Geist - A personal knowledge base with a focus on connections

  •        1063

A personal knowledge base with a focus on connections. The personal knowledge base (PKB) is basically a wiki system for personal use. Unlike a public wiki which most often focuses on representing facts, the PKB can contain subjective material relevant to the person or persons using the PKB. Therefore the desired properties of a PKB are equivalent to those of the personal wiki.



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foam - A personal knowledge management and sharing system for VSCode

  •    Typescript

Foam is a personal knowledge management and sharing system inspired by Roam Research, built on Visual Studio Code and GitHub. You can use Foam for organising your research, keeping re-discoverable notes, writing long-form content and, optionally, publishing it to the web.

kglib - Grakn Knowledge Graph Library (ML R&D)

  •    Python

To respond to these scenarios, KGLIB is the centre of all research projects conducted at Grakn Labs. In particular, its focus is on the integration of machine learning with the Grakn Knowledge Graph. More on this below, in Knowledge Graph Tasks. At present this repo contains one project: Knowledge Graph Convolutional Networks (KGCNs). Go there for more info on getting started with a working example.

dgl-ke - High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings

  •    Python

Knowledge graphs (KGs) are data structures that store information about different entities (nodes) and their relations (edges). A common approach of using KGs in various machine learning tasks is to compute knowledge graph embeddings. DGL-KE is a high performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings. The package is implemented on the top of Deep Graph Library (DGL) and developers can run DGL-KE on CPU machine, GPU machine, as well as clusters with a set of popular models, including TransE, TransR, RESCAL, DistMult, ComplEx, and RotatE. This command will download the FB15k dataset, train the transE model and save the trained embeddings into the file.

Logseq - Platform for knowledge management and collaboration.

  •    Clojure

Logseq is a platform for knowledge management and collaboration. It focuses on privacy, longevity, and user control. The server will never store or analyze your private notes. It works on top of local plain-text Markdown and Org-mode files. Use it to write, organize and share your thoughts, keep your to-do list, and build your own digital garden. It provides support to organize your tasks and projects with built-in workflow commands.

AmpliGraph - Python library for Representation Learning on Knowledge Graphs https://docs

  •    Python

Open source library based on TensorFlow that predicts links between concepts in a knowledge graph. AmpliGraph is a suite of neural machine learning models for relational Learning, a branch of machine learning that deals with supervised learning on knowledge graphs.

Dendron - The personal knowledge management (PKM) tool that grows as you do!

  •    Typescript

Dendron is an open-source, local-first, markdown-based, note-taking tool. It's a personal knowledge management solution (PKM) built specifically for developers and integrates natively with IDEs like VS Code and VSCodium.

atomspace - The OpenCog hypergraph database, query system and rule engine

  •    C++

The OpenCog AtomSpace is a knowledge representation (KR) database and the associated query/reasoning engine to fetch and manipulate that data, and perform reasoning on it. Data is represented in the form of graphs, and more generally, as hypergraphs; thus the AtomSpace is a kind of graph database, the query engine is a general graph re-writing system, and the rule-engine is a generalized rule-driven inferencing system. The vertices and edges of a graph, known as "Atoms", are used to represent not only "data", but also "procedures"; thus, many graphs are executable programs as well as data structures. The AtomSpace is a platform for building Artificial General Intelligence (AGI) systems. It provides the central knowledge representation component for OpenCog. As such, it is a fairly mature component, on which a lot of other systems are built, and which depend on it for stable, correct operation in a day-to-day production environment.

beam - A distributed knowledge graph store

  •    Go

There's a blog post that's a good introduction to Beam. Beam is a distributed knowledge graph store, sometimes called an RDF store or a triple store. Knowledge graphs are suitable for modeling data that is highly interconnected by many types of relationships, like encyclopedic information about the world. A knowledge graph store enables rich queries on its data, which can be used to power real-time interfaces, to complement machine learning applications, and to make sense of new, unstructured information in the context of the existing knowledge.

