AIDA uses some of the most advanced data analysis techniques to analyse the data available from space missions and from space simulations. AIDA identifies three major trends in our field of research and in the wider society.
First, there has been a tremendous accumulation of data from space studies. Every new space mission accumulates new data. But every new mission also increase the amount of data, its quality and resolution compared with previous missions, leading to an ever increasing quantity of data. Similarly, the computer simulations of space science are becoming ever more complex and their results are more detailed and rich, also leading to a rapidly increasing mass of data available.
All this data is becoming progressively more openly accessible. The data from space missions is now regularly made available to the public and even the results of simulations start to be shared in public databases. General databases of space data are also being created. AIDA intends to develop tools to make this data more readily accessible to the public, creating common standards for storing data when such standards do not yet exist while using community standards whenever possible. This advancement will be achieved by federating existing tools and creating new ones into AIDApy, the main outcome of the AIDA project: a software tool to gather and analyse space-relevant data from observations and simulations.
Second, the vast amount of space data accumulated by past missions and past simulation studies and the new data generated every day by new and ongoing missions and by new simulations is becoming so large that a single human brain cannot grasp its entire complexity. Luckily, a trend in sweeping society to address this very same problem arising in every aspect of human activities: machine learning and artificial intelligence (AI). AIDA wants to bring the latest developments in AI to the space arena (AI in AIDA is indeed Artificial Intelligence for Data Analysis, AIDA). The competences and passions needed to be a space scientist are quite different from those of an expert in artificial intelligence. AIDA brings together expertise in computer science, AI and space science to create a new tool AIDApy that will make the use of AI simpler for the space scientist and even the general public.
Third, there is an ongoing trend in all big data analysis and in AI in particular to move towards a free open source language for computers called python. The space community is traditionally linked primarily with MATLAB and IDL. These are commercial tools of highly refined tools that come at a very high cost, although non profit organisations and students can obtain better deals. To truly democratize science, including the so-called trend in citizen science, to promote its spread in developing countries and to simplify access to the data and its analysis to all, python provides a free alternative. Python potentially has even more features than those commercial alternatives and many science communities are currently making the transitions to it. AIDA aims at fostering this same transition to python also for the space community, collecting in AIDApy (where py stands for python) tools previously based on non-free languages. And developing new tools based on the most advanced tools in the state of the art.
As this brief summary clarifies, the aim of AIDA is as much scientific as it is directed at transforming the way society can access the results of space missions and space simulations, making the data accessible to all and giving to all, including non expert citizens, access to the most modern