jbarrasa/goingmeta

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Última atividade de origem registrada: 8 de abril de 2026 às 23:32

Catálogo do SkillsMP atualizado: 17 de outubro de 2026 às 00:09

skills coletadas: 2

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# GoingMeta We run the live streams on the **first Tuesday of each month**. (4pm BST, 11am ET, 8am PT, 3pm CEST, 8:30pm IST) Streaming on Twitch and Youtube Live. We will use this repo to share all resources used in the sessions. Give them a try and give us your feedback! ## SEASON 1 ### 2022 sessions | # | broadcast | title |tags| recording | code | |---:|:-----:| -----:|:---------:|:--------------------------:|:---:| | 1 | Feb 1 | Cypher and SPARQL on the British Library catalog |`Cypher` `SPARQL`| [📺](https://www.youtube.com/watch?v=NQqWBnyQlS4) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session01) | | 2 | Mar 1 | Semantic search. A worked example |`n10s` `Cypher` `Wikidata`| [📺](https://www.youtube.com/watch?v=y6eCKIRsA64) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session02) | | 3 | Apr 5 | Controlling the shape of your graph with SHACL |`data quality` `SHACL` `n10s`| [📺](https://youtu.be/Zkgu7YauOfs?t=693) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session03) | | 4 | May 3 | Ontology based reasoning 101 |`Ontologies` `Inference` `Cypher`| [📺](https://www.youtube.com/watch?v=XX7Ppc5T0GE) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session04) | | 5 | Jun 13 | Ontology-driven Knowledge Graph construction |`Ontologies` `Python` `ETL`| [📺](https://www.youtube.com/watch?v=05Wkg1p34ek) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session05) | | 6 | Jul 5 | Ontology learning from graph data |`Graph Algos` `ML` `Ontologies`| [📺](https://www.youtube.com/watch?v=fpt-OsGOzmo&t=1060s) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session06) | | 7 | Aug 2 | Generating natural language from your KG by annotating ontologies |`NL` `Ontologies` `Cypher`| [📺](https://youtu.be/Y_IygO4MOqc?t=445) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session07) | | 8 | Sep 6 | Common RDF integration patterns |`Cypher` `JSON-LD` `SPARQL`| [📺](https://www.youtube.com/watch?v=iCrdR86AorU) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session08) | | 9 | Oct 4 | Unsupervised KG construction. Graph Observability |`Orchestration` `Prefect` `Wikidata`| [📺](https://www.youtube.com/watch?v=YVaj2LEqDn0) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session09) | | 10 | Nov 1 | SPARQL based integrations |`DBPedia` `Cypher` `SPARQL`| [📺](https://www.youtube.com/watch?v=nG62SzxOBJc) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session10) | | 11 | Dec 6 | Graph data quality with graph expectations |`Python` `Data Quality` `SHACL`| [📺](https://www.youtube.com/watch?v=JrBOvdVkjU4) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session11) | ### 2023 sessions | # | broadcast | title |tags| recording | code | |---:|:-----:| -----:|:---------:|:--------------------------:|:---:| | 12 | Jan 16 | Importing RDF data into AuraDB with Python and RDFLib |`Python` `RDFLib` `AuraDB`| [📺](https://youtu.be/DWINSvRxIbw?t=927) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session12) | | 13 | Feb 9 | Creating (and RDF-izing) virtual graphs over external data |`SQL` `APOC` `RDF` `Python`| [📺](https://www.youtube.com/watch?v=FoHAyBhcH4s) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session13) | | 14 | Mar 7 | Taxonomy reconciliation |`RDF` `SPARQL` `Cypher`| [📺](https://www.youtube.com/watch?v=Aurp3eztRHM) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session14) | | 15 | Apr 5 | Building a Semantic Data App with Streamlit |`Python` `Ontology` `Streamlit` `Protege`| [📺](https://www.youtube.com/watch?v=m7kg33OsI_A) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session15) | | 16 | May 2 | Semantic Similarity Metrics in Taxonomies |`Python` `NLTK` `Semantics` `Taxonomy`| [📺](https://www.youtube.com/watch?v=WwTxlyjY35I) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session16) | | 17 | June 1 | RDF-ing between OpenAI and Neo4j |`OpenAI` `Generative AI` `APOC` `RDF`| [📺](https://www.youtube.com/watch?v=w-PwMyzokSw) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session17) | | 