All Library Events
How Art Survives: David Ohannessian and the Armenian Ceramics of Jerusalem
Intro to ArcGIS Pro
ArcGIS Pro is the newer alternative interface to the tried-and-true ArcGIS Desktop software (ArcMap), with essentially the same functions, but with more of a MS-Office feel. As a native 64-bit program, it also has superior performance. There are a few nice feature enhancements such as multiple layouts in a single project, and it's more fully integrated with ArcGIS Online (see schedule for workshops on ArcGIS Online or on StoryMaps).
ArcGIS Pro can help you analyze or visualize digital data that has a locational component, and we'll discuss starting points for obtaining data. Examples will focus on social science data and feature (vector) layers, but attendees are encouraged to ask questions regarding their own needs and will be welcome to make one-on-one appointments later for more focused instruction. This is an introductory class, and it's not necessary to be familiar with GIS software beforehand.
Attendees should have access to ArcGIS Pro. These are the options for Duke affiliates:
- OIT Download: Current Duke University students, faculty, and staff can get a free copy to install on their own Windows computer, or a Mac with virtual machine software installed (e.g., VMware or Parallels).
- Virtual Computing Manager (VCM) from Duke's Office of Information Technology (OIT) allows Duke users to check out a virtual machine with ArcGIS installed and connect via a remote connection.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Mapping & GIS
R for data science: getting started, EDA, data wrangling
Part of the Rfun series. R and the Tidyverse are a data-first coding language that enables reproducible workflows. In this two-part workshop, you’ll learn the fundamentals of R, everything you need to know to quickly get started. You’ll learn how to access and install RStudio, how to wrangle data for analysis, gain a brief introduction to visualization, practice Exploratory Data Analysis (EDA), and how to generate reports.
Part 1 has no prerequisites and no prior experience is necessary. By the end of part 1 you will import data, edit and save scripts, subset data, use projects to organize your work, and develop self-help techniques.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop. We will use the flipped classroom model. Quickstart videos will be distributed one week prior to the event.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Data Science
Geospatial Data in R: Mapping
This workshop introduces the use of the R language for producing maps. We will demonstrate the advantages of a code-drive approach such as R for visualizing geospatial data. Participants will gain the skills to quickly and efficiently create a variety of map types for a website, presentation, or publication. In addition to working on hands-on coding exercises, we will also review practical guidance on designing effective maps.
Attendees will need basic familiarity with R and RStudio to follow along with the exercises. Knowledge of tidyverse packages such as ggplot2 and dplyr is also helpful.
This workshop is a companion to Geospatial Data in R: Processing and Analysis, which focuses on data analysis more than visualization.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A Zoom link will be emailed to registered participants.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at any time prior to the conclusion of the workshop.
Mapping & GIS, Data Science
ArcGIS StoryMaps
This workshop will help you get started telling stories with maps on the ArcGIS StoryMaps platform. This easy-to-use web application combines interactive maps with narrative text, images, and videos to provide a powerful communication tool for any project with a spatial component. We will explore the capabilities of the platform, share best practices for designing effective stories, and guide participants through the process of creating their own story maps.
No previous experience with GIS is necessary.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A Zoom link will be emailed to registered participants.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at any time prior to the conclusion of the workshop.
Mapping & GIS
Duke Research Data Repository Overview
This workshop will provide an overview of the Duke Research Data Repository and how it can help Duke researchers comply with funder and journal policies as well as meet growing standards around data stewardship and sharing, such as the FAIR Guiding Principles. The general functionalities of the platform as well as tips for submitting data will be discussed. New features will also be demonstrated including a new integration with the Globus platform to support transferring large-scale data.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at any time prior to the conclusion of the workshop.
Data Management
R for data science: visualization, pivot, join, regression
Part of the Rfun series. R and the Tidyverse are a data-first coding language that enables reproducible workflows. In this two-part workshop, you’ll learn the fundamentals of R, everything you need to know to quickly get started. You’ll learn about visualization using ggplot2, how to make interactive charts for use in dashboards, how to reshape and merge data, and be introduced to models.
Part 2 requires the familiarity of part 1. By the end of part 2 you will have a familiarity with the grammar of graphics, be introduced to interactivity techniques, be able to invoke data joins and pivots, and gain an introduction to linear regression.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop. We will use the flipped classroom model. Quickstart videos will be distributed one week prior to the event.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Data Science
Intro to QGIS
Are you looking for an open source option for GIS to make maps or to analyze geospatial data? In this workshop we will demonstrate how to import and analyze data in QGIS and discuss the benefits of using QGIS over other GIS software. In the process, we'll go over some general GIS concepts such as layers, types of GIS files, and projections, with an emphasis on feature (vector) layers. This is an introductory class, and no prior GIS experience is needed.
