Sessions are from 10am-12pm and 1pm-3pm in Bobst Lower Level 1, Rm. 50 at the Elmer Holmes Bobst Library.
Finding and organizing project files, with emphasis on specifics of Mac and Windows systems
Key shortcuts and skills around command-line tools on Mac and Windows systems–automate the boring stuff
File naming, bulk renaming, and description
Setting up personal storage environment and cloud-storage clients, establishing backup systems
Installation of open-source software and understanding software dependencies
Understanding of how data files (text, tabular) store (encode) characters and sustainable ways to keep files usable over many years
Introduction to common formats for storing and collecting data (tabular, JSON, SQL)
Cleaning and transforming untidy data
Special case studies of spatial data files, image files, time-based media files–how they work and why they are more complex
Identify the ethical issues and data privacy risks associated with generative AI use
Think critically about generative AI use to support research and analyze the quality and accuracy of AI outputs
Explore NYU supported generative AI offerings
Evaluate Generative AI Tools for Academic Research
Sessions are from 10am-12pm and 1pm-3pm in Bobst Lower Level 1, Rm. 50 at the Elmer Holmes Bobst Library. Participants work with (choice of one) geospatial data display, simple data visualization tools, Optical Character Recognition (OCR) tools, audio transcription tools
StoryMaps: Telling Stories with Maps and Text
Define GIS and its uses.
Explore the Story Maps and ArcGIS Online interfaces.
Explore the NYU Spatial Data Repository and learn about spatial data.
Create a multimedia presentation including: an interactive GIS map using spatial data from NYU’s SDR, images, videos, webpages, and text
Share Story Maps.
Turning Texts into Data
Learn software designed for understanding a corpus of texts in a variety of disciplines.
Optimize your organization of document analysis and visualizing the contents of text data.
Sessions are from 10am-12pm and 1pm-3pm in Bobst Lower Level 1, Rm. 50 at the Elmer Holmes Bobst Library. Participants create a visualization in a tool such as StoryMaps or Knight Labs Storytelling tools.
Here is a sampling of projects NYU graduate students have worked on using the types of skills covered in this track:
Creating Interactive Maps: Mapping Artistic Activism Project (MAAP)
Building Digital Displays from Archives: Visualizing the Victorian Polar Network
Assembling a text corpus: Digitizing Chemical Humanities
Creating Data Visualizations: Insuring Slavery: Underwriting Risk in the 18th Century
Building Website Repository for Research Artifacts: Archive of Cuban Socialism