Insights for Manage Geospatial Big Data in Ecosystem Monitoring using Processing Chains and High Performance Computing

摘要

Big data (BD) is nowadays a research frontier and a strategic technology trend, which is still emerging as a new scientific paradigm in many fields (Chen and Zang, 2014). It is commonly conceptualized by the 3V's model of (Laney, 2009), who defines three dimensions in BD known as: volume (data size), variety (data types) and velocity (production rate); that could be challenging to analyze, especially in large quantities. For these reasons, processing and analysis of BD requires new approaches, which are not suitable for conventional software and hardware. According to (Percival, 2009) Geospatial data (GD) has always been BD but not as it is today, due the accelerated increase and accessibility of geographical technologies (as for example: state-of-art earth observation satellites, mobile devices, ocean-exploring robots, unmanned aerial vehicles, etc.). Moreover, the distribution policies in favor of free and open access to archives are giving way to automated mass processing of large collections of Geospatial data (Hansen and Loveland, 2012). Thereby, this type of data can be considered (under certain conditions), as a synonym of BD which requires not only powerful processors, software, algorithms and skilled data researchers (European Commission, 2014) but also a set of conditions that are not fully met to make possible and accessible the data-intensive scientific discovery.