The Eclipse Thingweb project will start with three sub-projects in the toolkit:
node-wot is the official reference implementation of the W3C WoT Working Group and implements the so-called "Servient Architecture":
With 'DATA' being 'the currency of the IOT', having a proper data-sharing technology will be a key-asset in any IOT-platform.
Eclipse Mita is a programming language for the embedded IoT. We combine a declarative setup of system resources (e.g. Bluetooth connectivity or a temperature sensor) with a modern imperative language. We introduce first-class primitives for sensor access and connectivity to other systems, which allows for quick exploration and integration into IoT ecologies. We support embedded algorithm through powerful primitives, e.g. lists, vectors and statistic functions. In order to prevent problems at compile-time Mita has a static strong type-system.
Eclipse Xsemantics is a DSL (implemented in Xtext itself) for writing type systems, reduction rules, interpreters and general relation rules for languages implemented in Xtext. A system definition in Xsemantics is a set of judgment rules which have a conclusion and a set of premises. Xsemantics then generates Java code that can be used in your Xtext-based language for scoping and validation.
Eclipse Xpect is a unit- and integration-testing framework to be used for Xtext-based languages. Test data (e.g. expectations) are embedded into programs written in the DSL under tests. Xpect itself is based on Junit; new test methods can be written in Java and are called by the Xpect framework with the test data.
Eclipse aCute provide development tools for C# and .NET Core inside the Eclipse IDE.
OpenJ9 is a high performance, enterprise calibre, flexibly licensed, openly governed cross platform Java Virtual Machine extending and augmenting the runtime technology components from the Eclipse OMR project (www.eclipse.org/omr) and OpenJDK project (openjdk.java.net).
It is highly optimized for fast startup, low memory footprint, quick ramp-up, and excellent throughput performance, both in dedicated as well as cloud deployments.
The Eclipse Bridge.IoT project aims at igniting an IoT ecosystem by introducing an API (Bridge.IoT API) for interoperability and an online marketplace (Bridge.IoT Marketplace) for providers to offer and monetize their IoT resources (data and services) and for consumers to discover them and access them from their applications and services.
The goal of Eclipse Deeplearning4j is to provide a core set of components for building applications that incorporate AI. AI products within an enterprise often have a wider scope than just machine learning. The overall goal of a distribution is to provide smart defaults for building deep learning applications.
Picasso is a free open-source (Eclipse Public License) web application written in Python for rendering standard visualizations useful for training convolutional neural networks. Picasso ships with occlusion maps and saliency maps, two visualizations which help reveal issues that evaluation metrics like loss and accuracy might hide: for example, learning a proxy classification task.