The Dataverse Project: 750K FAIR Datasets and a Living Knowledge Graph
"I'm Ukrainian and I'm wearing a suit, so no complaints about me from the Oval Office" - that's the start of my lecture about building Artificial Intelligence with Croissant ML in the Dataverse data platform, for the Bio x AI Hackathon kick-off event in Berlin. https://lnkd.in/ePYHCfJt
* 750,000+ FAIR datasets across the world forcing the innovation of the whole data landscape.
* A knowledge graph with 50M+ triples.
* AI-ready metadata exports.
* Qdrant as a vector storage, Google Meta Mistral AI as LLM model providers.
* Adrian Gschwend Qlever as fastest triple store for Dataverse knowledge graphs
Multilingual, machine-readable, queryable scientific data at scale.
If you're interested, you can also apply for the 2-month #BioAgentHack online hackathon:
• $125K+ prizes
• Mentorship from Biotech and AI leaders
• Build alongside top open-science researchers & devs
More info: https://lnkd.in/eGhvaKdH
Building Flexible Virtual Knowledge Graphs with Ontop and Apache Iceberg | LinkedIn
What’s So Special About Apache Iceberg? Apache Iceberg is one of the most fascinating technologies when it comes to standardized access to large analytic tables. And Apache Iceberg combines very well with the idea of virtual knowledge graphs.
Introducing CyVer: Schema-Aware Cypher Query Validation for Neo4j
🚀 Introducing 𝗖𝘆𝗩𝗲𝗿: Schema-Aware Cypher Query Validation for Neo4j!
We’re excited to share 𝗖𝘆𝗩𝗲𝗿, the Python library we developed to validate… | 12 comments on LinkedIn
Introducing 𝗖𝘆𝗩𝗲𝗿: Schema-Aware Cypher Query Validation for Neo4j
Synalinks is an open-source framework designed to streamline the creation, evaluation, training, and deployment of industry-standard Language Models (LMs) applications
🎉 We're thrilled to unveil Synalinks (🧠🔗), an open-source framework designed to streamline the creation, evaluation, training, and deployment of…
Synalinks (🧠🔗), an open-source framework designed to streamline the creation, evaluation, training, and deployment of industry-standard Language Models (LMs) applications
Announcing QLeverize: The Future of Open-Source Knowledge Graphs at Unlimited Scale | LinkedIn
Biel/Bienne, Switzerland – February 24, 2025 – Knowledge graphs are becoming critical infrastructure for enterprises handling large-scale, interconnected data. Yet, many existing solutions struggle with scalability, performance, and cost—forcing organizations into proprietary ecosystems with high op
yfiles jupyter graphs for sparql: The open-source adapter for working with RDF databases
📣Hey Semantic Web/SPARQL/RDF/OWL/Knowledge graph community:
Finally! We heard you! I just got this fresh from the dev kitchen: 🎉
Try our free SPARQL query result visualization widget for Jupyter Notebooks!
Based on our popular generic graph visualization widget for Jupyter, this widget makes it super convenient to add beautiful graph visualizations of your SPARQL queries to your Jupyter Notebooks.
Check out the example notebooks for Google Colab in the GitHub repo
https://lnkd.in/e8JP-eiM ✨
This is a pre-1.0-release but already quite capable, as it builds on the well-tested generic widget. We are looking to get your feedback on the features for the final release, so please do take a look and let me know your feedback here, or tell us on GitHub!
What features are you missing? What do you like best about the widget? Let me know in the comments and I'll talk to the devs 😊
#sparql #rdf #owl #semanticweb #knowledgegraphs #visualization
GitHub - yWorks/yfiles-jupyter-graphs-for-sparql: The open-source adapter for working with RDF databas
I have never been a fan of the "bubble and arrows" kind of graph visualizations. It is generaly useless.
But when you can see the entire graph, and can tune the rendering, you start understanding the topology and structure - and ultimately you can tell a story with your graph (and that's what we all love, stories).
Gephi is a graph visualization tool to tell these sort of stories with graphs, that has been around for 15 (20 ?) years. Interestingly, while quite a number of Gephi plugins exist to load data (including from neo4j), no decent working plugin exist to load RDF data (yes, there was a "SemanticWebImport" plugin, but it looks outdated, with an old documentation, and does not work with latest - 0.10 - version of Gephi). This doesn't tell anything good for the semantic knowledge graph community.
A few weeks ago I literally stumbled upon an old project we developed in 2017 to convert RDF graphs into the GEXF format that can be loaded in Gephi. Time for a serious cleaning, reengineering, and packaging ! So here is a v1.0.0 of the rebranded rdf2gephi utility tool !
