The EU SatCen organised on Thursday 4th of May 2017 (11.00-12.00 CET) an Hangout session on “Big Data for Secure Societies” in the framework of the BigDataEurope project and with regard to the “Secure Societies” Horizon 2020 Societal Challenge. The Hangout was the fourth of a scheduled series in the BigDataEurope project for the Secure Societies domain and it has been followed by attendees coming from EC, EU entities, ESA, private companies, universities and other public entities from a variety of domains in Secure Societies.
Back in March I attended the latest workshop in the Location Powers series organised by the Open Geospatial Consortium, OGC, with which W3C has an excellent and fruitful relationship. The theme for the day was Geospatial Linked Data and speakers included BDE partner Manolis Koubarakis of the University of Athens who talked about his work on using satellite data to monitor the effects of wild fires in Europe. It is that work that created the Strabon triple store that is one of the components in the BDE Integrator platform and that is used in the Societal Challenge 7 pilot on using satellite imagery to detect change on the ground.
What struck me particularly throughout the day was the ubiquity of the problems faced when dealing with large amounts of data: the focus always has to be on efficiency and performance. In the BDE Integrator platform, a semantic layer allows a SPARQL query to be executed across all the available data, irrespective of format, as the Ontario feature effectively creates a virtual graph at query time. This means that only the specific pieces of data needed to answer the query are examined, offering substantial performance increase over the more obvious method of converting all data to triples (or any other single format) at ingestion. Manolis described a very similar approach using Ontop and its spatial extension.
There was also a lively discussion about the need for being able to handle RDF triples not as immutable facts but as statements that are true for a defined period of time and/or with a probability of being true. That’s the kind of extra dimension needed for machine learning, AI and analytics engines – like the SANSA stack available in the BDE Integrator Platform.
The European Space Agency together with GEO, FAO and EU have organised the WorldCover 2017 Conference, hosted in ESA-ESRIN (I) from 14 to 16 March 2017.
The WorldCover 2017 Conference was the opportunity to present first-hand and up-to-date results from on-going research and application development activities by using data from past and current satellites for Land Cover studies.
The event was open to final users, scientists, students, representatives from National, European and International Space Agencies, Value Adding Industries, Laboratories and Universities.
The EU Satellite Centre (SatCen) participated with an oral presentation entitled “Land Cover data to support a Change Detection system for the Space and Security community” given by Sergio Albani, Responsible for RTDI (Research, Technology Development and Innovation).
The presentation showed the progresses on the development of the RTDI prototype platform, built on the results of different Big Data and Cloud Computing projects (e.g. BigDataEurope).
The platform aims at improving the capacity to manage and exploit a huge amount of heterogeneous data to timely provide decision-makers in the Space and Security domain with operational (i.e. clear and useful) information. The platform offers services to access, storage, process and visualize data; one of the core services is the Change Detection, which can benefit from the integration of collateral information such as Land Cover maps.