An ontological approach to dynamic fine-grained Urban Indicators

Publication Type:
Journal Article
Citation:
Procedia Computer Science, 2017, 108 pp. 2059 - 2068
Issue Date:
2017-01-01
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© 2017 The Authors. Published by Elsevier B.V. Urban indicators provide a unique multi-disciplinary data framework which social scientists, planners and policy makers employ to understand and analyze the complex dynamics of metropolitan regions. Indicators provide an independent, quantitative measure or benchmark of an aspect of an urban environment, by combining different metrics for a given region. While the current approach to urban indicators involves the systematic accurate collection of the raw data required to produce reliable indicators and the standardization of well-known commonly accepted or widely adopted indicators, the next generation of indicators is expected to support a more dynamic, customizable, fine-grained approach to indicators, via a context of interoperability and linked open data. Within this paper, we address these emerging requirements through an ontological approach aimed at (i) establishing interoperability among heterogeneous data sets, (ii) expressing the high-level semantics of the indicators, (iii) supporting indicator adaptability and dynamic composition for specific applications and (iv) representing properly the uncertainties of the resulting ecosystem.
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