Background

Over the past five years, Yale University has built an innovative knowledge graph that connects its libraries, archives and museums in a single discovery platform, advancing the university’s core missions of teaching and research excellence. 

Led by Conference Chair, Madi Weland Solomon, and with insights from the event’s speakers, this interactive roundtable is an opportunity to exchange views, share experiences, hear innovative questions, pose questions and expand one’s network - just the way to kickstart the afternoon. 

All in a collaborative environment designed to increase knowledge, enhance skills, and propel careers. 

Covering (just to start): 

Time to have some lunch and visit the exhibition. See you back at 2:00 for the start of the afternoon sessions!

The position up to now:

For a long time much of HealthStream’s’ taxonomy has remained static, hard coded into production environments that couldn’t be updated without development efforts. As a result, changes have not been made in years due to competing priorities.  As part of its evolution into a platform solution HealthStream is beginning to offer API services for taxonomy. 

The challenge now faced:

My experience: 

A career spent working with photos, videos, music, and books has provided me ample opportunities to experiment with AI solutions for content tagging and metadata generation. From counting the number of people in a photo to applying keywords to kittens to writing fun facts about pop stars, AI-powered tools can perform a lot of mundane tasks. I’ve evaluated the work of these “robots” for over a decade, and I’ve recommended ways to leverage automation for scale, while still adhering to the level of quality demanded by human end users. 

Effective knowledge orchestration demands more than data aggregation; it requires semantic coherence across diverse sources.

What it is:

The Ontology Pipeline is a framework for building a semantic knowledge infrastructure, with iterative steps to guide the process. 

What it does:

Your chance to visit the DAM New York and Semantic Data exhibition and network with fellow attendees - co-located with DAM New York.

Foundations matter. 

Data quality is one of the most important pillars of a Semantic Architecture. Regardless of our particular projects or roles well defined semantics are only valuable if there is accurate, representative, and timely data. Unfortunately, too many organizations are unable to (or shouldn’t) trust their data enough to create the information experiences where people learn, make decisions, or connect.