DeepCube: Ontologies for Semantic Data Cubes

To be able to implement a semantic data cube for a use case, we need to define an ontology for the data cube and the relevant external data sources that we would like to query. This ontology will be used to semantically enrich the data cube and the external data sources. In DeepCube, we have created the first version of the ontologies for the following use cases:

• UC2 - Climate induced migration in Africa
  In the current context of climate change, extreme heat waves, droughts and floods are not only impacting the biosphere and atmosphere but the anthroposphere too. Human populations are forcibly displaced, which are now referred to as climate-induced migrants. On the agenda of the United Nations Framework Convention on Climate Change (UNFCC), for instance, there is an item dedicated to migration, displacement and human mobility. The problem has obvious environmental, societal and economic implications, in both adaptation and mitigation to climate change, as well as for assistance to their home states. Modeling, anticipating, characterizing and understanding the severity of migration flows and the direct and latent factors are of paramount relevance.

• UC3 - Fire hazard short-term forecasting in the Mediterranean
  Climate change is playing an increasing role in determining wildfire regimes, with future climate variability expected to enhance the risk and severity of wildfires in many biomes including Southern Europe, according to the 2019 IPCC Report. Current 1-in-100-year fire events (burned area) could occur every 5 to 50 years in Europe by 2100. Scenarios for global warming greater than 1.5°C could lead to a 40% increase in Mediterranean burned area. Fire hazard forecasting systems linked with the operational authorities (Civil Protection, Fire Brigade/Service etc.), would increase their preparedness and enhance the emergency response capacity. This is the focus of this UC.

• UC5 - Copernicus services for sustainable and environmentally-friendly tourism
  Tourism is one of the pillars of the modern economy. It constitutes more than 10% of global GDP with a CAGR of 3+%. The number of international tourists is expected to hit the 1 Billion bar in 2020 and forecasted to rise to 1.8 Billion in 2030, making it crucial to find efficient ways to handle this growth, preserve the fragile destinations and adapt to the increasing demand over limited hospitality infrastructures. Additionally, more than 65% of European travellers have declared that they are striving to make their travels more sustainable but do not find the right information or the possibility to assess their environmental footprint.

The ontologies are developed using the Web ontology language OWL2, and enable access to the Semantic Data Cube through semantic web technologies, but also integration with Linked Open Data (LOD).