David Moreno

BabiaXR is a set of front-end FOSS modules for VR data visualization for the browser. BabiaXR is composed of different modules (for querying, filtering, and representing data) based on A-Frame and Threejs, with the goal of making it very easy to create different kinds of data visualizations (bar charts, bubble charts, cities, ...), by exploiting the power of WebXR and regular web front-end programming.

There are plenty of tools that can analyze data in many ways, most of them are composed of a full-stack app, and the well-known front-end libraries limit the visualization on the 2D and screen environment, just a few of them try to visualize this data in the browser integrating other technologies/environments like webXR. This is the goal of BabiaXR, a set of front-end modules for 3D and VR (virtual reality) data analysis. The visualization part of BabiaXR is based on A-Frame and Threejs, providing a collection of components for querying data, filtering data, and creating different kinds of visualizations, all of them developed using just front-end technology. Among the visualizations, there are common ones like bar charts, pie charts, bubbles chart, but now we are moving beyond that, exploring new ways of show data in 3D/VR. For example, we are working on representing software projects using the city metaphor, showing the evolution of the project as the evolution of a city, with building corresponding to the different files. In this talk, I will do an overview of BabiaXR, showing different examples of the power of WebXR and A-Frame with different visualizations, and how simple is to develop this kind of module using just JavaScript and other front-end libraries. Then, I will analyze a city corresponding to a well-known FOSS project, showing its evolution in different time snapshots and explaining how the code evolves as the city does.

There are plenty of tools that can analyze data in many ways, but just a few of them try to visualize this data in new ways. This is the aim of VBoard, a 100% open source web application that allows building visualizations and dashboards in 3D and VR using A-Frame as its core render library. The data is retrieved in real time using a ElasticSearch, and VBoard saves its objects (visualizations, dashboards) in it.

In this talk I will show the functionality of VBoard, starting with a general overview, its installation steps and a simple step by step user guide. All of this in order to build a 3D and VR dashboard from scratch. To finish, I will show examples of what kind of visualization/dashboard you can build with VBoard using data retrieved with GrimoreLab related to open source projects (e.g., commits, usernames, repositories, etc.).

The goal of VBoard is to have a complex data visualization system in a 3D and VR environment. It started as my master's thesis and finally became a web application that uses A-Frame as the visualization render engine and ElasticSearch as a database and search engine. Specifically, VBoard rests on A-FrameDC to show these data visualizations, A-FrameDC is a JavaScript library to create different kind of data visualizations based on A-Frame. A-FrameDC extends A-Frame, encapsulating it in another library so that the construction of 3D elements is focused on data visualization graphics and it allows the creation and interaction with them in a simple way. This library allows the creation of different kinds of charts, from the simplest 2D charts like pies to 3D charts like bubbles. VBoard takes advantage of A-FrameDC using it in a web interface, making the visualization building process easy and scalable, permitting also the persistence of the objects (visualization and dashboards) saving it in the same ElasticSearch that it does the queries.

The talk will show how to create visualization and dashboards with VBoard. I will start by explaining how to install it in a few steps. I will show how to import open source project data (e.g., commits, usernames, repositories, organizations, etc.) to ElasticSearch using GrimoireLab in order to build the visualization with it. Then, I will build visualizations from scratch, showing its features and usability. You will see how simple it is to create a 3D and VR dashboard that relates useful data like the relation of users with repositories, organizations, etc.

According to Wikipedia, Community is "a small or large social unit (a group of living things) who have something in common". If we want to analyze any Open Source development community, it's key to understand the relationships of the people that define that community. Open Source communities provide many ways for peers collaboration beyond participation in forums and mailing lists. In any case, people graph or network analysis is one the methodologies used for social interaction analysis. During this talk, I'll show social network analysis with a free, open source software Kibana plug-in integrated in GrimoireLab. I started this project during my degree thesis, 6 months ago, and once it was released everything has changed. People started to download the plugin and contribute to it. Now, the repository hosting the plugin has more than a hundred thousand clones and a hundred of daily visits. The talk will show how to use the Network plugin in order to analyze open source projects. I'm going to show data retrieved from an open source project and I will show that with differents types of networks/graphs.

This Kibana Network plugin has, as the main aim, the integration of visualization systems of social networks in complex systems of visualization and data interaction based on open source. It relies on Kibana as a complex system of data visualization and ElasticSearch as the database. In order to integrate these visualization systems, a Kibana plugin has been developed to visualize this data in a social network way. The plugin is an open source project, uses open source libraries, and it is completly integrated in Kibana (using its components). Hence, it's integrated in GrimoireLab to allow social network analysis in open source development communities. The talk will show how to use, and create graphs with it. I will show how to import open source project data (e.g., commits, usernames, repositories, organizations, etc.) to ElasticSearch form GitHub (or other sources) using GrimoireLab. I will build a graph visualization from scratch, showing its features and usability. You will see how simple it is to create a network that relates users with repositories, organizations, etc. in order to show how a community is related in their own projects. Finally, the talk will explain how a graph/network can be integrated into a dashboard with other visualizations, and how to deal with real time data and filters in order to show what it's happen in the community instantly. Since I started its development, many people contributed, tested and downloaded it. As a consequence, the plugin has evolved and adapted to the community needs. The plugin has had a big impact in the ElasticSearch and Kibana community, and currently it has more than a hundred thousand clones and it receives a hundred of daily visits. Kickstarting and managing this open source project has been a great experience for me, and now I understand more how to contribute, get involved and improve a project in a big open source community. And I hope you can find it useful for your communities too.

• Network plugin

• Network plugin Repo

• GrimoireLab