Digital Humanities and Data Analysis Workshops
The following workshops on research methods and software will be offered by the New Brunswick Libraries Graduate Specialists in Spring 2018. All workshops will be held on the 4th floor of Alexander Library on College Avenue. Room assignments and workshop instructors noted below.
More detailed descriptions of the workshops will be posted as they are made available at https://libguides.rutgers.edu/graduatespecialist/workshops.
Workshops held in rooms 413 and 415 are capped at 20 registrants. Workshops held in the Digital Humanities lab are capped at 12 registrants.
Workshops are grouped by instructor in the categories of Quantitative Methods, Digital Humanities, and Data Analytics.
Please sign up for the workshops you plan to attend at the following links:
Alex Leslie, Instructor
- Wednesday, March 21, 10:00-11:00 am (DH Lab)
- Tuesday, March 27, 10:00-11:00 am (DH Lab)
- Monday, April 2, 1:00-2:00 pm (DH Lab)
- Thursday, March 8, 10:00-11:00 am (DH Lab)
- Monday, March 26, 1:00-2:00 pm (DH Lab)
- Thursday, April 5, 10:00-11:30 am (Room 413)
- Monday, April 9, 1:00-2:30 pm (Room 413)
- Thursday, April 12, 10:00-11:30 am (Room 413)
- Monday, April 16, 1:00-2:30 pm (Room 413)
To download the materials for these two workshops, visit GitHub.
Data Analytics and Visualization with Python
Miranda So, Instructor
- Thursday, March 8, 2:00-3:30 pm (Room 413)
- Friday, March 9, 1:00-2:30 pm (Room 413)
- Friday, March 23, 2:00-3:30 pm (Room 413)
- Wednesday, March 28, 1:00-2:30 pm (Room 413)
- Thursday, March 22, 1:00-2:30 pm (Room 413)
- Friday, March 30, 1:00-2:30 pm (Room 413)
- Wednesday, April 4, 1:00-2:30 pm (Room 413)
- Thursday, April 12, 2:00-3:30 (Room 413)
- Thursday, April 5, 1:00-2:30 pm (Room 415)
- Wednesday, April 11, 1:00-2:30 pm (Room 413)
- Thursday, April 19, 1:00-2:30 pm (Room 413)
- Friday, April 20, 2:00-3:30 pm (Room 413)
**Python workshops on Data Manipulation and Data Visualization assume familiarity with basic Python syntax and programming concepts (looping, conditional structures, data types, etc.). Consider attending Python Basics first if you are not familiar with these.
In this collaborative workshop, we will explore a number of pedagogical ideas for using the historical newspapers in Chronicling America (https://chroniclingamerica.loc.gov/). Anyone with an interest in historical newspapers or teaching with digital archives is welcome to attend. Participants are encouraged but not required to bring a course exercise or assignment of their own to workshop. For those intending to do so, please prepare a short summary that includes:  objectives and learning outcomes for the course/assignment; and  a description of how the framework of a database might serve to accomplish those learning objectives.
As archives increasingly allow and encourage photography, researchers are finding themselves with the mixed blessing of even more data to manage. In this workshop, we’ll learn how to use Tropy (https://tropy.org/), open-source software that allows users to organize and describe photos of research materials. We’ll also review the limitations of Tropy and additional tools that can be used in conjunction with it.
This workshop is the first of two exploring the recently added New Jersey newspapers in Chronicling America (https://chroniclingamerica.loc.gov/). In this first part, we’ll focus on techniques and strategies for fuzzy string matching in the R programming language, using the OCR-derived text from the Perth Amboy Evening News. Anyone interested in fuzzy string matching or textual analysis of mass print is encouraged to attend.
This workshop is the second of two exploring the recently added New Jersey newspapers in Chronicling America (https://chroniclingamerica.loc.gov/). In the second part, we’ll begin with the results of the previous workshop and do some basic analysis of phrase use over time, frequency, and collocate words. Anyone interested in fuzzy string matching or textual analysis of mass print is encouraged to attend.
Python Basics and Data Exploration
This workshop will be an accelerated introduction to fundamental concepts such as variable assignment, data types, basic calculations, working with strings and lists, control structures (e.g. for-loops), functions. We will also start working with pandas, a popular data science library in Python, to explore a dataset on food-borne outbreaks reported to the CDC.
Data Manipulation and Analysis
In this workshop, we will dive into the world of arrays and data frames using the NumPy and pandas libraries. We’ll cover data cleaning and pre-processing, joining and merging, group operations, and more. If you work with tabular data, this workshop is for you!
Data Visualization and Machine Learning
Interested in finding patterns and predicting unknown attribute values in your data? Join us for an overview of machine learning techniques implemented using the scikit-learn library. We’ll also learn how to do data visualization with matplotlib, a popular plotting library in Python.