A Platform for Urban Analytics and Semantic Data Integration in City Planning

Psyllidis, Achilleas; Bozzon, Alessandro; Bocconi, Stefano; Bolivar, C. Titos

doi:10.1007/978-3-662-47386-3_2

Cited by 57 publications

(38 citation statements)

References 14 publications

(13 reference statements)

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“…Having said that, there exist other studies working on this paradigm. The authors in [26] present a novel web-based platform to that end, which includes data from heterogeneous sources via semantic integration. However, it is focused on public data and social media, which still is not the single objective of a Smart City, and is missing data from private companies (e.g., energy generation plants).…”

Section: Scientific Backgroundmentioning

confidence: 99%

Interoperable Open Specifications Framework for the Implementation of Standardized Urban Platforms

Hernández¹,

García²,

Schonowski³

et al. 2020

Sensors

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The current cities' urban challenges go through digitalization and integration of new technologies under the perspective of actual and future ecological, as well as socio-economic commitments. This process is translated into the Open Standardized Urban Data Platform, which plays a pivotal role. Within its main functionalities, data ingestion, analytics and services as vertical domains become necessary to create more environmentally friendly cities. However, there still exist some deficits. Among them, openness and interoperability are outlined. On the one hand, there is a lack of open data initiatives for increasing the smart services stock. On the other hand, interoperability depends upon vendors and integrators, reducing the possibilities of Smart City growth. In this context, under the mySMARTLife project (GA #731297) umbrella, an Open Specifications Framework has been developed in order to address four main issues: (1) data interoperability; (2) services or verticals interoperability; (3) openness; and (4) replicability. It enlightens the implementation and integration of multiple city domains (like infrastructures, mobility, energy, buildings) for smart management and big-data analytics. Its applicability is demonstrated in the three lighthouse cities of the project, Nantes (France), Hamburg (Germany) and Helsinki (Finland).

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Section: Scientific Backgroundmentioning

confidence: 99%

Interoperable Open Specifications Framework for the Implementation of Standardized Urban Platforms

Hernández¹,

García²,

Schonowski³

et al. 2020

Sensors

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“…In the area is Smart Cities there are initiatives that create Linked Data based collection of citizen complaints [12] or collect and integrate urban data to sup-port city planning [36]. Mobile crowdsourcing is the basis of several papers which deal with geo-data, for example, the verification and extension of geo data collections such as the OpenStreetMap dataset [21] or enabling collaborative ontology construction in crowdsourced cartographic projects [3].…”

Section: Combining Semantic Web and Humanmentioning

confidence: 99%

Semantic Web and Human Computation: The status of an emerging field

Sabou

Aroyo

Bontcheva

et al. 2018

Self Cite

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This editorial paper introduces a special issue that solicited papers at the intersection of Semantic Web and Human Computation research. Research in that inter-disciplinary space dates back a decade, and has been acknowledged as a research line of its own by a seminal research manifesto published in 2015. But where do we stand in 2018? How did this research line evolve during the last decade? How do the papers in this special issue align with the main lines of work of the community? In this editorial we inspect and reflect on the evolution of research at the intersection of Semantic Web and Human Computation. We use a methodology based on Systematic Mapping Studies to collect quantitative bibliographic data which we analyze through the lens of research topics envisioned by the research manifesto to characterize the evolution of research in this area, thus providing a context for introducing the papers of this special issue. We found evidences of a thriving research field; while steadily maturing, the field offers a number of open research opportunities for work where Semantic Web best practices and techniques are applied to support and improve the state-of-the-art in Human Computation, but also for work that exploits the strength of both areas to address scientifically and societally relevant issues.

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“…To better characterize a specific energy consumption type, Social Smart Meter computes the frequency of occurrence of relevant terms, aggregated by area and time. Moreover, for the mobility energy consumption type, it calculates the user displacement and radius of gyration as implemented in [6]. Social Smart Meter provides views to explore the extracted information.…”

Section: Analysis and Visualizationmentioning

confidence: 99%

“…In recent years, the proliferation of social data has given rise to a new source of information about peoples' daily spatiotemporal behavior [2,4,6]. While other sources, such as mobile phones, satellite imagery, and traffic sensors are increasingly used in deriving information about energy consumption behavior, in this work we focus on user-generated content from social media.…”

Section: Introductionmentioning

confidence: 99%

Social Smart Meter

Mauri

Psyllidis

Bozzon

2018

Companion of the the Web Conference 2018 on the Web Conference 2018 - WWW '18

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Having a thorough understanding of energy consumption behavior is an important element of sustainability studies. Traditional sources of information about energy consumption, such as smart meter devices and surveys, can be costly to deploy, may lack contextual information or have infrequent updates. In this paper, we examine the possibility of extracting energy consumption-related information from user-generated content. More specifically, we develop a pipeline that helps identify energy-related content in Twitter posts and classify it into four categories (dwelling, food, leisure, and mobility), according to the type of activity performed. We further demonstrate a web-based application-called Social Smart Meter-that implements the proposed pipeline and enables different stakeholders to gain an insight into daily energy consumption behavior, as well as showcase it in case studies involving several world cities. CCS CONCEPTS • Information systems → Web searching and information discovery; • Human-centered computing → Social media;

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A Platform for Urban Analytics and Semantic Data Integration in City Planning

Cited by 57 publications

References 14 publications

Interoperable Open Specifications Framework for the Implementation of Standardized Urban Platforms

Interoperable Open Specifications Framework for the Implementation of Standardized Urban Platforms

Semantic Web and Human Computation: The status of an emerging field

Social Smart Meter

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