Cloud Infrastructures, Services, and IoT Systems for Smart Cities. Second EAI International Conference, IISSC 2017 and CN4IoT 2017, Brindisi, Italy, April 20–21, 2017, Proceedings

Research Article

Comparison of City Performances Through Statistical Linked Data Exploration

  • @INPROCEEDINGS{10.1007/978-3-319-67636-4_1,
        author={Claudia Diamantini and Domenico Potena and Emanuele Storti},
        title={Comparison of City Performances Through Statistical Linked Data Exploration},
        proceedings={Cloud Infrastructures, Services, and IoT Systems for Smart Cities. Second EAI International Conference, IISSC 2017 and CN4IoT 2017, Brindisi, Italy, April 20--21, 2017, Proceedings},
        proceedings_a={IISSC \& CN4IOT},
        year={2017},
        month={11},
        keywords={Statistical datasets Performance indicators Logic reasoning Smart cities},
        doi={10.1007/978-3-319-67636-4_1}
    }
    
  • Claudia Diamantini
    Domenico Potena
    Emanuele Storti
    Year: 2017
    Comparison of City Performances Through Statistical Linked Data Exploration
    IISSC & CN4IOT
    Springer
    DOI: 10.1007/978-3-319-67636-4_1
Claudia Diamantini1,*, Domenico Potena1,*, Emanuele Storti1,*
  • 1: Universita Politecnica delle Marche
*Contact email: c.diamantini@univpm.it, d.potena@univpm.it, e.storti@univpm.it

Abstract

The capability to perform comparisons of city performances can be an important guide for stakeholders to detect strengths and weaknesses and to set up strategies for future urban development. Today, the rise of the Open Data culture in public administrations is leading to a larger availability of statistical datasets in machine-readable formats, e.g. the RDF Data Cube. Although these allow easier data access and consumption, appropriate evaluation mechanisms are still needed to perform proper comparisons, together with an explicit representation of how statistical indicators are calculated. In this work, we discuss an approach for analysis and comparison of statistical Linked Data which is based on the formal and mathematical representation of performance indicators. Relying on this knowledge model, a set of logic-based services are able to support novel typologies of comparison of different resources.