  In a decentralized household energy system consisting of various devices such
as washing machines, heat pumps, and solar panels, understanding the electric
energy consumption and production data at the granularity of the device helps
end-users be closer to the system and further achieve the sustainability of
energy use. However, many datasets in this area are isolated from other domains
with records of only energy-related data. This may raise a loss of information
(e.g. weather) that is relevant to the energy use of each device. A noticeable
disadvantage is that many of those datasets have to be used in computational
modeling approaches such as machine learning models, which are vulnerable to
the data feed, to advance the understanding of energy consumption and
production. Although such computational methods have achieved a high benchmark
merely through a local view of datasets, the reusability cannot be firmly
guaranteed when the information omission is taken into account. This paper
addresses the data isolation problem in the smart energy systems area by
exploring Semantic Web techniques on top of a household energy system. We
propose an ontology modeling solution for the management of decentralized data
at the resolution of a device in the system. As a result, the scope of the data
concerning each device can be easily extended to be wider across the web and
more information that may be of interest such as weather can be retrieved from
the Web if the data are structured by the ontology.
