=Paper=
{{Paper
|id=Vol-1280/paper2
|storemode=property
|title=A Linked Data Lifecycle for Spanish Smart Cities
|pdfUrl=https://ceur-ws.org/Vol-1280/paper2.pdf
|volume=Vol-1280
|dblpUrl=https://dblp.org/rec/conf/semweb/GuimeransVG14
}}
==A Linked Data Lifecycle for Spanish Smart Cities==
https://ceur-ws.org/Vol-1280/paper2.pdf
A Linked Data Lifecycle for Smart Cities in Spain
Almudena González, Boris Villazón-Terrazas, and José Manuel Gómez
{agonzalez, bvillazon, jmgomez}@isoco.com
iSOCO, Avda. del Partenon 10, Campo de las Naciones, Madrid, Spain
Abstract. Smart Cities combine diverse technologies to reduce their environ-
mental impact and offer citizens a higher quality of life. In this paper we present
an ongoing effort, within the context of Ciudad2020 project, for overcoming the
challenge of homogenizing the citizen’s access to services offered by heteroge-
neous, and independent entities within a Smart City scenario. We describe how
we are applying the Linked Data Lifecycle, from specification to exploitation,
within the vertical domains defined in such Spanish project.
1 Introduction
The increasing urbanization of the world, along with global problems of climate change,
water scarcity, environmental degradation, economic restructuring and social exclusion
require further consideration of the cities of the future. Moreover, we are seeing the rapid
rise in the connection and usage of billions of low-end and affordable smart devices to
the Internet.
Lately, the concept of Smart Cities has attracted considerable attention. However,
there is a lack of formal models and consensual definitions. Cities are defined smart
when their investments in the human and social capital, as well as in the communication
infrastructures are aimed at fuelling a sustainable economic growth and a high quality
of life [3].
Smart Cities combine diverse technologies to reduce the environmental impact and
improve citizens lives. This is not, however, simply a technical challenge; organisational
change in governments - and indeed society at large - is also necessary. Making a city
smart is therefore a very multidisciplinary challenge, bringing together city officials, in-
novative suppliers, national and international policymakers, academics and civil society.
Big industrial players as well as governments are focusing their research around Smart
Cities, some examples are the European Union1 and IBM2 . One particular challenge of
the Smart Cities is to find the means to manage all the big data coming from the cities.
In this paper we present an ongoing effort, within the context of a Spanish Project,
Ciudad20203 , for overcoming the challenge of homogenizing the citizen access to services
offered by heterogeneous, and independent entities within a Smart City scenario. Next,
Section 2 describes the related efforts for introducing Linked Data within Smart Cities.
Then, Section 3 introduces the Linked Data Life Cycle within the vertical domains
defined in the project. Finally, Section 4 presents some conclusions and future work.
2 Related Work
The number of Open Data portals is increasing, because of the demand of transparency
and easy access to the data. In this context, there are also plenty of works related to
1
http://eu-smartcities.eu
2
http://www.ibm.com/uk/smarterplanet
3
http://www.innprontaciudad2020.es/
Smart Cities, though not all of them are related to Linked Data. In this section we
present some of the approaches related to Smart Cities that follow the Linked Data
paradigm.
Zaragoza Public Data Catalogue4 is an Open Data Portal that shows a Smart City
as a city that allows mobility, knowledge and open access to the data. For this purpose,
it includes twenty different datasets and mobile applications. It also provides a catalogue
and a SPARQL End Point to the user.
Opendata Cáceres5 is an Open Data Portal that offers Linked Open Data datasets,
allowing to the citizens and the companies access to the municipal data, facilitating
reuse for developing applications.
United Kingdom Catalogue6 promotes Innovation as the key of and Smart City. This
portal works with UK Public Sector information and data, encouraging the use and re-
use of government datasets. It includes a directory of data avaliable, applications and a
SPARQL EndPoint.
Liviu-Gabriel Cretu [4] defines a Smart City as an event-oriented architecture, where
digital devices allow interoperability between Internet of Services, Internet of Things
and Internet of People. They explore the usability of the latest advances in SOA or
Services-oriented Architecture and Semantic Technologies.
Lopez et al. [8] describe a Smart City as a complex system with heterogeneous data
and present a Linked Data Platform for cataloguing, indexing and querying all the
information.
Tallevi-Diotallevi et al. [9] aim to capture the pulse of the city of Dublin monitoring
and decision-making with three aspects: Extending the SPARQL Language, processing
heterogeneous data (streams and static) in real time and using a hybrid RDFS reasoner.
Balduini et al. [1] present a Streaming Linked Data framework to collect data streams,
analyse and visualize the results using London Olympic Games and Milano Design Week
as use-cases. This proposal is related to event analysis in the city, uses RDF for modelling
and integrating data, SPARQL and sentiment analysis techniques for processing and
analyse social data.
Table 1 summarizes the classification by domain, data and target audience of the
Linked Data initiatives included in this survey.
The lack of Linked Data initiatives following a Multi-Domain, Multi-user and Multi-
nature Data approach along with the needs of the Spanish Citizens and Public Ad-
ministrations is what encouraged us to apply Linked Data Lifecycle within Ciudad2020
project along their vertical domains.
