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The topic description

Gaia is an ambitious ESA mission to chart a three-dimensional map of our Galaxy, with a first data release towards the end of 2016. Gaia will provide unprecedented positional and radial velocity measurements with the accuracies needed to produce a stereoscopic and kinematic census of about one billion stars in our Galaxy. The Astronomical community has never been faced with such a exciting but challenging task.

The goal of this project is to get a first contact with the newly released astronomical data base and perform a clustering analysis towards a search for new types of astronomical objects or groups of objects. This will be done on a sub-set of the full data, for which distances are known (about 2 million stars). We will first identify known groups of stars, extract parameters, and search for so far non identified, or previously ill-defined objects or structures. More information.

The project type

Gaia provides Datasets with a huge amount of entries including the location, magnitudes and distances of over 1 billion stars. Thus it would be interesting to visualize this dataset to find out even more about it. Therefore we chose to work on a Design Study Project where the main goal is to create a visualization system for a given task. Because of this we think this approach would work well with our Project Topic.

Target application

There are some applications that can be helpful for completing our project. We met with Joao Alves and then later with his PhD Student. They gave us some ideas and also softwares that can help us to understand the Gaia Catalogues better. For gaining insight on the data, we use Topcat and Glue. For prototyping, we will use Tableau. And for the end project, we will work with D3 and Javascript.

Dataset

We want to use Gaia's first dataset, which was collected on September 14th in 2016. These data contains positions, distances, values of motions, characteristics, as well as magnitudes etc. — all important data that characterizes more than a billion space objects using the TGAS (Tycho-Gaia Astrometric Solution). This dataset and more detailed information about it can be found here.

Users

Of course we want to create a vizualisation that is understandable for almost every audience. After some brainstorming we decided to choose scientific students as our target group and provide our graphics for educational purposes. Certainly, they are not as familial with astronomical data as scientists in this area but still have a basic understanding of scientific knowledge. Our graphics should help students from areas such as computer science, nature sciences or Mathematics with important tasks, i.e. implementing a clustering analysis or creating statistics based on the Gaia dataset. Anyway, our images should only provide a guideline how the dataset should look like, so it can be used as a reference. Besides our vizualization could also find its use in university courses or educational programs for students, mostly in astronomy.

Tasks

First of all, we need to study the data and terminology.

We must properly prepare the data, for example apply grouping and filtering. We need to minimize the probability of making mistakes, so that the data is shown in a meaningful way.

Determine what exactly we want to visualize, what would be really interesting and useful for our target audience.

Creating prototypes based on the decisions in in the previous paragraph.

Actually visualize the data based on our prototypes.

Create a kind of interaction and animation between our graphics to allow the user to manipulate the data and see not only the general context of the dataset, but also the specific vision of a particular problem.

System Design: improving our visualization system, comparing it to our prototype, further adjustments.

Proposed solution

It is hard to create a specific description here, as it is only the first Step of the Project, but I think the descriptions above already tell the most important. As already described earlier, we want to provide a simple vizualization design for our target audience. It should be easy to understand and not be overloaded with complicated information. So we will use the design principles from the VIS lecture in order to create a clear scientific representation of the Gaia Dataset in Tableau so our users can get out the most of the data.

Work distribution

The work distribution in our group was fairly equal. We met and made the brainstorming together.

Visual data analysis 2017