Attendees should have installed QGIS beforehand.
- Go to the QGIS Downloads webpage.
- Download and install the QGIS Installer for either the latest version or the latest long-term (most stable) release, either 64-bit or 32-bit. Versions for several platforms are available.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Mapping & GIS
Web Mapping
This introductory workshop will teach you how to build interactive online maps. After reviewing fundamental mapping concepts and technologies, we will walk through hands-on activities in Esri's ArcGIS Online. Topics will include: finding geospatial data, designing effective maps, sharing web applications, and using basic spatial analysis tools.
No previous GIS experience is required.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A Zoom link will be emailed to registered participants.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at any time prior to the conclusion of the workshop.
Mapping & GIS
Tools for Data Management
This workshop will introduce data management practices for researchers to consider and apply throughout the research lifecycle. Good data management practices pertaining to planning, organization, documentation, storage and backup, sharing, citation, and preservation will be presented using examples that span disciplines. The second hour of this workshop will offer a mini “tour” of research data management tools including GitHub, LabArchives, OSF, and Tropy and provide a framework for considering how to assess data management tools for future adoption.
This workshop contains similar material to the “Research Data Management 101” workshop offered in past semesters - participants who have attended this previous workshop should not attend.
This workshop (GS717.03) is eligible for 2 hours of Graduate School RCR Credits.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at any time prior to the conclusion of the workshop.
Data Management
Tools for Data Management
This workshop will introduce data management practices for researchers to consider and apply throughout the research lifecycle. Good data management practices pertaining to planning, organization, documentation, storage and backup, sharing, citation, and preservation will be presented using examples that span disciplines. The second hour of this workshop will offer a mini “tour” of research data management tools including GitHub, LabArchives, OSF, and Tropy and provide a framework for considering how to assess data management tools for future adoption.
This workshop contains similar material to the “Research Data Management 101” workshop offered in past semesters - participants who have attended this previous workshop should not attend.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at any time prior to the conclusion of the workshop.
Data Management
PowerPoint Skills for Diagrams
While Adobe Illustrator is my preferred software for producing diagrams, PowerPoint is quite full-featured and a great option for those who don't have access to Illustrator. Plus, any skills you gain drawing diagrams will help you create better presentation slides! In this workshop I'll cover basic shape creation and manipulation in Microsoft PowerPoint, including ways to make your own icons with shape combinations.
Expectations:
- If you need help with something during the session, you'll be expected to share your screen.
- You will be expected to arrive with Microsoft PowerPoint already installed on your computer if you want to work along with me or do the exercises during the workshop!
This event is offered virtually in accordance with Duke's Coronavirus-19 Events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Data Visualization
Geospatial Data in R: Processing and Analysis
The R language has became a popular option for working with geospatial data. Compared to traditional GIS software, the code-driven approach of R can be more reproducible and efficient. This workshop give participants the skills to perform geospatial workflows entirely within R. We will discuss how different types of geospatial data work in R, walk through examples of data operations, and explore common analysis methods for geospatial data.
Attendees will need basic familiarity with R and RStudio to follow along with the exercises. Knowledge of tidyverse packages such as ggplot2 and dplyr is also helpful.
This workshop is a companion to Geospatial Data in R: Mapping, which focuses on visualization more than analysis.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A Zoom link will be emailed to registered participants.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at any time prior to the conclusion of the workshop.
Mapping & GIS, Data Science
Designing a Reproducible Workflow with R and GitHub
Part of the Rfun series. The importance of reproducibility, replication, and transparency in the research endeavor is increasingly discussed in academia. This workshop will introduce foundational strategies that can increase the reproducibility of your work and present a potential end-to-end reproducible workflow using a suite of tools, including git, RStudio, Binder, and Zenodo. Configuration for the hands-on portion of the workshop will be sent to participants one week before the workshop.
Prerequisites:
-
Introductory familiarity with R (consider attending one of our R workshops or watch a prerecorded workshop)
-
A GitHub account
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at any time prior to the conclusion of the workshop.