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TypeDB - A strongly-typed database

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TypeDB is a strongly-typed database with a rich and logical type system. TypeDB empowers you to tackle complex problems, and TypeQL is its query language. TypeDB allows you to model your domain based on logical and object-oriented principles. Composed of entity, relationship, and attribute types, as well as type hierarchies, roles, and rules, TypeDB allows you to think higher-level as opposed to join-tables, columns, documents, vertices, edges, and properties.

Documize Community - Modern Confluence alternative designed for internal & external docs, built with Golang + EmberJS

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Documize Community is an open source modern, lightweight alternative to Confluence. It is built for technical and non-technical users, Designed to unify both customer-facing and internal documentation. It supports Organization through labels, spaces and categories.

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  •    Prolog

TerminusDB is an open-source graph database and document store. It is designed for collaboratively building data-intensive applications and knowledge graphs. If you want to collaborate with colleagues or build data-intensive applications, nothing will make you more productive. It is a native revision control database that is architecturally similar to Git and other distributed version control systems.

Cerebrum : Object-oriented database and knowledge base management system

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The Object-oriented database and knowledge base management system Cerebrum uses network data model. Cerebrum makes it easier for developers to save the state of the complex objects graph or the neural network into the database.

awesome-network-embedding - A curated list of network embedding techniques.


Also called network representation learning, graph embedding, knowledge embedding, etc. The task is to learn the representations of the vertices from a given network.

HyperGraphDB - Database for Storing Strongly-Typed Hypergraphs

  •    Java

HyperGraphDB is a general purpose, open-source data storage mechanism based on a powerful knowledge management formalism known as directed hypergraphs. While a persistent memory model designed mostly for Knowledge management, Artificial Intelligence and Semantic web projects, it can also be used as an embedded object-oriented database for Java projects of all sizes. It could also be used as graph database or as (non-SQL) relational database.

NoLedge - Note taker and knowledge database


NoLedge is an open-source freeware designed to serve as an academic or general notebook. It includes a simple and (hopefully) user-friendly interface and allows the creation of "notes", similar to articles in Wikis. It is also meant to be used as a reference management softwar...

graph-notebook - Library extending Jupyter notebooks to integrate with Apache TinkerPop and RDF SPARQL

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The graph notebook provides an easy way to interact with graph databases using Jupyter notebooks. Using this open-source Python package, you can connect to any graph database that supports the Apache TinkerPop, openCypher or the RDF SPARQL graph models. These databases could be running locally on your desktop or in the cloud. Graph databases can be used to explore a variety of use cases including knowledge graphs and identity graphs. We encourage others to contribute configurations they find useful. There is an additional-databases folder where more information can be found.

nb - CLI and local web plain text note‑taking, bookmarking, and archiving with linking, tagging, filtering, search, Git versioning & syncing, Pandoc conversion, + more, in a single portable script

  •    Shell

and more, in a single portable script. nb creates notes in text-based formats like Markdown, Org, and LaTeX, can work with files in any format, can import and export notes to many document formats, and can create private, password-protected encrypted notes and bookmarks. With nb, you can write notes using Vim, Emacs, VS Code, Sublime Text, and any other text editor you like, as well as terminal and GUI web browsers. nb works in any standard Linux / Unix environment, including macOS and Windows via WSL. Optional dependencies can be installed to enhance functionality, but nb works great without them.

graph-learn - An Industrial Graph Neural Network Framework

  •    C++

Graph-Learn (formerly AliGraph) is a distributed framework designed for the development and application of large-scale graph neural networks. It abstracts a set of programming paradigms suitable for common graph neural network models from the practical problems of large-scale graph training, and has been successfully applied to many scenarios such as search recommendation, network security, knowledge graph, etc. within Alibaba. Graph-Learn provides both Python and C++ interfaces for graph sampling operations, and provides a gremlin-like GSL (Graph Sampling Language) interface. For upper layer graph learning models, Graph-Learn provides a set of paradigms and processes for model development. It is compatible with TensorFlow and PyTorch, and provides data layer, model layer interfaces and rich model examples.

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