R for data science: getting started, EDA, data wrangling

This working is 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

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Souvenirs of leisure and entertainment in the late Ottoman Empire

Registration Required: https://duke.zoom.us/meeting/register/tJIqd-uqqz8rGNRKs2oAiZvA_K6BOo5n-61t Art historian Berin Golonu will discuss the production of leisure space by looking at selections of Ottoman and Turkish Republican postcard imagery held in the Duke Libraries. Golonu is currently working on a book project on Ottoman sites of leisure referred to as public gardens or "people's gardens," which were modeled after European-style urban parks. Golonu will look at how these gardens replaced older sites of leisure in Thessaloniki and Istanbul, and contextualize their imagery with Ottoman novels, newspaper columns, or memoirs of the day. As public, semi-public and social spaces, these gardens can be viewed as a symptom and cause of the modernizing changes remaking Ottoman society during the late nineteenth and early twentieth centuries. Bio: Born in Istanbul, Berin Golonu holds a PhD from the Visual and Cultural Studies Program at the University of Rochester, an MA from the California College of the Arts and a BA from Vassar College. Golonu's research interests include Ottoman and Turkish modern art and visual culture, art and environmentalism in developing Asian countries, and photographic histories of the Middle East. She is currently working on a book titled People's Garden's: Structuring Public Leisure Space in the late Ottoman Empire which traces the establishment of European-style public parks in key Ottoman cities during the late 19th & early 20th centuries.

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Data Science Tools Showcase: Spatial Analysis

Some people who want to do spatial (geographic) analysis don’t know GIS software such as ArcGIS Pro or QGIS, but do know R or Python. In this workshop, we will present a command-line, or code-driven, approach to working with geospatial data. This method offers several advantages over traditional GIS software that can make your work easier, faster, and more reproducible!

We will share a showcase of spatial data science workflows that demonstrate the possibilities opened up by tools available from the command-line and scripting for processing, analyzing and visualizing data.

This workshop would be helpful for participants with some GIS experience who want to expand their data science toolkit, or for those who currently use R and/or Python and are curious about the geospatial capabilities of these languages.

Some basic familiarity with programming in R and/or Python will make this workshop more useful. We encourage anyone without this background to attend (or watch a recording of) our Introduction to R or Python for Data Science workshops.

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

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R for data science: visualization, pivot, join, regression

This workshop is 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

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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.

1. Windows: Go to the QGIS Downloads webpage.
2. Mac: Go to the QGIS Downloads webpage, or go to the Mac OS X QGIS download page from KyngChaos.com. Please see instructions regarding GDAL and Python packages you may need to install before QGIS, if they're not already on your computer.

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

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Research Data Management 201: How and where to publish your data

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 builds upon the foundational concepts covered in the Research Data Management 101 course offered earlier this semester. Data management practices help researchers take care of their data throughout the entire research process from the planning phase to the end of a project when data might be shared or “published” within a repository.

Participants are not required to have taken a Research Data Management 101 course (although it is recommended). This workshop is also a reconceptualization of the previously offered “RDM 201: Preparing Your Data for Publishing” and “Finding a Home for Your Data: An Introduction to Archives and Repositories” workshops offered in previous semesters - participants who have attended these previous workshops 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.

This workshop is eligible for 2 hours of Graduate School RCR Credits.

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 Management

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Paper Maps for Digital Projects

Do you want to incorporate paper maps into a digital project? Overlaying scanned maps can help illustrate change over time, offer additional context, provide a visually appropriate background, and give access to spatial data not available in other formats.

This workshop will teach you how to bring paper maps into modern GIS applications. We will cover concepts and techniques related to georeferencing, the process of aligning map images with the correct locations on the earth. We will also create new GIS data by extracting features from scanned maps. Tutorials will present steps in several desktop and web-based tools. In addition to learning the software, we will discuss some challenges of working with historical maps.

Prior experience with desktop GIS software is helpful but not required. If you have no experience with GIS, we encourage you to attend Introduction to ArcGIS Pro or QGIS prior to this workshop.

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

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Sallie Bingham Reads from her books: "Treason" and "The Silver Swan"

Join us for readings and conversation with Sallie Bingham, author of two new books "Silver Swan: In Search of Doris Duke" and "Treason: A Sallie Bingham Reader." Sponsored by the Sallie Bingham Center for Women's History and Culture, which was endowed by Bingham and is named in her honor.

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Mapping with R

R has become a popular and reproducible option for supporting spatial and statistical analysis. This hands-on workshop will demonstrate how to plot x/y coordinates; how to generate thematic chloropleths with US Census and other federal data; import GIS shapefiles; and create interactive maps on the web. The focus will be on mapping (making a visual). Please see the schedule for related workshops that focus on performing geospatial analysis using R, and that showcase some of the geospatial work that you can do with programmic tools such as R and Python.

Prerequisites:

• Required (or equivalent): Intro to R. All attendees are expected to be basically familiar with R, R Studio, and the Tidyverse.
• Strongly recommended: Visualization with ggplot2

On your laptop, you must install R and some packages. Follow the steps below to prepare.

1. Install R & RStudio in advance (instructions), or use a cloud version of R.
2. Install the tidyverse, tidycensus, tigris, and sf packages in advance (instructions)

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 Science

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ONLINE Exhibit Opening and Lecture: Creativity and Mental Health

This event is being offered virtually. A Zoom link will be emailed to registered participants to join. Please register to attend.

In honor of Mental Health Awareness Week, join us for a panel discussion on mental health and creativity.

This year marks the 30th anniversary of the publication of William Styron's Darkness Visible, a memoir of his own severe depression and recovery, a work that helped to break the silence around the illness and proved revelatory to his readers and others with depression. Styron's papers are held at Duke.

