ConferenceCall 2023 10 25

Session	A look across the industry, Part 2
Duration	1 hour
Date/Time	25 Oct 2023 16:00 GMT
	9:00am PDT/12:00pm EDT
	4:00pm GMT/5:00pm CST
Convener	Andrea Westerinen and Mike Bennett

Ontology Summit 2024 A look across the industry, Part 2

Agenda

• Evren Sirin, Stardog CTO and lead for their new Voicebox offering
  • Title: How Stardog Uses AI and How AI Uses Stardog
  • Abstract: Stardog’s AI strategy can be summarized as hybrid, applied, in-house, and user-focused. "Hybrid" derives from understanding that data management systems should provide crisp, provably correct, trusted answers to questions, but also benefits from considering fuzzy, not-terribly-wrong answers. "Applied and in-house" is focused on using foundational LLMs, NLP, or AI infrastructures to address the challenges of data modeling, data mapping, query generation, rule creation and more. "User-focused" pivots around capabilities such as question answering without any need to write queries, using ordinary language to manage a data lifecycle, and semi-supervised integration of an enterprise's structured, semi-structured, and unstructured data. The overall goal is universal self-service analytics. A significant step towards the goal is Stardog's Voicebox which leverages LLM to build, manage, and query knowledge graphs using ordinary language.
• Yuan He, Key contributor to DeepOnto, a package for ontology engineering with deep learning
  • Title: DeepOnto: A Python Package for Ontology Engineering with Deep Learning and Language Models
  • Abstract: Integrating deep learning techniques, particularly language models (LMs), with knowledge representations like ontologies has raised widespread attention, urging the need for a platform that supports both paradigms. However, deep learning frameworks like PyTorch and Tensorflow are predominantly developed for Python programming, while widely-used ontology APIs, such as the OWL API and Jena, are primarily Java-based. To facilitate seamless integration of these frameworks and APIs, we present DeepOnto, a Python package designed for ontology engineering with deep learning. The package encompasses a core ontology processing module founded on the widely-recognized and reliable OWL API, encapsulating its fundamental features in a more “Pythonic” manner and extending its capabilities to incorporate other essential components including reasoning, verbalization, normalization, projection, taxonomy, and more. Building on this module, DeepOnto offers a suite of tools, resources, and algorithms that support various ontology engineering tasks, such as ontology alignment and completion, by harnessing deep learning methods, primarily pre-trained LMs.

Conference Call Information

• Date: Wednesday, 25 October 2023
• Start Time: 9:00am PDT / 12:00pm EDT / 6:00pm CEST / 5:00pm BST / 1600 UTC
  • ref: World Clock
• Expected Call Duration: 1 hour
• Video Conference URL: https://bit.ly/48lM0Ik
  • Conference ID: 876 3045 3240
  • Passcode: 464312

The unabbreviated URL is: https://us02web.zoom.us/j/87630453240?pwd=YVYvZHRpelVqSkM5QlJ4aGJrbmZzQT09

Previous Meetings

	Session
ConferenceCall 2023 10 18	A look across the industry, Part 1
ConferenceCall 2023 10 11	Setting the stage
ConferenceCall 2023 10 04	Overview

Next Meetings

	Session
ConferenceCall 2023 11 01	Demos of information extraction via hybrid systems
ConferenceCall 2023 11 08	Broader thoughts
ConferenceCall 2023 11 15	Synthesis
... further results