Data Science, Data Management
Designing a Reproducible Workflow with R and GitHub
Part of the Rfun series. The importance of reproducibility, replication, and transparency in the research endeavor is increasingly discussed in academia. This workshop will introduce foundational strategies that can increase the reproducibility of your work and present a potential end-to-end reproducible workflow using a suite of tools, including git, RStudio, Binder, and Zenodo. Configuration for the hands-on portion of the workshop will be sent to participants one week before the workshop.
Prerequisites:
-
Introductory familiarity with R (consider attending one of our R workshops or watch a prerecorded workshop)
-
A GitHub account
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at any time prior to the conclusion of the workshop.
Data Science, Data Management
Effective Academic Posters
Poster sessions are an incredible opportunity to share our work with a broader audience, get feedback, and network with our peers, as well as potential employers, funders and collaborators. Our careers often depend on performing well in these exciting and often chaotic venues, but few of us are trained in graphic design and visual storytelling! In this talk, I will present some principles for creating an effective academic poster, and introduce you to a group critique process that should help you tell your story more clearly and stand out from the crowd.
You don't need any software installed for this workshop – it is a talk with an interactive portion at the end.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Data Visualization
Mapping in Tableau
Tableau is a software package that is increasingly popular for creating striking visualizations, such as charts and graphs, from tabular data. It also has an increasing number of capabilities to create maps. Source data can include native geospatial files (such as shapefiles or GeoJSON files), but also tabular data (such as CSV or Excel files) that include locational values, such as place names or coordinate data. This workshop will cover how to create maps in Tableau and on ways to manipulate the data and to effectively symbolize it on a map.
You can install Tableau for free as a university student: https://www.tableau.com/academic/students. You need to have it installed before the class.
Expect to receive more information before the day of the workshop regarding some background tasks to complete beforehand to help prepare.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Mapping & GIS, Data Visualization
R case study: public datasets in Google BigQuery using DBplyr
Building on earlier Rfun workshops, exploit your knowledge of familar Tidyverse syntax to query remote databases via RStudio. Attendees will be introduced to the dBplyr package as an alternative to SQL database querying. Following a review of dplyr and an overview of Google BigQuery public datasets, attendees will practice querying Google BigQuery public data.
Prerequisites:
- Introductory familiarity with R and the Tidyverse (e.g. quickStart with R, part 1)
- Have a free Google BigQuery account; BigQuery registration details will be sent in advance
- Install R and RStudio on your computer
- tidyverese, DBI, dbplyr, bigrquery installed in your R environment
install.packages(c("tidyverse", "DBI", "dbplyr", "bigrquery"))
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Data Science
R case study: public datasets in Google BigQuery using DBplyr
Bulding on earlier Rfun workshops, exploit your knowledge of familir Tidyveres syntax to query remote databases via RStudio. Attendees will be introduced to the dBplyr package as an alternative to SQL database querying. Following a review of dplyr and an overview of Google BigQuery public datasets, attendees will practice querrying Google BigQuery public data.
Prerequisites:
- Introductory familiarity with R and the Tidyverse (e.g. quickStart with R, part 1)
- Have a free Google BigQuery account; BigQuery registration details will be sent in advance
- Install R and RStudio on your computer
- tidyverese, DBI, dbplyr, bigrquery installed in your R environment
install.packages(c("tidyverse", "DBI", "dbplyr", "bigrquery"))
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Data Science
Ethics of Data Management and Sharing
This workshop will explore the many different ethical issues that can arise with data management and sharing and strategies to address those issues to ensure that goals set by publishers and funders around reproducibility and reuse can be met. How are researchers expected to comply with data sharing policies and practices when they do not actually own the data or ensure disclosure protection for human participants? Likewise how can researchers ethically collect, handle, and share data from certain communities, such as Indeginous People? Topics covered will include proper consent procedures, de-identification, the impact of privacy laws on data sharing, and the application of diversity and equity principles to open science and data sharing.
This workshop (GS717.04) is eligible for 2 hours of Graduate School RCR Credits.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at any time prior to the conclusion of the workshop.
Data Management
Ethics of Data Management and Sharing
This workshop will explore the many different ethical issues that can arise with data management and sharing and strategies to address those issues to ensure that goals set by publishers and funders around reproducibility and reuse can be met. How are researchers expected to comply with data sharing policies and practices when they do not actually own the data or ensure disclosure protection for human participants? Likewise how can researchers ethically collect, handle, and share data from certain communities, such as Indeginous People? Topics covered will include proper consent procedures, de-identification, the impact of privacy laws on data sharing, and the application of diversity and equity principles to open science and data sharing.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at any time prior to the conclusion of the workshop.
