Big data management and processing in the context of the system wide information management

The 4D trajectory management program will require a major shift in infrastructure and operational management processes to deliver accurate and reliable information to trajectory management team. As a result, air traffic management operation will demand Network Enabled Operations (NEO) concepts such as the System Wide Information Management (SWIM) framework to ensure that the decisions are made with the correction information at the right time. SWIM provides standards, infrastructure, and governance practices to allow information exchanging through interoperable services. Consequently, SWIM must provide methods to (a) integrate a large variety of data; (b) filter information in a way that only the relevant ones are retained to explain the results; (c) enable National Airspace System (NAS) operators, pilots, controllers, and traffic flow specialists to extract value of air traffic systems in real-time; and (d) to seek and explore complex and evolving data's relationships. However, SWIM still lacks support to deal with big data analytics and to aggregate computing resources on-demand. As the main contribution of this paper, we describe the challenges and new focuses of SWIM researches. Likewise, we present an architecture to enable big data analytics services in SWIM. The proposed architecture relies on big data processing frameworks to handle data acquisition and data filtering on near-real time taking into account users' objectives; and to guarantee that the data go through all the gives stage of the life cycle of ATM applications, avoiding the silos that may happen in each data analysis stage.