Skip to content

Latest commit

 

History

History
126 lines (78 loc) · 5.39 KB

README.md

File metadata and controls

126 lines (78 loc) · 5.39 KB

shacl-vue

THIS REPOSITORY IS UNDER CONTINUOUS DEVELOPMENT

Overview

shacl-vue is an effort to create a web-based user interface for entering, editing, and viewing linked (meta)data using a VueJS application driven by the Shapes Constraint Language (SHACL).

Think of it as an automatic builder that you just have to feed with a model of your data. If you have a SHACL schema, or a schema in a format that can be exported to SHACL, then you're good to go. No need to build custom forms for data entry, no need to struggle with post-entry data validation, no need to create a catalog application that renders all the entered data. shacl-vue does all of this automatically.

shacl-vue is built with VueJS 3, Vuetify frontend components, and Vite build tools, and was heavily inspired by the WC3 Draft: Form Generation using SHACL and DASH. For reading, manipulating, and writing RDF data (including shacl), the package uses libraries compatible with the RDF/JS specifications (see also: https://github.com/rdfjs-base)

Links

Installation and usage

shacl-vue can be installed from npm:

npm install shacl-vue

Use as a library

The npm package currently provides the named export ShaclVue:

import { ShaclVue } from 'shacl-vue'

This is the main configurable VueJS component that is used to render all functionality of shacl-vue. It can be instantiated inside a VueJS application as follows:

<template>
    <ShaclVue :configUrl="myconfig"></ShaclVue>
</template>
<script setup>
    const myconfig = 'config.json'
</script>

Here, config.json is used to configure the properties of the specific shacl-vue deployment. See examples here, and here.

For the above to work, the VueJS application will have to install Vuetify and the ShaclVue might need to be registered explicitly.

Use as a standalone site

The build steps of shacl-vue produce both the library as well as a set of static files that can be served as a standalone site. The abovementioned metadata annotation tool of the TRR379 Research Consortium deploys shacl-vue in this manner, and its source code can be viewed here.

To use shacl-vue to deploy a standalone site, follow the build steps below. In addition, a deployment-specific confi file should be provided.

Local development and building

The shacl-vue source code can be cloned for local development, testing, or building. First clone the repository:

git clone https://github.com/psychoinformatics-de/shacl-vue.git
cd shacl-vue

Then create a local NodeJS virtual environment, e.g with micromamba:

micromamba create -n <my-env-name> nodejs
micromamba activate <my-env-name>

Then install the application:

npm install .

Local rendering during development

To serve the application locally in order to test it in the browser, run:

npm run dev

Build steps

To build the library (output at /dist/lib):

npm run build:lib

To build the standalone site, i.e. VueJS application (output at /dist/app):

npm run build:app

To build both the library and the standalone site:

npm run build

Testing

Testing remains a primary TODO for this package, although a minimal test is in place to check whether the named exports can be imported into a new project. Testing is done with Vitest.

npm run test

Dependency on shacl-tulip

In an effort to generalize shacl-vue for improved use by and interoperability with other applications, the underlying functionality was factored out and packaged as the shacl-tulip library (like "shacl-vue-lib"). shacl-tulip provides the main (derived) classes for handling RDF data and related form data. It is completely independent of VueJS, yet class constructors allow passing reactive objects as arguments, which shacl-tulip handles seamlessly. It also focuses purely on library-level functionality (including utilities that were previously part of shacl-vue), and contains no frontend code. shacl-vue imports shacl-tulip classes and uses them mainly in its composable code.

Acknowledgements

This work was funded, in part, by

  • Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under grant TRR 379 (546006540, Q02 project)
  • Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under grant SFB 1451 (431549029, INF project)
  • MKW-NRW: Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen under the Kooperationsplattformen 2022 program, grant number: KP22-106A