Panelists will include James L. W. West III (Professor of English Emeritus, Pennsylvania State University), author of William Styron: A Life (1998), and Sneha Mantri, M.D., M.S., neurologist and Director of the Trent Center's Medical Humanities Program. Additional speakers and Rubenstein librarians will also share information about the manuscripts in the Williams Styron papers and about mental health resources at Duke.

The event will include recorded talks followed by a live virtual question and answer webinar session with the speakers. All are welcome to join the conversation, or to submit questions and comments anonymously.

The event will also serve as a virtual opening to an exhibition exploring mental health and creativity.

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Reproducible Research: Tips and Tools

The importance of reproducibility, replication, and transparency in the research endeavor is increasingly discussed in academia. This workshop will introduce foundational data management strategies that can increase the reproducibility of your work. Participants will engage in peer-to-peer discussions to assess common reproducibility challenges and will learn about specific tools and protocols that you might use within your research workflows including the TIER protocol, git and GitHub, and online containerization tools such as Binder and Code Ocean.

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.

This workshop is eligible for 2 hours of Graduate School RCR Credits.

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 Management, Data Science

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The "Science" of Publishing in Academia

From traditional to open access journals. How scientific publishing has changed in the past years and where is it heading? Will traditional journals adapt their business models and co-exist with open access journals or will they disappear? Is publishing in peer-reviewed publications as important for Academia as it used to be? How the current Pandemic affects the "changing game"? How could universities impact the future of science publishing and what are some of the possible implications of the "scientific publishing revolution" for the Duke researchers? REGISTER: http://duke.is/DLdTr6 Zoom information will be sent registrants by email.

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SSRI~ Workshop: Evaluation 101 - Assessing Impact and Informing Improvement

This session offers an overview of program evaluation and evaluation research, or the systematic investigation of the merit, worth, or significance of an entity/initiative. Topics covered will include: when and why to conduct evaluation; types of evaluations; key aspects of an evaluation, including logic model development, data sources and data collection, analysis and reporting, and guiding resultant programmatic change; and tips for feasibly and effectively implementing evaluation in an entity or initiative. This session may be of particular interest to: individuals working in initiatives or entities that are looking utilize evaluation to inform decision-making, as well as faculty, graduate students, undergraduates or others who are interested in evaluation and related partnered/applied research. Please click "More Event Information" (box below) to register.

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Digital Humanities: Acquiring and Preparing a Corpus of Texts (RCR)

Before you can undertake automated text analysis, it's necessary to obtain a corpus of digitized texts and, in many instances, take steps to prepare them for further processing. This hands-on digital humanities workshop focuses on the technical dimensions of corpus development. We will explore:

• the risks and benefits of optical character recognition (OCR)
• file formatting and naming issues
• organization strategies for large corpora
• problems of data cleaning and preparation
• common sources for textual research data; and
• common legal concerns around the use of textual corpora.

This workshop is open to all graduate students and is offered for Responsible Conduct of Research (RCR) credit as GS717.08. Priority registration will be given to students who intend to receive RCR credit.

Zoom information will be emailed to participants in advance of the session.

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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.

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

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Python for Data Science: Pandas 103

Data exploration In Python using grouping and aggregation. This is an intermediate-level, live teaching session where you will learn how to use the Pandas module for exploring tablular (spreadsheet) data using the groupby() and pivot_table() functions, as well as some visualizations of results.

Python can be a great option for exploration, analysis and visualization of tabular data, such as spreadsheets and CSV files, if you know which tools to use and how to get started. This workshop builds upon the introductory Pandas workshops I gave in Fall 2019 and Spring 2020. (Code repository. See below for recordings.) In Pandas 101, I covered the very basics of how to access your data in a Panda DataFrame and do some basic plotting. In Pandas 102, I introduced how to get data into a "tidy" form, and merge datasets (like doing an SQL JOIN). In this Pandas 103, I will show you some of the way you can explore patterns in data by aggretating across categories and time. This is similar to the process of data exploration in Tableau, but here with Python, Pandas and JupyterLab.

• If you don't have any programming experience, or you have never used Python at all before, the material may be too confusing to be useful. I won't be teaching the language itself.
• If you have at least a little bit of Python exposure, but haven't used Pandas much or at all, I would advise watching at least the Spring 2020 Pandas 102 video before you attend. If you find that too advanced, or want a more complete introduction to Pandas, start instead with the Fall 2019 Intro to Pandas video.

Expectations:

• You will be expected to have your video on for at least part of the session, although we won't be doing any group work or sharing.
• If you need help with something during the session, you'll be expected to share your screen.
• You will be expected to arrive with the Anaconda Python distribution already installed on the machine you're Zooming from if you want to work along with me or do the exercises during the workshop!
  • They now call this the Anaconda Individual Edition, available for Mac, Windows, or LInux
  • I would advise installing just for yourself, not for all users (installs in your Users directory, and doesn't need administrator priviledges)
  • I will hold open Zoom walk-in hours for an hour before the workshop to help remotely troubleshoot installation issues. Email me at emonson@duke.edu to get the URL.

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, Data Visualization

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SSRI~ Workshop: Community-Partnered and Community-Engaged Research

Engaging and partnering with community members and entities in research, sometimes in the form of research practice partnership (RPP), can be a powerful mechanism for fostering social change and ensuring that research is appropriately situated within context. This session will focus on what these and related concepts mean, the ways in which they can be relevant and meaningful for both researchers and community entities, core challenges encountered, and recommendations for enacting these principles in practice. Please click "More Event Information" (box below) to register.

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