Data Management
R case study: web scraping
Building on knowledge from earlier Rfun workshops, useRs will be introduced to web crawling and HTML parsing. In this introductory web scraping workshop, attendees will use the rvest package to deconstruct a target site into structured data by combining limited knowledge of HTML specifications with a very limited appreciation of the HTTP protocol along with basic Tidyverse-style iteration.
Prerequisites:
- Introductory familiarity with R and the Tidyverse (e.g. quickStart with R, part 1)
- Install R and RStudio on your computer
- tidyverese and rvest packages installed in your R environment
install.packages(c("tidyverse", "rvest"))
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Data Science
R case study: web scraping
Bulding on knowledge from earlier Rfun workshops, useRs will be introduced to web crawling and HTML parsing. In this introductory web scraping workshop, attendees will use the rvest package to deconstruct a target site into structured data by combining limited knowledge of HTML specifications with a very limited appreciation of the HTTP protocol along with basic Tidyverse-style iteration.
Prerequisites:
- Introductory familiarity with R and the Tidyverse (e.g. quickStart with R, part 1)
- Install R and RStudio on your computer
- tidyverese and rvest packages installed in your R environment
install.packages(c("tidyverse", "rvest"))
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Data Science
Introduction to R
Part of the DataFest Workshop Series. R and the Tidyverse are a data-first coding language that enables reproducible workflows. Attendees will learn the fundamentals of R, the Tidyverse, how to wrangle data for analysis, and practice reporting Exploratory Data Analysis (EDA) with R Markdown.
Part 1 has no prerequisites although you will want to download and install R and RStudio (details will be sent a week in advance.) By the end of the workshop you will import data, edit and save scripts, subset data, use projects to organize your work, and develop self-help techniques.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop. We will use the flipped classroom model. Quickstart videos will be distributed one week prior to the event.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Data Science
Meeting Data Management Plan Requirements
There are many federal and private funders who require data management plans as part of a grant application, including NIH who recently released a new Data Management and Sharing Policy that takes effect in 2023 and will apply to all grants. This workshop will cover the components of a data management plan, what makes a strong plan and how to adhere to it, and where to find guidance, tools, resources, and assistance for building funder-based plans. We will also discuss how to make data management plans actionable and meaningful living documents to support research integrity, reproducibility, reuse, and verification of results.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at any time prior to the conclusion of the workshop.
Data Management
Visualization in R using ggplot2
Part of the DataFest Workshop Series. In this workshop we will focus on ggplot2, a library for R that creates clear and well-designed visualizations and that plays well with other tidyverse packages. Attendees will get up and running quickly with ggplot2, going through a variety of examples to learn how to understand, modify, and create ggplot2 visualizations. Building basic skills with visualization will improve your ability to create quick, exploratory visualizations for data analysis as well as more formal, outward-facing visualizations for presentations or publications.
While prior experience with ggplot2 and with other tidyverse packages is not required, some basic familiarity with R is expected. Please consider attending an Introduction to R workshop (or reviewing onling learning materials) before attending this workshop on ggplot2. In this workshop, we will use RStudio and RMarkdown files for all exercises.
Expectations:
- You will be expected to arrive with R, RStudio, and the tidyverse package already installed on the machine you're Zooming from if you want to work along with me or do the exercises during the workshop.
- If you need help with something during the session, you'll be expected to share your screen.
This event is offered virtually in accordance with Duke's Coronavirus-19 Events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Data Visualization, Data Science
R case study: Twitter data
Bulding on knowledge from earlier Rfun workshops, learn how to gather and analyze tweets with the rvest package. Attendees will use R, RStudio, and the Tidyverse to orchestrate Twitter data gathering via the Twitter API.
Prerequisites
- Introductory familiarity with R and the Tidyverse (e.g. quickStart with R, part 1)
- A Twitter account
- Install R and RStudio on your computer
- tidyverese and rtweet packages installed in your R environment
install.packages(c("tidyverse", "rtweet"))
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Data Science
Intro to Geospatial Data
Part of the DataFest Workshop Series. This workshop provides an introduction to the foundational concepts behind geospatial data—data that includes location information. We will focus on the special characteristics of geospatial data that differ from other types of data, and explore how these differences affect visualization, processing, and analysis. Participants will also learn about data types, methods for finding data, and commonly used tools for working with geospatial data.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Mapping & GIS
Intro to Tableau: Easy charts and maps
Part of the DataFest Workshop Series. Tableau Public (available for both Windows and Mac) is incredibly useful free software that allows individuals to quickly and easily explore their data with a wide variety of visual representations, as well as create interactive web-based visualization dashboards. This workshop will focus on using Tableau Public to create data visualizations, starting with an overview of how the program thinks about data, common data manipulation and loading, and the terminology used. Activities will include a sample data visualization and mapping project, which will give people hands-on experience using Tableau’s basic chart types and dashboard creation tools. We will also discuss publishing to the Tableau Public web server and related services and tools, like the full Tableau Desktop application (free for full-time students).
