Virtual Reality Exhibition Manager (VREM)

The Virtual Reality Exhibition Manager (VREM) is a tool that allows for configuration, storage of and access to VR exhibition definitions.
While VREM acts as a back end, the exhibitions can be viewed in the Virtual Exhibition Presenter (VREP) (Unity).
For the Angular UI see VREM-UI. It has been created as part of the Open Cultural Data Hackathon 2018, held in Zurich, Switzerland.

Prerequisites

Below is a very shortened version of the setup guide on how to setup VREM.

System dependencies

• Git
• JDK 11 or higher
• You will require MongoDB as storage engine. We recommend using Docker. If you have installed docker, you can start a new container using docker run --name vrem-container -d -p 27017:27017 mongo. If you already have a container, restart it using docker start mongo. If you're on a unix-system, use the launch_db.sh script.

Building VREM

VREM can be built using Gradle. Building and running it is as simple as:

 ./gradlew clean distZip
 unzip build/distributions/virtual-exhibition-manager-$
 virtual-exhibition-manager-$/bin/virtual-exhibition-manager <command>

Make sure you have the correct working directory set so VREM can properly import exhibitions and serve content.

Starting a server

Before starting, you should adapt the configurations in your config.json file (see example file).
After doing so, you may serve stored exhibitions by running VREM with the following command:

 virtual-exhibition-manager-$/bin/virtual-exhibition-manager server -c /path/to/your/config.json

Importing an exhibition

By using the import-folder command, you can import a stored exhibition to the running MongoDB instance in order to be able to serve the exhibition via the servercommand afterwards.
The following command imports a collection from the data/import/my_exhibition folder (relative to VREM's directory):

import-folder --config=config.json --path=data/import/my_exhibition --name=demo

Since the images themselves are not stored in the database, VREP will maintain a folder containing the exhibition images in data/ (relative to VREM).

For an exhibition example, consult the repository at https://github.com/VIRTUE-DBIS/vre-mixnhack19.