reserve Economic Data Service: 11 am­–noon

Federal Reserve Economic Data Service (FRED), maintained by the St. Louis Federal Reserve, provides access to over 750,000 financial and data economic data series across 100 public and proprietary data sources. Guest speaker Diego Mendez-Carbajo, Senior Economic Education Specialist of the Federal Reserve Bank of St. Louis, will give the history of FRED, along with features, and how FRED can be used for storytelling and skill building.

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Introduction to Tableau: 1–3 pm

Tableau is a data analysis and visualization tool used to help people see, understand, and make decisions with data. In this two-hour workshop, participants will learn to add and manipulate data, and will create a dashboard to display their data.

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Thursday, February 11

Introduction to MDClone: 10–11 am

MDClone is a free and secure self-service platform for building queries and downloading computationally derived (“synthetic”) data from the Institute for Informatics (I2) research data core (RDC). This webinar will include a demonstration of creating a query to obtain synthetic data.

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Friday, February 12

Visualization of COVID-19 Data Using R: 10–11 am

This workshop will provide an introduction to using R packages for visualization of COVID-19 data. Participants will have the opportunity to learn about the structure of publicly available COVID-19 data and explore methods to visualize the data with an aim to understand the disease epidemiology. Hands-on exercises will be presented in the interactive web-based environment RStudio Cloud.

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The Lion in the Path—The Future of Data Management and Sharing: 1­–3 pm

Carrie Wolinetz, PhD, Associate Director for Science Policy at the National Institutes of Health (NIH), will give a presentation focusing on the future of data management and sharing in the context of the recently announced NIH Policy for Data Management and Sharing.

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