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SciPy

machine_learning data_science data_analysis

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2020-Q1 2026-Q1

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Scientific Python is not only at the heart of discovery and advancement, but also infrastructure. This talk will provide a perspective on how open-source Python tools that are already powering real-world impact across the sciences are also supportive of public institutions and critical public data infrastructure. Drawing on her previous experience leading policy efforts in the Department of Energy as well as her experience in open-source scientific computing, Katy will highlight the indispensable role of transparency, reproducibility, and community in high-stakes domains. This talk invites the SciPy community to recognize its unique strengths and to amplify their impact by contributing to the public good through technically excellent, civic-minded development.

Ontologies provide a powerful way to structure knowledge, enable reasoning, and support more meaningful queries compared to traditional data models. Recently, interest in ontologies has resurged, driven by advancements in language models, reasoning capabilities, and the growing adoption of platforms like Palantir Foundry.

In this hands-on tutorial, participants will explore ontology development across multiple domains using a variety of Python-based tools such as rdflib, Owlready2, PySpark, Pandas, and SciPy. They will learn how ontologies facilitate semantic reasoning, improve data interoperability, and enhance query capabilities.
Additionally, attendees will build a rudimentary reasoning engine to better understand inference mechanisms.
The tutorial emphasizes practical applications and comparisons with conventional data representations, making it ideal for researchers, data engineers, and developers interested in knowledge representation and reasoning.