This workshop is designed for beginners who might be comfortable with data and spreadsheets, but have no experience with Tableau, are curious about what it can do, and want to get a quick introduction so they can start playing on their own.
Expectations:
- If you need help with something during the session, you'll be expected to share your screen.
- You will be expected to arrive with Tableau Public or Desktop already installed on the machine you're Zooming from if you want to work along with me or do the exercises during the workshop!
- Tableau is available through the company itself, not OIT
- Tableau Public is free and available for Mac and Windows
- Tableau Desktop is free for students or those doing non-profit research (as defined by Tableau)
This event is offered virtually in accordance with Duke's Coronavirus-19 Events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Data Visualization
Preparing Data for Publishing
In this workshop participants will learn strategies for how to prepare data for publishing by “curating” an example dataset and identifying common data issues. Participants will also learn about the overall role of repositories within the data sharing landscape and apply strategies for locating and assessing repositories. The workshop will include short lectures and group work via break-out rooms.
This workshop contains similar material to the “Research Data Management 201: How and where to publish your data” workshop offered in past semesters - participants who have attended this previous workshop should not attend.
This workshop (GS717.05) is eligible for 2 hours of Graduate School RCR Credits.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at any time prior to the conclusion of the workshop.
Data Management
Preparing Data for Publishing
In this workshop participants will learn strategies for how to prepare data for publishing by “curating” an example dataset and identifying common data issues. Participants will also learn about the overall role of repositories within the data sharing landscape and apply strategies for locating and assessing repositories. The workshop will include short lectures and group work via break-out rooms.
This workshop contains similar material to the “Research Data Management 201: How and where to publish your data” workshop offered in past semesters - participants who have attended this previous workshop should not attend.
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at any time prior to the conclusion of the workshop.
Data Management
Presenting Data Science Results to Stakeholders
Part of the DataFest Workshop Series. This presentation will focus on strategies for developing a short presentation that summarizes a data science project, including: identifying a compelling story in the analysis; leading with the key takeaways; and presenting results simply, effectively, and visually. Communicating with stakeholders is a core process in any data science project. Attendees will learn to construct a visually effective and time-efficient presentation for sharing data science results with your stakeholders to maximize the time you have with them.
NOTE: This is not a hands-on workshop. No special software is required, other than Zoom.
This event is offered virtually in accordance with Duke's Coronavirus-19 Events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Data Visualization
Slides with Rmarkdown: Xaringan
Part of the DataFest Workshop Series. R markdown is a means of applying structure to the prose in your coding document. Using R Markdown and the xaringan package, attendees will integrate code with natural language (i.e. prose) to render presentation slides as a reproducible report. The method of integrating code with prose is known as literate coding. Attendees will focus their energies on rendering slides as one type of report while being introduced to an array of report types that can be generated from the same code.
Prerequisites
- Introductory familiarity with R and the Tidyverse (e.g. quickStart with R, part 1)
- A Twitter account
- Install R and RStudio on your computer
- tidyverese and xaringan packages installed in your R environment
install.packages(c("tidyverse", "xaringan"))
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Data Science
R case study: sentiment analysis
Bulding on knowledge from earlier Rfun workshops, learn basic text mining techniques with RStudio and critical packages. Attendees will analyze public domain novels by Jane Austen, wrangle text-data into submission, tokenize corpora, generate word clouds, and be introduced to introductory sentiment analysis.
Prerequisites
- Introductory familiarity with R and the Tidyverse (e.g. quickStart with R, part 1)
- Install R and RStudio on your computer
- tidyverese, tidytext, janeaustenr, wordcloud2 and packages installed in your R environment
install.packages(c("tidyverse", "tidytext", "janeaustenr", "wordcloud2"))
This event is offered virtually in accordance with Duke's Coronavirus events policies. A zoom link will be sent via email to registered participants to join the workshop.
The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at anytime prior to the conclusion of the workshop.
Data Science