How Chive's community-governed knowledge graph replaces hardcoded categories with a portable, extensible vocabulary.
AutoSchemaKG: Autonomous Knowledge Graph Construction through Dynamic Schema Induction from Web-Scale Corpora
In the current era of information abundance, transforming vast amounts of unstructured data into structured, machine-readable knowledge remains one of the most significant challenges in artificial intelligence. Knowledge Graphs (KGs) have emerged as the cornerstone technology for this transformation Zhao et al. (2024), providing the semantic backbone for applications ranging from search engines and question answering Wu et al. (2024); Chen et al. (2024c); Zong et al. (2024); Sun et al. (2024b) to recommendation systems Lyu et al. (2024) and complex reasoning tasks Li et al. (2024b). Yet despite their critical importance, current KG construction approaches remain hampered by an inherent paradox: they require predefined schemas created by domain experts, which fundamentally limits their scalability, adaptability, and domain coverage.
Ologs: A Categorical Framework for Knowledge Representation
In this paper we introduce the olog, or ontology log, a category-theoretic model for knowledge representation (KR). Grounded in formal mathematics, ologs can be rigorously formulated and cross-compared in ways that other KR models (such as semantic networks) cannot. An olog is similar to a relational database schema; in fact an olog can serve as a data repository if desired. Unlike database schemas, which are generally difficult to create or modify, ologs are designed to be user-friendly enough that authoring or reconfiguring an olog is a matter of course rather than a difficult chore. It is hoped that learning to author ologs is much simpler than learning a database definition language, despite their similarity. We describe ologs carefully and illustrate with many examples. As an application we show that any primitive recursive function can be described by an olog. We also show that ologs can be aligned or connected together into a larger network using functors. The various methods of information flow and institutions can then be used to integrate local and global world-views. We finish by providing several different avenues for future research.
Orrery, a Knowledge Graph That Adapts to Its Corpus
Orrery is our open-source knowledge graph that gets deeper as you feed it: domains that hit critical mass earn their own custom extraction specs, agents get an API, and humans get a galaxy. The whole …
Relational foundations for functorial data migration | Proceedings of the 15th Symposium on Database Programming Languages
In this paper we present a simple database definition language: that of categories and functors. A database schema is a small category and an instance is a set-valued functor on it. We show that morphisms of schemas induce three ''data migration ...
DevReal: Simple Knowledge Graphs with Outlines, neo4j, and Modal, Cameron Pfiffer
cheese.community/cheese-community-lexicon
Lexicons for cheese types, and a cheese log to track them
Ontology-Driven Observability: Building an End-to-End Knowledge Graph at Netflix Scale
Prasanna Vijayanathan, Renzo Sanchez-Silva
Functorial data migration
In this paper we present a simple database definition language: that of categories and functors. A database schema is a small category and an instance is a set-valued functor on it. We show that morphisms of schemas induce three “data migration functors”, which translate instances from one schema to the other in canonical ways. These functors parameterize projections, unions, and joins over all tables simultaneously and can be used in place of conjunctive and disjunctive queries. We also show how to connect a database and a functional programming language by introducing a functorial connection between the schema and the category of types for that language. We begin the paper with a multitude of examples to motivate the definitions, and near the end we provide a dictionary whereby one can translate database concepts into category-theoretic concepts and vice versa.
Linked Open Vocabularies (LOV)
Your entry point to high quality and reusable Vocabularies to describe Linked Data.
Wiki Builder: A Claude Code Plugin for Building LLM Knowledge Bases
Wiki Builder is an open-source Claude Code plugin that turns the LLM-knowledge-base workflow into a one-command setup. Scaffold a configurable wiki, point Claude at sources, and let the agent compile durable pages, indexes, and concept maps for you.
Wikidata
the free knowledge base with 120,900,955 data entities that anyone can edit.