Chaitan Baru | Open Knowledge Network
KGC | The Complete Collection
•
20m
The concept of an Open Knowledge Network (OKN) is one of the components of the National Science Foundation’s Harnessing the Data Revolution (HDR) Big Idea, with the objective of providing semantic information infrastructure. By encoding information and knowledge about real-world entities and their relationships, the OKN would enable next generation artificial intelligence-based technologies and applications, focusing in particular on science and engineering information. While large-scale knowledge networks have been deployed in services like Google Search, Amazon catalogs, Apple Siri, Microsoft Cortana, and WolframAlpha, an open effort would expand this approach, enabling discovery of non-trivial information from multiple disparate knowledge sources for thousands of new topic areas in scientific and engineering information.
With this objective in mind, the NSF Convergence Accelerator announced a “track” on the Open Knowledge Network (Track A) in 2019. Twenty-one projects were funded in Phase I in 2019 and five were funded in Phase II in 2020. Multidisciplinary, multi-sector teams in these projects are addressing a range of issues including, programming environments for knowledge network creation, making hidden/implied geospatial information explicit in knowledge graphs, and encoding information in specific domains, viz. urban flooding, biomedicine, and court records.
Chaitan Baru is member of the National Science Foundation. He is currently a working at the Convergence Accelerator office and his talk is going to pertain to the Open Knowledge Network(OKN) program at the National Science Foundation. The panel discusses the background on OKN and its participation in the Convergence Accelerator program. NSF was trying set out a strategy to see how do they take data to knowledge and create an action based off of that data. Soon development of large knowledge networks based off of this conversation leading to subsequent meetings which led to workshops about this "Open Knowledge Network", which are knowledge networks that aren't specialized for certain companies cases but rather broad public use cases. Chaitan talks about several projects and gives an overview of OKN Convergence Accelerator program and the Open Knowledge Network activities. #knowledgegraph #knowledgegraphconference #knowledgegraphnetwork
Up Next in KGC | The Complete Collection
-
Chen Zhang & Dmytro Dolgopolov | Enti...
During the presentation, we will share our experience in building a knowledge graph leveraging Spark, NLP, and Machine Learning. We will start with explaining the business problems and challenges. Then walk through our data pipeline, including text analytics processes, name similarity solutions, ...
-
Chris Welty | Shopping Sense: Bringin...
Knowledge Graphs (KGs) continue to penetrate the industrial world after Google's famous "things not strings" was used to explain their acquisition of FreeBase ten years ago. While many KGs exist, they are by and large little more than "entity catalogs", missing entirely the links between those e...
-
Dan McCreary | Graph Hardware Is Coming!
In this presentation we will show how current general-purpose CPU hardware fails to deliver high performance graph analytics. We show that by doing a detailed analysis of the actual hardware functionally needed by graph queries (pointer jumping), we can redesign hardware that is optimized for fas...