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Using linked open geo boundaries for adaptive delineation of functional urban areas

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Abstract

The concentration of people, companies, research organizations and other activities in urban areas is a key process in the development of economies and societies. In order to investigate how these urban systems function, the OECD (Organization for Economic Co-operation and Development) in collaboration with EC (European Commission) and Eurostat have introduced the concept of Functional Urban Areas (FUAs). FUAs consider a preliminary set of socio-economic and environmental factors and provide a basis for an agreed definition for measuring development of metropolitan areas. However, because FUAs are predefined they do not meet the need for designing policies and research questions involving different types of urban areas that are defined by weighting some factors more than others or by using additional factors. Therefore, providing an adaptive approach for dynamic and multi-faceted delineation of FUAs, rather than merely relying on a rigid schema with a fixed list of FUAs per country, allows to more flexibly reflect the socio-economic geography of where people live and work. This adaptive definition of FUAs demands integration of data from multiple up-to-date linked data sources. In this paper, we describe an approach and implementation for a Linked Open Geo-Data space, which combines openly available spatial and non-spatial resources on the Web to classify urban areas with the aim to more flexibly monitor and research urban development.

Original languageEnglish
Title of host publicationThe Semantic Web: ESWC 2018 Satellite Events: Revised Selected Papers
Subtitle of host publicationESWC 2018 Satellite Events, Heraklion, Crete, Greece, June 3-7, 2018, Revised Selected Papers
EditorsAldo Gangemi, Anna Lisa Gentile, Andrea Giovanni Nuzzolese, Sebastian Rudolph, Maria Maleshkova, Heiko Paulheim, Jeff Z. Pan, Mehwish Alam
PublisherSpringer/Verlag
Pages327-341
Number of pages15
ISBN (Electronic)9783319981925
ISBN (Print)9783319981918
DOIs
Publication statusPublished - 2018
Event15th Extended Semantic Web Conference, ESWC 2018 - Heraklion, Greece
Duration: 3 Jun 20187 Jun 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11155 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th Extended Semantic Web Conference, ESWC 2018
Country/TerritoryGreece
CityHeraklion
Period3/06/187/06/18

Funding

– RVO dataset34 provides a list of R&D projects that have received subsidies and financial support from the Netherlands Enterprise Agency35. Projects information includes companies and research institutes which are collaborat-ing on the project together with the geographical coordinates of the projects. We would like to thank our colleagues from the Knowledge Representation & Reasoning research group at Vrije Universiteit Amsterdam for their helpful comments during the development of our approach for delineation of functional urban areas. This work was supported by a grant from the European Union’s 7th Framework Programme provided for the project RISIS (GA no. 313082). Aknowledgement. We would like to thank our colleagues from the Knowledge Representation & Reasoning research group at Vrije Universiteit Amsterdam for their helpful comments during the development of our approach for delineation of functional urban areas. This work was supported by a grant from the European Union’s 7th Framework Programme provided for the project RISIS (GA no. 313082).

FundersFunder number
Rijksdienst voor Ondernemend Nederland
Seventh Framework Programme
Vrije Universiteit Amsterdam
European Commission313082

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 11 - Sustainable Cities and Communities
      SDG 11 Sustainable Cities and Communities

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