Knowledge Graph Conference (KGC)*

Knowledge Graph Conference (KGC)*

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The Knowledge Graph Conference (KGC) is a world-class curated program that brings experienced practitioners, technology leaders, cutting-edge researchers, academics and vendors together for two days of presentations, discussions and networking on the topic of knowledge graphs.

The conference was founded at the School of Professional Studies, Columbia University, in 2019. Since 2020 it is organized by Knowledge Graphs Conference or The Data Chefs, resp.

The Knowledge Connexions Conference (KnowCon) is adressing the transition from data to knowledge by connections and metadata. Graph Databases, Semantic Technology, Knowledge Graphs and Graph AI are solid building blocks that support this process.
The one-day conference with pre-conference workshops and masterclasses is organized by Connected Data London, in partnership with the Knowledge Graphs Conference.

Conference History:

2022 Knowledge Graph Conference (KGC), May 2-5, 2022, Cornell University, New York City, NY, USA / Virtual venue

(Host: Cornell Tech, Cornell University)

    Conference Tracks:
    Data Architecture; Natural Language Processing; Graph Data Science; Business Use Cases (Business Summit); Ontologies and Taxonomies; Content Knowledge Graphs; Search Engine Optimization; Health Care; Libraries; Open Knowledge Networks; EU projects

    Program TBD

2021 Knowledge Graph Conference (KGC), May 5–6, 2021, Virtual venue

Conference Theme: Connecting the Knowledge Ecosystem
(Host: Knowledge Graphs Conference)

    Pre-conference Workshops: (May 3-4)
    Knowledge Graphs for Social Good; Modeling Sustainability (CANCELLED); Enterprise Knowledge Graph Workshop; Workshop on Knowledge-infused Learning (K-iL 2021); Second Workshop on Personal Health Knowledge Graphs

    Pre-conference Tutorials: (May 3-4)
    Semantic Modeling for Knowledge Graphs; Validating semantic knowledge graphs using SHACL; Graph-Based Data Science; DBpedia Knowledge Graph Tech Tutorial; Annotating Tabular Data using Semantic Data Dictionaries; Integrating Data through Virtual Knowledge Graphs with Ontop; An Introduction to Knowledge Graphs; Foundation for a Knowledge Graph: Taxonomy Design Best Practices; How Graphs Improve Systems Thinking; Katana Graph (CANCELLED); Intro to Data Mesh (CANCELLED)

    Panel Discussions:
    Life Sciences; NLP for Knowledge Graphs; Standardization efforts for Knowledge Graphs; Graph Data Science; Knowledge Graphs Adoption in Finance

    High-Performance Knowledge Graph Computing on the Katana Graph Engine; From Network Medicine to Food and Knowledge Graphs; Introduction to Data Mesh: A paradigm shift in managing analytical data; Accelerating Industry Data Integration: Knowledge Graph Enabled Data Mesh; Knowledge Graph Industry Survey

    Conference Tracks:

Knowledge Connexions Conference (KnowCon), November 30 – December 2, 2020, Virtual venue

Conference Theme: Connecting data, people, and ideas: Building a global knowledge ecosystem
(Organizer: Connected Data London, Knowledge Graphs Conference)

    Pre-conference Workshops (Nov 30):
    Knowledge Graphs and SEO: The next chapter; AI + Knowledge – a match made in heaven?; From databases to platforms: the evolution of Graph databases; Knowledge Graph adoption in the Enterprise (Executive RoundTable)

    Pre-conference Masterclasses (Dec 1):
    Flawless Semantic Modeling in OWL and SKOS – The Theory; From Knowledge Graphs to AI-powered SEO – The Theory; Validating semantic knowledge graphs using SHACL; Graph Powered Machine Learning; Promoting Enterprise Knowledge Graphs with Metaphors and Stories; KG 101: Hands-on coding in Python

    Conference Tracks (Dec 2):
    Leaders; Innovators

    Conference Keynotes:
    Secret Knowledge: Visualizing Complexity
    Sales AI – Building and maintaining a knowledge graph
    Rebooting AI: Adding Knowledge to Deep Learning
    Powering the Connected Enterprise in a Hybrid, Multicloud World

2020 Knowledge Graph Conference (KGC), May 4-7, 2020, Columbia University, New York, NY, USA Virtual venue

Conference Theme: Knowledge Graphs for Artificial Intelligence in the Enterprise
(Host: Knowledge Graphs Conference School of Professional Studies, Columbia University)

    Pre-conference Workshops (May 4-5):
    Knowledge Graphs for Social Good (KGSG) – Best Practices, Methods, and Challenges; Personal Health Knowledge Graphs (PHKG): Challenges and Opportunities

    Pre-conference Tutorials (May 4-5):
    Building a Knowledge Graph from annotations; Data discovery on Siren Community Edition: a hybrid BI/Search/Knowledge graph platform for investigative intelligence; Virtualized Knowledge Graphs for Enterprise Applications; Designing and Building Enterprise Knowledge Graphs from Relational Databases; Introduction to Logic Knowledge Graphs, Succinct Data Structures and Delta Encoding for Modern Databases, and the Web Object Query Language; Rapid Knowledge Graph development with GraphQL and RDF databases; Modeling Evolving Data in Graphs While Preserving Backward Compatibility: The Power of RDF Quads

    Conference Sessions:
    Product Demos; Lightning Talks; Ask Me Anything Sessions (AMA); Knowledge Graph Conference Prize

    Discussion Panels:
    Frontiers in Data Intelligence

    Side events (May 5):
    Enterprise Knowledge Graph Foundation (EKG Foundation) launch; Inaugural investor/startup pitch event

2019 Knowledge Graph Conference (KGC), May 7-8, 2019, Columbia University, New York, NY, USA

Conference Theme: Learn to develop enterprise-wide knowledge graphs
(Host: School of Professional Studies, Columbia University)

    Knowledge Graph Architecture (Storing and Querying Knowledge Graphs; Metadata, Schemas, Ontologies, Taxonomies; Integrating multiple source systems; Aligning multiple data models); Use Cases (Machine Learning and Artificial IntelligenceNatural Language Processing; Understanding Knowledge Graph Embeddings; Data integration; Semantic data lakes; Security and Privacy; Business Intelligence and Data Analytics; Reasoning and Inference; Customer 360; Distributed ledger; Fraud detection); Tools (Visualization; Mapping and Integration); Formats and Languages; Data Management (Data Governance Data Quality; Data Responsibility)

    Discussion Panels:
    Graph Databases, Graph Query Languages, Graph Data Models

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