Metadata Research Center: Data Science Foundation Carpentry
Event Information
About this Event
What: Metadata Research Center: Data Science Foundations Carpentry
When: Thursday, January 23, 2020
Where: Hagerty Library, Drexel University,3141 Chestnut Street, Philadelphia PA
Room: L33
About: The Metadata Research Center at the College of Computing and Informatics, Drexel University, is please to host the Data Science Carpentry workshop. The Carpentry workshop is part of the Library Carpentry program advancing “software and data skills for people working in library- and information-related roles.” The workshop is also connected with Drexel University’s LEADS (Library Education and Data Science) program, supported by the Institute of Museum and Library Services (IMLS)
The workshop will cover GitHub basics, OpenRefine, best data practices, and terminology
• GitHub basics covered include creating a local git repository (repo), adding a new file to the repo, adding a file to the staging environment, and creating a commit.
• OpenRefine is an open source tool that allows you to analyze, clean, and extract data. OpenRefine’s APIs work with regular expressions, and is often used to reconcile linked data. The workshop will cover OpenRefine working through hands-on exercises and demonstrations to gain knowledge and skills enabling independent working upon workshop completion. OpenRefine APIs, works with regular expressions, and is often used to reconcile linked data, and this topic will also be introduced.
• Terminology issues include jargon-busting.
Workshop Instructors:
Chris Erdmann is the Engagement, Support, and Training Expert at the RENCI (Renaissance Computing Institute) in North Carolina. RENCI develops and deploys advanced technologies to enable research discoveries and practical innovations. Juliane Schneider.
Julianne Schneider is the Lead Data Curator for Harvard Catalyst’s eagle-i. She has had a long, weird library career, starting as a traditional cataloger and is currently using ontologies and data harmonization to maximize discovery and data sharing/reuse.
Workshop made possible with IMLS Support: RE-70-17-0094-17
