Metadata Analysis Workshop (sold out!)


Event has reached capacity and no further registrations can be accepted.

Description: This full day workshop will introduce library, archive, and museum metadata practitioners and technologists with the basic skills and knowledge needed to assess metadata quality using data analysis tools. Workshop participants will be introduced to the Metadata Assessment Framework developed by the DLF Assessment Interest Group, Metadata Working Group. Using this framework as a guideline, participants will be taught the basics of using several tools to harvest, analyze, and remediate metadata, both for a local and aggregated context. The workshop will close by helping participants strategize ways to bring these tools back into their daily workflows and continue to train others they work with to do the same.

Date & Time:  Thursday, 10/26 (9am-5pm)

Registration: $25.To sign up, add the workshop to your ticket when you register for the DLF Forum, or have it appended to a completed registration by contacting Morning coffee break and afternoon snack will be included (lunch on your own).

Workshop Facilitators: Scott Carlson (Rice University), Kate Flynn (Chicago Collections, University of Illinois at Chicago), Gretchen Gueguen (DPLA), Christina Harlow (Stanford University), Laura Smart (University of California, Irvine), Hannah Stitzlein (University of Illinois at Urbana-Champaign)

Audience: Cultural heritage metadata practitioners or technologists.

Prerequisites: Some experience with command line and basic metadata concepts will be presumed. Workshop registrants will receive an email with some materials to brush up on command line before the workshop. Basic familiarity with xml-based metadata is also presumed. Participants should bring their own laptops so that they can more easily take home what they learn.

Goals: Workshop attendees should leave the workshop with:

  • Ability to recognize and diagnose common metadata quality issues, both locally and in an aggregated environment
  • Knowledge of common indicators of metadata quality such as consistency or use of standards
  • Basic working knowledge of several tools for harvesting, analyzing, and remediating data
  • Recommendations for using what they’ve learned to train others

Technologies/Best Practices/Frameworks covered:

  • DLF Assessment Interest Group, Metadata Working Group’s Metadata Assessment Framework
  • Regular expressions
  • Command line-based harvesting and metadata analysis tools
  • OpenRefine

Questions? Get in touch with Gretchen Gueguen.





Skip to content