From Open Urban Data to Locative Services: Eligibility Criteria and a Faceted Typology for Urban Digital Locative Elements

Open urban data portals are increasingly proposed as infrastructures for citizen-facing locative services, yet there are no explicit criteria for deciding which georeferenced entities qualify as urban digital locative elements, nor a principled basis for organising them. This hinders semantic interoperability, discovery, and reuse. This article pursues three objectives: to define eligibility criteria distinguishing such elements from other georeferenced data; to derive a faceted, multi-label typology organising them for discovery and reuse; and to assess operational feasibility in a real setting. Following a design-science approach, the artefact, five eligibility criteria and a nine-category typology, was derived by synthesising three evidence sources: a structured literature review, a comparative analysis of six CKAN-based portals in Portugal and Brazil, and an exploratory pilot in Fortaleza, with explicit mappings to FIWARE, schema.org/Place, OpenStreetMap, and CityGML/INSPIRE. The framework was then exercised on the portal corpus and in a working platform, complemented by a small in-situ user study (n = 17). The criteria filtered locative elements effectively, all categories were populated by real datasets, and category-based discovery was understandable in situ, though these findings are preliminary. Open government data thus emerges as an active layer for operationalising locative services, with broader validation left to future work.

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Publication Details

Journal
Smart Cities
Published
2026-08-21
DOI
https://doi.org/10.3390/smartcities9080135
Primary Topic
Geographic Information Systems Studies
Type
article
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article

From Open Urban Data to Locative Services: Eligibility Criteria and a Faceted Typology for Urban Digital Locative Elements

Rui José, Pedro Henrique Nunes, José Eurico de Vasconcelos Filho, Maurício Bezerra et al.
Smart Cities
Geographic Information Systems Studies
article

From Open Urban Data to Locative Services: Eligibility Criteria and a Faceted Typology for Urban Digital Locative Elements

Rui José, Pedro Henrique Nunes, José Eurico de Vasconcelos Filho, Maurício Bezerra, Carlos Carvalho
article en

Abstract

Open urban data portals are increasingly proposed as infrastructures for citizen-facing locative services, yet there are no explicit criteria for deciding which georeferenced entities qualify as urban digital locative elements, nor a principled basis for organising them. This hinders semantic interoperability, discovery, and reuse. This article pursues three objectives: to define eligibility criteria distinguishing such elements from other georeferenced data; to derive a faceted, multi-label typology organising them for discovery and reuse; and to assess operational feasibility in a real setting. Following a design-science approach, the artefact, five eligibility criteria and a nine-category typology, was derived by synthesising three evidence sources: a structured literature review, a comparative analysis of six CKAN-based portals in Portugal and Brazil, and an exploratory pilot in Fortaleza, with explicit mappings to FIWARE, schema.org/Place, OpenStreetMap, and CityGML/INSPIRE. The framework was then exercised on the portal corpus and in a working platform, complemented by a small in-situ user study (n = 17). The criteria filtered locative elements effectively, all categories were populated by real datasets, and category-based discovery was understandable in situ, though these findings are preliminary. Open government data thus emerges as an active layer for operationalising locative services, with broader validation left to future work.

Smart CitiesVol. 9(8)
Prefeitura Municipal de Tauá (BR), University of Minho (PT)
Sustainable cities and communities
Openalex Percentile: Top 3%
Geographic Information Systems Studies
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From Open Urban Data to Locative Services: Eligibility Criteria and a Faceted Typology for Urban Digital Locative Elements — Rui José, Pedro Henrique Nunes, et al. · Smart Cities (2026) | TGRS Research Map | TGRS