{"id":15626392,"url":"https://github.com/jbarrasa/goingmeta","last_synced_at":"2025-05-15T16:06:03.453Z","repository":{"id":39602010,"uuid":"454535016","full_name":"jbarrasa/goingmeta","owner":"jbarrasa","description":"code and resources used in the Going Meta sessions ","archived":false,"fork":false,"pushed_at":"2025-03-08T10:19:35.000Z","size":46025,"stargazers_count":493,"open_issues_count":9,"forks_count":86,"subscribers_count":45,"default_branch":"main","last_synced_at":"2025-04-07T22:05:06.883Z","etag":null,"topics":["graph-data-science","integration","knowledge-graph","ontologies","semantics"],"latest_commit_sha":null,"homepage":"http://goingmeta.live","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jbarrasa.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-02-01T20:10:16.000Z","updated_at":"2025-04-07T13:43:53.000Z","dependencies_parsed_at":"2024-01-11T16:58:39.446Z","dependency_job_id":"371d420a-c032-4295-a7e6-167b46ccf9b2","html_url":"https://github.com/jbarrasa/goingmeta","commit_stats":{"total_commits":254,"total_committers":5,"mean_commits":50.8,"dds":0.3661417322834646,"last_synced_commit":"000ba99d6bc2eb0da54f3670f5df1d3a5fcf53cc"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jbarrasa%2Fgoingmeta","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jbarrasa%2Fgoingmeta/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jbarrasa%2Fgoingmeta/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jbarrasa%2Fgoingmeta/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jbarrasa","download_url":"https://codeload.github.com/jbarrasa/goingmeta/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254374461,"owners_count":22060611,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["graph-data-science","integration","knowledge-graph","ontologies","semantics"],"created_at":"2024-10-03T10:12:21.535Z","updated_at":"2025-05-15T16:05:58.443Z","avatar_url":"https://github.com/jbarrasa.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# GoingMeta\n\nWe run the live streams on the **first Tuesday of each month**.\n(4pm BST, 11am ET, 8am PT, 3pm CEST, 8:30pm IST) \nStreaming on Twitch and Youtube Live.\n\nWe will use this repo to share all resources used in the sessions. Give them a try and give us your feedback!\n\n## SEASON 1\n\n### 2022 sessions\n\n| #  | broadcast | title |tags| recording  | code |\n|---:|:-----:| -----:|:---------:|:--------------------------:|:---:|\n| 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) |\n| 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) |\n| 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) |\n| 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) |\n| 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) |\n| 6  | Jul 5 | Ontology learning from graph data |`Graph Algos` `ML` `Ontologies`| [📺](https://www.youtube.com/watch?v=fpt-OsGOzmo\u0026t=1060s) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session06) |\n| 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) |\n| 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) |\n| 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) |\n| 10  | Nov 1 | SPARQL based integrations |`DBPedia` `Cypher` `SPARQL`| [📺](https://www.youtube.com/watch?v=nG62SzxOBJc) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session10) |\n| 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) |\n\n### 2023 sessions\n\n| #  | broadcast | title |tags| recording  | code |\n|---:|:-----:| -----:|:---------:|:--------------------------:|:---:|\n| 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) |\n| 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) |\n| 14  | Mar 7 | Taxonomy reconciliation |`RDF` `SPARQL` `Cypher`| [📺](https://www.youtube.com/watch?v=Aurp3eztRHM) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session14) |\n| 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) |\n| 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) |\n| 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) |\n| 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) |\n| 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) |\n| 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)) |\n| 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) |\n| 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) |\n| 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) |\n\n### 2024 sessions\n\n| #  | broadcast | title |tags| recording  | code |\n|---:|:-----:| -----:|:---------:|:--------------------------:|:---:|\n| 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) |\n| 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) |\n| 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) |\n| 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) |\n\n\n## SEASON 2\n\n### 2024 sessions\n\n| #  | broadcast | title |tags| recording  | code |\n|---:|:-----:| -----:|:---------:|:--------------------------:|:---:|\n| 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) |\n| 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) |\n| 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) |\n| 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) |\n\n\n### 2025 sessions\n\n| #  | broadcast | title |tags| recording  | code |\n|---:|:-----:| -----:|:---------:|:--------------------------:|:---:|\n| 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) |\n| 6  | Feb 4 | Retrieval Methods Compared | `LLM` `Ontology` `Knowledge Graph` `GraphRAG` | [📺](https://youtube.com/live/GPmHpp3QEWc) | [💻](https://github.com/jbarrasa/goingmeta/tree/main/session33) |\n| 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) |\n| 8  | Apr 1 | tbd | | [📺](#) | [💻](#) |\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjbarrasa%2Fgoingmeta","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjbarrasa%2Fgoingmeta","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjbarrasa%2Fgoingmeta/lists"}