In this week’s featured article, Agustin Martinez presents a comprehensive overview of RDF (Resource Description Framework) and LPG (Labeled Property Graph) models. He describes the various elements that exist in both models, and reviews the languages used to model, ingest, query, and validate data. There are links to source materials throughout, so it can be used as a point of departure for further research.
To help expand your graph skills leading up to NODES 2022, expert practitioners are offering the Road to NODES workshops. In these free two-hour workshops, you can learn about Apache Hop, Graph EDA, Apache Arrow, healthcare analytics, and Neo4j graph database. Register.
FEATURED NODES SPEAKER: Ward Cunningham
Ward Cunningham has served as CTO, Director, Fellow, Principal Engineer, and Inventor. He is best known for creating Wiki. He leads an open-source project rebuilding Wiki to solve more complex sharing situations addressing some of society’s toughest problems. He co-authored (with Bo Leuf) a book about wikis, “The Wiki Way,” and invented the Framework for Integrated Tests.
Ward founded movements in object-oriented, agile software, extreme programming, and pattern languages. His session at NODES 2022 is: Hypertext Super Collaborator. Don’t miss it: save your seat now!
You can also follow him on Twitter.
KNOWLEDGE GRAPH: The Future of Data StructuresIn this post, Hugo Jiménez describes the RDF standard model and SPARQL protocol. He discusses the advantages of knowledge graphs in the areas of data portals, semantic information on websites, search, question answering, and knowledge exploration.
LEARNING: What Is a Graph Database?
INDUSTRIAL STRENGTH: Combining Three Biochemical Datasets in a Graph Database
TWEET OF THE WEEK: @tlarsendataguyDon’t forget to retweet if you like it!
Occasionally, I rest from building our SAP knowledge graph in Neo4j by running test queries. By doing so, I validate the data and practice my (lackluster) Cypher skills.— Thomas Larsen (@tlarsendataguy) September 27, 2022
I like this one. It identifies companies we bought materials from, and also sold them the same materials. pic.twitter.com/kdhrfji3sd
… Of Special Interest