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R4SC Guidelines for Linked Energy Data generation and publication

The Ready4SmartCities consortium has published guidelines for Linked Energy Data generation as part of deliverable D4.1 as well as publication as part of D4.2.

Adoption of Semantic Web standards and technologies in the energy domain promises to enable a new energy data ecosystem that will support the interoperability and exploitation of energy-related data, which is the main task of the READY4SmartCities project. Linked Data is the key paradigm of the Semantic Web movement, a new generation of the World Wide Web, and a large number of both private and public companies and institutions from various domains have generated and published Linked Data. However, this is not the case in the energy domain – the number of companies that have their data following the Linked Data principles is rather low.

The process of Linked Data generation is an intensive engineering process and requires high attention in order to ensure the high quality of the produced Linked Data. Therefore, in the READY4SmartCities project we have developed a set of guidelines for generating and publishing Linked Data in the energy domain. These guidelines have been developed having in mind requirements derived from a survey that investigated various companies in the energy domain, as well as from well-established ISO and AENOR standards related to Linked Open Data and Smart Cities.

The Linked Data generation and publication guidelines help organizations in the energy domain from both public and private sectors in generating and publishing Linked Data, by providing detailed descriptions of each task in the generation and publication process. Furthermore, the guidelines contain several examples of Linked Data generation and publication, giving a more detailed view and helping interested parties to better understand the process.

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Ready4SmartCities

The READY4SmartCities project intends to increase awareness and interoperability for the adoption of ICT and semantic technologies in energy system to obtain a reduction of energy consumption and CO2 emission at smart cities communities level through innovative relying on RTD.
Energy