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For over 20 years, ESIP meetings have brought together the most innovative thinkers and leaders around Earth observation data, thus forming a community dedicated to making Earth observations more discoverable, accessible and useful to researchers, practitioners, policymakers, and the public. The theme of this year’s meeting is Leading Innovation in Earth Science Data Frontiers.
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Wednesday, July 21 • 11:00am - 1:30pm
Graph-Based Data Science

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This tutorial introduces graph-based data science work, where machine learning approaches can be combined with complementary knowledge graph work. The tutorials leverage a popular library `kglab` – an open source project that integrates RDFlib, OWL-RL, pySHACL, NetworkX, iGraph, pslpython, node2vec, PyVis, and more – to show how to use a wide range of graph-based approaches, blending smoothly into data science workflows, and working efficiently with popular data engineering practices.

Within this space of open source graph libraries in Python, there are several camps: semantic graphs, probabilistic graphs, graph algorithms, graph ML, interactive visualization, etc. Previously these "camps" did not collaborate much and the libraries were difficult to integrate. We'll show how to write brief Python code to build complementary "Hybrid AI" workflows, which is ideal for strategies such as self-supervised learning. All of the training material is available as Jupyter notebooks.

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Organizers & Speakers
avatar for Paco Nathan

Paco Nathan

Managing Partner, Derwen, Inc.
Known as a "player/coach", with core expertise in data science, natural language, machine learning, cloud computing; ~40 years tech industry experience, ranging from Bell Labs to early-stage start-ups. Advisor for Amplify Partners, Recognai, KUNGFU.AI, Primer. Lead committer PyTe... Read More →


Wednesday July 21, 2021 11:00am - 1:30pm EDT
TBA