This is an umbrella repository which holds collections of NGSI-v2 and NGSI-LD tutorials for developers wishing to learn about the FIWARE ecosystem and allow users and developers to easily navigate to the relevant source code, documentation and Docker images.
Note
FIWARE offers two flavours of the NGSI interfaces:
- NGSI-v2 offers JSON based interoperability used in individual Smart Systems
- NGSI-LD offers JSON-LD based interoperability used for Federations and Data Spaces
NGSI-v2 is ideal for creating individual applications offering interoperable interfaces for web services or IoT devices. It is easier to understand than NGSI-LD and does not require a JSON-LD
@context.
However, NGSI-LD and Linked Data is necessary when creating a data space or introducing a system of systems aproach, and in situations requiring interoperability across apps and organisations.
This is a collection of tutorials for the FIWARE ecosystem designed for NGSI-v2 developers. Each tutorial, based around a Smart Supermarket consists of a series of exercises to demonstrate the correct use of individual FIWARE components using NGSI-v2 interfaces and shows the flow of context data within a simple Smart Solution either by connecting to a series of dummy IoT devices or manipulating the context directly or programmatically.
| ๐ฅ Introduction to NGSI-v2 |
๐ NGSI-v2 Tutorial Documentation |
|---|
๐ฏ๐ต ใใฎใใฅใผใใชใขใซใฏๆฅๆฌ่ชใงใใ่ฆงใใใ ใใพใใ
This is a collection of tutorials for the FIWARE ecosystem designed for NGSI-LD developers. Linked data concepts are explained using the entities from a Smart Farm. Each tutorial then demonstrates the correct use of individual FIWARE components via the NGSI-LD interface and shows the flow of context data within a simple Smart Solution either by connecting to a series of dummy IoT devices or manipulating the context directly or programmatically.
| ๐ฅ Introduction to Linked Data |
๐ฅ Introduction to NGSI-LD |
๐ NGSI-LD Tutorial Documentation |
|---|
To download the full set of tutorials, simply clone this repository:
git clone https://github.com/FIWARE/tutorials.Step-by-Step.git
cd tutorials.Step-by-Step/
git submodule update --init --recursiveThe NGSI-v2 and NGSI-LD tutorials are then available under the NGSI-v2 and NGSI-LD directories respectively.
Each tutorial runs all components using Docker. Docker is a container technology which allows to different components isolated into their respective environments.
- To install Docker on Windows follow the instructions here
- To install Docker on Mac follow the instructions here
- To install Docker on Linux follow the instructions here
Docker Compose is a tool for defining and running multi-container Docker applications. A series of *.yaml files
are used configure the required services for the application. This means all container services can be brought up in a
single command. Docker Compose is installed by default as part of Docker for Windows and Docker for Mac, however Linux
users will need to follow the instructions found here
You can check your current Docker and Docker Compose versions using the following commands:
docker-compose -v
docker versionPlease ensure that you are using Docker version 24.0.x or higher and Docker Compose 2.24.x or higher and upgrade if necessary.
The tutorials which use HTTP requests supply a collection for use with the Postman utility. Postman is a testing framework for REST APIs. The tool can be downloaded from www.getpostman.com. All the FIWARE Postman collections can downloaded directly from the Postman API network
Apache Maven is a software project management and comprehension tool. Based on the concept of a project object model (POM), Maven can manage a project's build, reporting and documentation from a central piece of information. Maven can be used to define and download our dependencies and to build and package Java or Scala code into a JAR file.
We will start up our services using a simple bash script. Windows users should download the Windows Subsystem for Linux to provide a command-line functionality similar to a Linux distribution on Windows.
MIT ยฉ 2018-2024 FIWARE Foundation e.V.