The sheer vastness of space is almost impossible to imagine, all of those planets, stars, and solar systems that make up the many universes, all waiting to be explored and understood. This is one of the great challenges for NASA in the 21st Century, to begin to understand the universes around us, how they came to be, how they are changing, as well as try to answer the big question of ‘is there life out there?’ This is in no way a small feat, as technology advances, progress also needs to be made in data analysis in order to keep up, otherwise huge amount of data are collected but not interpreted. This is the current situation with the Hubble telescope 1 taking constant detailed images of the universe. Huge amount of data accumulates but it needs interpreting. This is not an easy task, because of the subtlety of many of the images, computers cannot yet distinguish the shapes and outlines and accurately determine what type of astral body it is, or if in fact it is just an artifact.
This has lead to the rise of several projects, one of which relies on people around the world who have an interest in space and who want to help out, joining the network “Galaxy Zoo” 2 which allows members of the public to go through the images that have been collected and classify them in to categories. This is quite enjoyable and you get to see many incredible images taken by the telescope. However, this is obviously a slow process relying on people accurately being able to classify the images by hand, and several people need to classify each image to make sure its accurate, whilst it is enjoyable and you can have your name referenced when any discoveries are made; it is labor intensive and not efficient.
Another route being explored is looking for people with knowledge of computer programming and machine learning to get involved 4 in designing a program able to analyse these images accurately, making the process more efficient. Derren Brown recently wrote about this on his blog 3, and although this would not easy to design, computer algorithms would be more desirable in the long run.
Over all, it is nice to know that ordinary individuals can contribute to the great discoveries currently taking place in physics and astronomy, and that when groups of people get together and help each other great problems can be over come. We are a long way off understanding all of the data currently collected, but we are slowly moving forward, and with each step we get closer to really understanding the universe we live in and how we came to be here.