Data insights from linked data

by Jordan Pedersen and Rachel Wang

Data Science

Our entire world wide web already is composed of linked data. In this talk we will demonstrate how python module RDFlib is able to traverse and parse linked data. As we will learn in this talk, linked data is queried with a query language called SPARQL which is supported by the RDFlib library. We will also show you how to level up your data insights by introducing graph databases. By the end of this talk you will be able to see for yourself draw relationships out of open linked data, as well as the unique value of communicating the relationships from linked data.

About the Author

Jordan Pedersen is the Metadata Librarian at the University of Toronto Libraries, and an enthusiastic newbie to python. She is passionate about teaching technical skills and breaking down the barriers to learning new skills. As a Certified Library Carpentry Instructor she has taught a variety of workshops, such as SQL, regex, OpenRefine, and FAIR data practices, for a wide range of audiences. She likes to balance her work life with lots of doodling. For more information about Jordan’s current projects feel free to contact her at

Rachel Wang is a Software Developer and Pythonista at the University of Toronto Libraries. She uses Python to support ETL and data heavy tasks at the library. When away from the keyboard she enjoys helping others learn technical skills as a Certified Software Carpentry Instructor. Rachel is also a co-organizer for a meetup called Code4Lib Toronto and when she isn’t using Python, Golang and Vue.js are always on her mind. You can find her @rwangca.

Talk Details

Date: Sunday Nov. 17

Location: Round Room (PyData Track)

Begin time: 15:25

Duration: 25 minutes