Date(s) - 10/06/2022
11:00 am - 12:00 pm
A talk focused on facilitating software understanding by automatically capturing Knowledge Graphs from software documentation and code.
Research Software is key to understand, reproduce and reuse existing work in many disciplines, ranging from Geosciences to Astronomy or Artificial Intelligence. However, research software is usually difficult to find, reuse, compare and understand due to its disconnected documentation (dispersed in manuals, readme files, web sites, and code comments) and a lack of structured metadata to describe it. These problems affect not only researchers, but also students who aim to compare published findings and policy makers seeking clarity on a scientific result. In this talk I will present the main research challenges and our recent efforts towards facilitating software understanding by automatically capturing Knowledge Graphs from software documentation and code.
Dr. Daniel Garijo Verdejo is a Distinguished Researcher at the Ontology Engineering Group of Universidad Politécnica de Madrid (UPM). Previously, he held a Research Computer Scientist position at the Information Sciences Institute of the University of Southern California, in Los Angeles. Daniel’s research activities focus on e-Science and Knowledge Capture, specifically on how to increase the understandability of research software and scientific workflows by creating Knowledge Graph from their documentation and provenance (i.e., steps, outputs, inputs, intermediate results).
This is a hybrid event.
In person attendance
Room 1.33, Jack Cole Building, School of Computer Science, University of St Andrews.
Instructions on how to attend online (via Teams) will be released closer to the event date.
Register via Eventbrite.