Semantics-based services for a low carbon society: An application on emissions trading system data and scenarios management

Abstract

A low carbon society aims at fighting global warming by stimulating synergic efforts from governments, industry and scientific communities. Decision support systems should be adopted to provide policy makers with possible scenarios, options for prompt countermeasures in case of side effects on environment, economy and society due to low carbon society policies, and also options for information management. A necessary precondition to fulfill this agenda is to face the complexity of this multi-disciplinary domain and to reach a common understanding on it as a formal specification. Ontologies are widely accepted means to share knowledge. Together with semantic rules, they enable advanced semantic services to manage knowledge in a smarter way. Here we address the European Emissions Trading System (EU-ETS) and we present a knowledge base consisting of the EREON ontology and a catalogue of rules. Then we describe two innovative semantic services to manage ETS data and information on ETS scenarios. Accepted Author Manuscript 2 and different countries. Managing such complexity requires tackling several issues. Among them, we cite those covered in this work:1. need for an integrated environmental modeling (IEM) approach. LCS concerns multi-disciplinary and inter-dependent knowledge. IEM is considered as one of the most promising approaches to define break-through solutions leveraging on such knowledge [Laniak et al., 2013] [Argent, 2004. 2. sharing common understanding. A complete scenario (made by the mix-up of energetic, industrial, technological, political and environmental aspects) should be framed into a shareable "scientific" formulation. The importance of involving a multidisciplinary community of people [Laniak et al., 2013] [Krueger et al., 2012 is a precondition to reach such understanding. 3. structural and behavioural knowledge modelling. The LCS domain concerns both the structural aspects of entities (e.g., the energy price) and others related to how entities behave or should behave (e.g., the allocated CO2 emissions of the ACME company are 3710 4 tCO2). A modelling approach covering both aspects is required. 4. managing large governmental datasets. LCS data are needed for LCS analysis and definition of scenarios. Although their availability from governments might be an issue [Zicari, 2013] due to the lack of competitive pressure for making data open, one problem is to assess their quality and veracity since such data are usually manually collected by error-prone processes. Further relevant problems related to data management concern data integration and data privacy. 5. need to develop multi-domain scenarios. In order to use "federated" scenarios, all the problem's components should be made interoperable and fed into a common scheme. The present work proposes a semantics-based approach to address these issues. Indeed, semantic technologies based on ontologies help to better organize data [Poggi et al., 2008] [Reichman et al., 2011] and enable development of intelligent services for data management (e.g., to...

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