18 | July 4 | Easy Full-Graph Migrations from Triple Stores to Neo4j |`Python` `RDF` `Migration` `Triple Store`| [📺](https://www.youtube.com/watch?v=9DDdFKVvZQc) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session18) | | 19 | Aug 1 | Ontology Versioning in Neo4j |`Python` `Ontologies` `Protege`| [📺](https://www.youtube.com/watch?v=xK_07cqKwMk) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session19) | | 20 | Sep 12 | Going Meta: A recap |`All`| [📺](https://www.youtube.com/watch?v=Tx1zCnlc0_g) | [💻]([https://github.com/jbarrasa/goingmeta/tree/main/session19](https://medium.com/neo4j/20-episodes-of-going-meta-a-recap-5a0ccd689c6c)) | | 21 | Oct 6 | Vector-based and Graph-based semantic search |`Cypher` `Ontologies` `Embeddings`| [📺](https://www.youtube.com/watch?v=bRD09ndyJNs) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session21) | | 22 | Nov 7 | RAG with Knowledge Graphs |`LLM` `Semantic Search` `Python` `Vector Index`| [📺](https://www.youtube.com/watch?v=9DxwgIKVSHY) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session22) | | 23 | Dec 6 | Advanced RAG patterns with Knowledge Graphs |`LLM` `Semantic Search` `Python` `Vector Index` `Streamlit`| [📺](https://www.youtube.com/watch?v=E_JO4-2D5Xs) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session23) | ### 2024 sessions | # | broadcast | title |tags| recording | code | |---:|:-----:| -----:|:---------:|:--------------------------:|:---:| | 24 | Jan 4 | KG+LLM: Ontology-driven RAG patterns |`Python` `Ontology` `Langchain` `Vector Index` `Cypher`| [📺](https://www.youtube.com/watch?v=5_WXr0GtVas) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session24) | | 25 | Feb 5 | LLMs for automated KG construction | `LLM` `Python` `OpenAI` `CompletionsAPI` `Kaggle` `Modelling`| [📺](https://www.youtube.com/watch?v=ViHV16ly-qs) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session25) | | 26 | Mar 5 | Unpicking the data.world Benchmark on the Role of KGs in LLM QA over relational data|`Benchmark` `SPARQL` `OWL` `LLM` `Python` `R2RML` `Semantic Layer` | [📺](https://www.youtube.com/watch?v=ReRH53amZ4M) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session26) | | 27 | Apr 2 | Building a Reflection Agent with LangGraph |`LangChain` `LangGraph` `Python` `LLM` `Modelling` | [📺](https://www.youtube.com/watch?v=Sra-1xhNn28) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session27) | ## SEASON 2 ### 2024 sessions | # | broadcast | title |tags| recording | code | |---:|:-----:| -----:|:---------:|:--------------------------:|:---:| | 1 | Sep 3 | Using Ontologies to Guide Knowledge Graph Creation from Unstructured Data (no code) |`LLM` `Ontology` `Knowledge Graph Builder` `Cypher` `SHACL`| [📺](https://www.youtube.com/watch?v=RYuw4oq0G84) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session28) | | 2 | Oct 1 | Using Ontologies to Guide KG Creation from Unstructured Data (through code) |`LLM` `Ontology` `Python` `Cypher` `RDFLib`| [📺](https://www.youtube.com/watch?v=rde3ak_H70Y) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session29) | | 3 | Nov 20 | Blueprints for Knowledge Graph Construction from Unstructured Data | `LLM` `Ontology` `Python` `Cypher` `RDFLib` `Pydantic` `RDF`| [📺](https://youtube.com/live/cPzy61odKCg) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session30) | | 4 | Dec 3 | Ontology-driven end-to-end GraphRAG | `LLM` `Ontology` `Python` `GraphRAG`| [📺](https://youtube.com/live/UmP0pFFsMsE) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session31) | ### 2025 sessions | # | broadcast | title |tags| recording | code | |---:|:-----:| -----:|:---------:|:--------------------------:|:---:| | 5 | Jan 7 | One Ontology To Rule Them All: Building KG from Mixed Data | `LLM` `Ontology` `Knowledge Graph` `GraphRAG` | [📺](https://youtube.com/live/0c3WicsmLuo) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session32) | | 6 | Feb 4 | Retrieval Methods Compared | `LLM` `Ontology` `Knowledge Graph` `GraphRAG` | [📺](https://youtube.com/live/GPmHpp3QEWc) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session33) | | 7 | Mar 4 | Enhancing LLM Tool Calling with Ontologies | `LLM` `Ontology` `Knowledge