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Part of the book series: Modeling and Optimization in Science and Technologies ((MOST,volume 4))

Abstract

In the last decade big efforts have been carried out in order to move towards the Smart City concept, from both the academic and industrial points of view, encouraging researchers and data stakeholders to find new solutions on how to cope with the huge amount of generated data. Meanwhile, Open Data has arisen as a way to freely share contents to be consumed without restrictions from copyright, patents or other mechanisms of control. Nowadays, Open Data is an achievable concept thanks to the World Wide Web, and has been re-defined for its application in different domains. Regarding public administrations, the concept of Open Government has found an ally in Open Data concepts, defending citizens’ right to access data, documentation and proceedings of the governments.

We propose the use of Linked Open Data , a set of best practices to publish data on the Web recommended by the W3C, in a new data life cycle management model, allowing governments and individuals to handle better their data, easing its consumption by anybody, including both companies and third parties interested in the exploitation of the data, and citizens as end users receiving relevant curated information and reports about their city. In summary, Linked Open Data uses the previous Openness concepts to evolve from an infrastructure thought for humans, to an architecture for the automatic consumption of big amounts of data, providing relevant and high-quality data to end users with low maintenance costs. Consequently, smart data can now be achievable in smart cities.

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Emaldi, M., Peña, O., Lázaro, J., López-de-Ipiña, D. (2015). Linked Open Data as the Fuel for Smarter Cities. In: Xhafa, F., Barolli, L., Barolli, A., Papajorgji, P. (eds) Modeling and Processing for Next-Generation Big-Data Technologies. Modeling and Optimization in Science and Technologies, vol 4. Springer, Cham. https://doi.org/10.1007/978-3-319-09177-8_18

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  • DOI: https://doi.org/10.1007/978-3-319-09177-8_18

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