Overview

We are aiming to create a one stop resource, providing information on all exploratory missions to other planets and objects in the solar system, including the information we learned and the new technologies developed for each mission.

The demo of the resource presents all of the successful missions to Mars, with the key information about the flights, simplified spacecraft trajectories, the collection of images returned, and interesting factoids about the mission.

Our goal is to make the information more accessible for those not wishing to navigate through the jungles of Wikipedia, NASA and JPL microsites to find the core information they need. All the links to these resources are available through our site, however, for those who want to study a particular mission in more depth.

Dataset

The key to this project is the curated dataset produced from existing internet resources. In many cases the dataset links out to external sources where they are available and serves as an aggregating mechanism for the vast amount of existing data across many different sites. The dataset produced here is a sample focusing on the Mars missions and in the future would be expanded with additional tagging and keywords whilst bringing in a much broader set of data than was possible during the hack.

Tech-tree proof of concept

As part of the dataset construction we produced a graphical proof of concept, available in the linked folders, of how mission technologies and objectives may be visualised as part of a technology tree, leading towards key milestones. This concept was borrowed from the visualisation often found in computer games and tries to add context to a lot of the science going on in each mission.

Web App

The web development team used the Mars missions as a template, to create an intuitive interface presenting the key data, as well as a set of data management tools, to simplify future expansion of the resource to include all solar system missions.

The web app serves as one demonstration of a way of using the dataset but we envisage other people coming up with ways to use this data. It tries to present the chronology of space missions in as simple a manner as possible. It consists of a visualisation of the solar system - distances to scale, with the ability to zoom out as far as Voyager 1. Mousing over each planet will give crucial mission statistics such as number of successful / failed missions. Clicking on a planet will open a mission timeline for that planet and clicking on a mission on the timeline will open an info panel for that mission.

In addition to the base dataset, the web app tries to find a new method of viewing flight paths for missions. Mariner 4 and Curiosity show basic fly by / direct transfer paths plotted on top of the solar system view and this image shows what we this the Cassini mission may have looked like. This visualisation is in no way accurate but just aims to give new users a feel for what the flight path was without them needing to be familiar with any orbital dynamics.

The web app is constructed using HTML5 and JavaScript using a number of libraries (JQuery, Grunt, Bower, Require.js, Mustache.js) and pulls in a sample JSON file from the data tools containing the Mars missions. The app has been tested in the latest version of Google Chrome.

Data tools

Alongside the dataset, as seen in the Google docs folder and sample data included in the Website project, two members of our team also produced a Java EE tool for maintaining the dataset, although these are not live at the moment, once hosting is sorted they will be available for other to modify the dataset. Alternatively, the dataset is available as a JSON download so changes can be made directly with pull requests in Github.

Next Steps

The next stage of the project will be be to collect data on all remaining space missions. This data will be imported using the data tools we created, and the Mars interface will be used as a template for the other planets. The web app will be finalised and published and the tech tree taken from proof of concept to product. Following this we will be focused on expanding the dataset to include more expert level information to enable more detailed visualisations.

Project Information

Resources