From dusk to dome - About the journey of raw data towards visualization

Presentation theme: fulldome

The era of big data comes with chances and challenges, especially for observing sciences like astronomy. Together with modern technology in fulldome systems, we are able to display astronomical phenomena like never before. However, the journey from raw observations towards an appropriate visualization takes place on a rocky road. 

Astronomical surveys contain multiple thousands of data points. Before the information can be used to create expressional images, a number of preprocessing actions like filtering, summarizing, and highlighting is necessary. 

We are going to elaborate on how automatic and semi-automatic approaches help to understand and visualize astronomical data. In the process, we lay eyes on one issue that is familiar to data processing in general, as well as to fulldome visualization in specific: The lack of standardization and infrastructures to process, visualize, prepare and share research data. Various methods exist to prepare raw data, but all so often the outputs of different methods are incompatible. Likewise, there are multiple types of visualization and imagery available for fulldome systems, but not all types are supported by every system. We will discuss how solutions for this problem can be applied to both ends of the pipeline with the ultimate goal of one smooth road from arbitrary raw data to a multi-compatible visual output.

Image © Arena Berlin