Скачать или смотреть Graph Data Standards Rebooted KGC 2024

Graph Data Standards Rebooted KGC 2024
Joshua Shinier | Principal Engineer at Microsoft
🔗 connect with speaker on LinkedIn   / joshuashinavier  

Deborah McGuinness | Tetherless World Chair, Professor at Rensselaer Polytechnic Institute
🔗 connect with speaker on LinkedIn   / deborah-mcguinness-088167  

Alastair Green | Vice Chair at Linked Data Benchmark Council
🔗 connect with speaker on LinkedIn   / alastair-green-65a861a7  

Molham Aref | CEO RelationalAI
🔗 connect with speaker on LinkedIn   / molham  

Ora Lassila | Principal Technologist at Amazon Web Services
🔗 connect with speaker on LinkedIn   / oralassila  

Graph data models, like graph databases, have a long history which is characterized more by sudden shifts than by a deliberate and continuous progression. From the navigational databases of the 1960s to today’s Semantic Web standards and the upcoming GQL standard for property graphs, each generation of data models has been a reaction to changing conditions and a distinct class of graph users and use cases. The RDF and OWL ecosystems came about as answers to grand questions like “how can we turn the Web into a giant global graph of machine-readable knowledge?” and accordingly, are strong on data integration and knowledge representation. Property graphs were originally a tool for otherwise untrained developers to build domain-specific graph applications very efficiently and effectively. Other innovations have focused on extending ubiquitous technologies like relational databases to support graph applications, or have explored the capabilities of advanced graph variants like labeled hypergraphs. Most recently, of course, the widespread availability of generative AI is driving these existing graph communities in new directions with enormous pressure, and seems certain to give rise to entirely new and unrelated classes of graph applications. In this panel, we will survey together the current landscape of graph data standards, with an eye toward knowledge representation and with a particular focus on standardization efforts which are currently underway. However, we will also do our level best to peer several years into the future and ask, without attachment to the fine technologies we have already built, what the role of graph standards will be in a world where machines can create models, produce knowledge, write queries, and even build applications in tandem with human developers. This will be a panel to look back on five or ten years from now, and gauge how prescient the graph community was, or how we really had no idea what was coming.

#graphdatamodels #SemanticWeb #generativeai

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