The tool runs as a command line that can read an RDF knowledge graph (from files or a SPARQL endpoint), execute a set of SPARQL queries, and turn that into a set of nodes and edges in a GEXF file. rdf2gephi provides default queries to run a simple conversion without any parameters, but most of the time you will want to tune how your graph is turned into GEXF nodes and edges (for example, in my case, `org:Membership` entities relating `foaf:Persons` with `org:Organizations` are not turned into nodes, but into edges, and I want to ignore some other entities).
And then what ? then you can load the GEXF file in Gephi, and run a few operations to showcase your graph (see the little screencast video I recorded) : run a layout algorithm, color nodes based on their rdf:type or another attribute you converted, change their size according to the (in-)degree, detect clusters based on a modularity algorithm, etc. etc. - and then export as SVG, PNG, or another format. Also, one of the cool feature supported by the GEXF format are dynamic graphs, where each nodes and edges can be associated to a date range. You can then see your graph evolving through time, like in a movie !
I hope I will be able to tell a more concrete Gephi-powered, RDF-backed graph-story in a future post !
All links in comments.
We're very happy to announce our latest release of Kùzu, version 0.8.0, is now available and ready to use! This release brings an exciting new feature that…
Nakala : from an RDF dataset to a query UI in minutes - SHACL automated generation and Sparnatural - Sparna Blog
Here is a usecase of an automated version of Sparnatural submitted as an example for Veronika Heimsbakk’s SHACL for the Practitioner upcoming book about the Shapes Constraint Language (SHACL). “ The Sparnatural knowledge graph explorer leverages SHACL specifications to drive a user interface (UI) that allows end users to easily discover the content of an RDF graph. What…
GitHub - apache/incubator-hugegraph: A graph database that supports more than 100+ billion data, high performance and scalability (Include OLTP Engine & REST-API & Backends)
A graph database that supports more than 100+ billion data, high performance and scalability (Include OLTP Engine & REST-API & Backends) - apache/incubator-hugegraph
A zero-hallucination AI chatbot that answered over 10000 questions of students at the University of Chicago using GraphRAG
UChicago Genie is now open source! How we built a zero-hallucination AI chatbot that answered over 10000 questions of students at the University of… | 25 comments on LinkedIn
a zero-hallucination AI chatbot that answered over 10000 questions of students at the University of Chicago
Enhancing RAG-based apps by constructing and leveraging knowledge graphs with open-source LLMs
Graph Retrieval Augmented Generation (Graph RAG) is emerging as a powerful addition to traditional vector search retrieval methods. Graphs are great at repre...
We contributed recently to the "awesome semantic shapes" repository. This is a community-curated list of RDF shape resources, be it validators, generators…
We're excited to publicly release the Diffbot GraphRAG LLM! With larger and larger frontier LLMs, we realized that they would eventually hit a limit in terms… | 48 comments on LinkedIn
What if creating Linked Open Data was less like coding and more like writing? Could anyone extend the Semantic Web by sharing a document? Publish a knowledge… | 13 comments on LinkedIn
Graph_RAG: A Flask app running GraphRAG for healthcare, made with Vertex AI and Neo4j, to be deployed in a container
A Flask app running GraphRAG for healthcare, made with Vertex AI and Neo4j, to be deployed in a container (Cloud Run or ECS). - RubensZimbres/Graph_RAG
Building Knowledge Graphs with LLM Graph Transformer
🧱Building Knowledge Graphs with LLM Graph Transformer A deep dive into LangChain’s implementation of graph construction with LLMs If you want to try out… | 32 comments on LinkedIn
Building Knowledge Graphs with LLM Graph Transformer
SimGRAG is a novel method for knowledge graph driven RAG, transforms queries into graph patterns and aligns them with candidate subgraphs using a graph semantic distance metric
SimGRAG is a novel method for knowledge graph driven RAG, transforms queries into graph patterns and aligns them with candidate subgraphs using a graph…
SimGRAG is a novel method for knowledge graph driven RAG, transforms queries into graph patterns and aligns them with candidate subgraphs using a graph semantic distance metric
Using LLMs in each stage of building a Graph RAG chatbot: A case study
How we used Kùzu in combination with LLMs in multiple stages of the Graph RAG pipeline to build a QA chatbot for the Connected Data London Knowledge Graph Challenge
🚀 R2R : The Most Advanced AI Retrieval System We're excited to announce R2R's V3 API, bringing production-ready RAG capabilities to teams building serious AI… | 10 comments on LinkedIn