Graph` `GraphRAG` `Agents` | [📺](https://youtube.com/live/WOyb7XW7ppQ) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session34) | | 8 | Apr 8 | Agentic Workflows for Dynamic Ontology Selection in KG Construction | `LLM` `Ontology` `Knowledge Graph` `GraphRAG` `Agents` | [📺](https://youtube.com/live/OhsfdRxcTqQ) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session35) | | 9 | May 6 | Structural Patterns for Ontology Reconciliation | `Ontology` `RDFLib` `RDF` `Knowledge Graph` | [📺](https://youtube.com/live/xuyJTHBbf0U) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session36) | | 10 | July 2 | Structuring Biomedical Noise: Graphs, AI and the Drug Discovery Dilemma | `LLM` `AI` `Pharma` `LifeScience` `Conversation` | [📺](https://youtube.com/live/J5aar9j9FWQ) | | 11 | August 5 | 2 years of KGs and GenAI. A Recap | `LLM` `Knowledge Graph` `GraphRAG` `Agents` | [📺](https://youtube.com/live/IlI3uNjquKI) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session38) | ## SEASON 3 ### 2025 sessions | # | broadcast | title |tags| recording | code | |---:|:-----:| -----:|:---------:|:--------------------------:|:---:| | 1 | Oct 7 | Ontology Creation with the Neo4j MCP Server | `LLM` `Ontology` `GraphRAG` `Agents` `MCP` `Modelling` | [📺](https://youtube.com/live/lAg7ZweHhbI) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session39) | | 2 | Nov 4 | Supercharging Neo4j Aura Agents with Ontologies | `LLM` `Ontology` `Agents` | [📺](https://youtube.com/live/wFfld2vrqkk) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session40) | | 3 | Dec 9 | Ontologies, LLMs, Property Graphs - Do we really have a "Jaguar Problem"? | `LLM` `Ontology` `RDF` `Knowledge Graph` | [📺](https://youtube.com/live/TJI6XiHSYt4) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session41) | ### 2026 sessions | # | broadcast | title |tags| recording | code | |---:|:-----:| -----:|:---------:|:--------------------------:|:---:| | 4 | Jan 6 | Evaluating the Quality of Ontologies | `Ontology` `OWL` `Knowledge Graph` | [📺](https://youtube.com/live/16oBgsWPX1o) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session42) | | 5 | Feb 3 | Neo4j Agent Memory | `Agents` `Memory` `LLM` | [📺](https://youtube.com/live/rnERHmj81VI) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session43) | | 6 | Mar 3 | Validating Neo4j Graphs with SHACL | `SHACL` `RDF` `Validation` | [📺](https://youtube.com/live/u7fsq5vEA3E) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session44) | | 7 | Apr 7 | Agent Skills For Creating and Using Ontologies | `Agents` `Ontology` `Skills` `LLM` | [📺](https://youtube.com/live/6bIUwMrKDlk) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session45) | | 8 | May 5 | The Graph Behind the Graph: Tracing Ontology Design Decisions | `Agents` `Ontology` `Skills` `LLM` | [📺](https://youtube.com/live/FuUNOBdRRLQ) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session46) | | 9 | June 2 | Shape agent memory with ontologies | `Agents` `Ontology` `Skills` `LLM` | [📺](https://youtube.com/live/fEQlTt7vDb0) | | | 10 | July 7 | Actionable Knowledge For Agents With Context Graphs | `Agents` `Ontology` `Skills` `LLM` | [📺](https://youtube.com/live/JGFoTQt4GA0) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session48) | | 11 | August | Unwrapping OKF (and Season 3) | `OKF` `Agents` `Ontology` `Skills` `LLM` | [📺](https://youtube.com/live/h4DLcWi9jGc) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session49) | ### Going Meta is on a short break! We will return with Season 4

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descrição

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hello

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A simple skill that responds to hello with a greeting.

Idioma do texto original: inglês

2026-04-08

ontology-builder-assistant

Desenvolvedores de software

derive a minimal reusable ontology from purpose statements, competency questions, sample data, reusable vocabularies, supporting semantic evidence, and implementation constraints. use when you're asked to draft an ontology for a specific use case. Especially…

Idioma do texto original: inglês

2026-04-08

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