Agricultural Ontologies in Use: New Crops and Traits in the Crop Ontology | CGIAR Platform for Big Data in Agriculture
The Ontologies Community of Practice is engaged in the development of ontologies for agricultural research. In a series of blog posts, we’ll take a look at ongoing ontologies projects and developments.
Agronomic Linked Data (AgroLD): A knowledge-based system to enable integrative biology in agronomy
Recent advances in high-throughput technologies have resulted in a tremendous increase in the amount of omics data produced in plant science. This increase, in conjunction with the heterogeneity and variability of the data, presents a major challenge to adopt an integrative research approach. We are facing an urgent need to effectively integrate and assimilate complementary datasets to understand the biological system as a whole. The Semantic Web offers technologies for the integration of heterogeneous data and their transformation into explicit knowledge thanks to ontologies. We have devel...
Ahren Lehnert latest blog on knowledge management, knowledge graphs and ontologies #knowledgemanagement #knowledgegraphs #ontology buff.ly/2uDuv7V https://t.co/DdPxioGxnE
#Knowledgegraphs are a natural fit for knowledge management: they model domains to retain more context & meaning even as information is parsed and abstracted for digital representation. Information is modeled in a way that is more intuitive & useful
AI and Graph Technology: 4 Ways Graphs Add Context
Read the first installment of this blog series on artificial intelligence on the ways graph technology adds necessary context for powerful AI solutions.
AI Institute "Geometry of Deep Learning" 2019 [Day 2 | Session 4] - Microsoft Research
Deep learning is transforming the field of artificial intelligence, yet it is lacking solid theoretical underpinnings. This state of affair significantly hinders further progress, as exemplified by time-consuming hyperparameters optimization, or the extraordinary difficulties encountered in adversarial machine learning. Our three-day workshop stems on what we identify as the current main bottleneck: understanding the geometrical […]
AI, Knowledge Representation and Graph Databases - Key Trends in Dat…
Knowledge Representation is a key focus for most modern AI texts. Many AI experts feel that over half of their work is understanding how to find the right know…
Alan Morrison's answer to What areas of machine learning would you encourage startups to spend time innovating on? In others words, what tools are engineers missing (ie, better data labeling, etc.) to make their machine learning experience more streamline
Alan Morrison's answer to What is the difference between a knowledge graph and a graph database? - Quora
Alan Morrison's answer: Graph databases are often used to store knowledge graph data and the accompanying description, predicate and rule-based logic. Knowledge graph: A knowledge graph is a knowledge base that’s made machine readable with the help of logically consistent, linked graphs that tog...
What are your options for visualizing a network with many attributes? We review the alternatives and introduce a typology in a new state of the art report. #eurovis #datavis https://t.co/96dhomPTRt w. @carolinanobre84 @miriah_meyer @marc_streit 1/8 pic.twitter.com/PCAk5ptBp3— Alexander Lex (@alexander_lex) June 4, 2019
All It Takes is 20 Questions!: A Knowledge Graph Based Approach. (arXiv:1911.05161v1 [cs.IR])
#knowledgegraph-based #research to design a 20 questions game on Bollywood movies. Uses probabilistic learning model for template-based question generation & answer prediction. Dataset of interrelated entities represented as weighted knowledge graph #AI
Amazon Neptune now supports TinkerPop 3.4 features
#Amazon Neptune #graphDB now supports @apachetinkerpop 3.4.1. @gfxman shows examples of new features in the Gremlin query/traversal language #softwaredevelopment #analytics #database #data #tech #tutorial #opensource #AWS [LINK]https://muawia.com/amazon-neptune-now-supports-tinkerpop-3-4-features/[/LINK] [IMAGE]https://s.put.re/NzhUFENd.png[/IMAGE]
Amazon Neptune now supports TinkerPop 3.4 features | AWS Database Blog
Amazon Neptune now supports the Apache TinkerPop 3.4.1 release. In this post, you will find examples of new features in the Gremlin query and traversal language such as text predicates, changes to valueMap, nested repeat steps, named repeat steps, non-numerical comparisons, and changes to the order step. It is worth pointing out that TinkerPop 3.4 […]
Amazon Neptune offers full-text search integration with Elasticsearch clusters
#graphDB #Amazon Neptune now supports full-text search integration with Elasticsearch clusters. Using Elasticsearch users can run full-text search query types such as match query, intervals query, query strings using extensions to Gremlin & SPARQL #AWS
Amazon Neptune releases Streams, SPARQL federated query for graphs and more | AWS Database Blog
The latest Amazon Neptune release brings together a host of capabilities that enhance developer productivity with graphs. This post summarizes the key features we have rolled out and pointers for more details. Getting started This new engine release will not be automatically applied to your existing cluster. You can choose to upgrade an existing cluster […]