3 Generation and Exploitation of Linked Data within
Ciudad2020 Project
Ciudad2020 project7 is focussed on the three fundamental axes of a Smart City, which are
Energy, Transport, Environment, and City. Within this project, the Linked Data Portal8
was created for integrating the data coming from Smart Cities in the four axes, as shown
in Fig. 1. This portal has several datasets whose contents include bike sharing systems,
restaurants, museums, energy performance certificates and city tweets. For developers
and for Public Administrations, it also provides a SPARQL endpoint and the possibility
4
http://www.zaragoza.es/ciudad/risp/
5
http://opendata.caceres.es
6
http://statistics.data.gov.uk/flint-sparql
7
http://www.innprontaciudad2020.es/
8
http://ciudad2020.linkeddata.es/
Reference Domain Used Data Target Users
Zaragoza Public Mobility, Knowledge and Open Data Citizens and Devel-
Data Catalogue4 Open Access opers
Opendata Cáceres5 Culture, Transport, Linked Open Data Citizens, Companies
Environment, Society, and Developers
Healthy, Energy
United Kingdom Environment, Govern- Open Data Citizens, Developers,
Catalogue6 ment, Mapping, Society, and Administration
Health, Education,
Bussiness and Justice
Cretu, L.[4] Event-driven Architec- Semantic Citizens
ture Smart Cities Web/Linked Data
Lopez et al. [8] Urban Monitoring Static and Streaming Citizens and Admin-
Data istration
Tallevi-Diotallevi et Transport, Environment Streams and Static Citizens
al. [9] and Energy
Balduini et al. [1] City-scale Events Streaming Linked Administration
Data, Social Data
Table 1. Linked Data initiatives related to Smart Cities
of querying streaming data, showing results in real time. In the following sections we
are going to describe how we apply the Linked Data Life Cycle [7]; which consists of the
following activities (1) specification, (2) modelling, (3) generation, (4) publication, and
(5) exploitation; for each one of the Ciudad2020 vertical domains.
Fig. 1. High level overview of the Ciudad2020 Portal architecture.
3.1 Mobility and Transport
Specification. The Transport Portal9 combine Static Data Sources and Streaming Data
Sources, using Linked Data as the homogenizer element for the process of combining this
heterogeneous data:
– Static Data Sources. We use data of museums and libraries of the city of Leon and
restaurants of Saragossa. This data come from Open Data Portals and Travel Guides,
both available since February 2013:
9
http://transporte.linkeddata.es/
• Junta de castilla y León Catalogue 10 is the Open Portal of the city of León.
• Zaragoza Public Data Catalogue 11 is the Open Portal of the city of Saragossa.
• El viajero [6] is a travel guide resulting from PRISA Group Data12 .
– Dynamic Data Sources. These data compress available bikes and slots in the different
bike stations.
• Citybike API 13 is the API for Bike Sharing Systems.
Data Conversion Services. We make different types of transformation depending on
the nature of the data. In the case of Static Data Sources, we transform them by ETL
processes (Extract, Transform and Load), generating data in RDF format.
On the other hand, regarding the Streaming Data Sources, we do not use an ETL
transformation, since it would result in a hard and slow process. This Data Sources are
shown as virtual RDF sources via streaming, by using the morph-streams technology,
connecting the API REST of streaming services, web services and database producers
based on complex events (CEP), establishing R2RML mappings [5].
Exploitation Use Case - Zaragoza Bizi. The Zaragoza Bizi Use Case14 combine
static data and real time in the context of two cities: Saragossa and Leon. For instance,
in Saragossa city there are 1300 bikes and more than 100 Km of cycle paths, serving
citizens and tourists. This sums a total of 4,5 millions of uses and 13 millions of kilometres
travelled in the last two years. At the same time, it avoided 2000 Tons of CO2 emissions.
Within this use case, citizens and tourists can check the number of available bikes
as well as the number of free slots. They can also check in the map the location of
the stations (the exact latitude and longitude are provided), nearby points of interest
(including restaurants and museums) by choosing a determinate distance, routes between
different stations, sharing the resource via Twitter, and send a suggestion for updating
a resource. Finally, for developers, they can also access the traditional RDF information
associated to a resource or consult de SPARQL endpoint15 .
3.2 Environmental Control
Specification We collect weather data streams from the weather API of OpenWeath-
ermap16 . It provides data from more than 40,000 weather stations. All weather data are
obtained in JSON format.
Data Conversion Services In this case, the transformation process of the Streaming
Data is the same we previously described in the Mobility and Transport section, we use
the morph-streams technology [2] .
Exploitation Use Case - Weathermap Meteo The Weathermap Meteo Use Case17
shows the current weather and it is available for 200,000 cities.
This Use-Case provides a streaming querying service. The users can get the current
weather data for any location on the Earth in real time by consulting the SPARQLStream
endpoint.
10
http://www.datosabiertos.jcyl.es/
11
http://www.zaragoza.es/ciudad/risp/
12
http://www.prisa.com/es/
13
http://api.citybik.es/
14
http://transporte.linkeddata.es/browser.html
15
http://transporte.linkeddata.es/sparql.html
16
http://openweathermap.org/API
17
http://streams.linkeddata.es/register/weathermap
3.3 Energy and Efficiency
Specification. The Energy Portal18 combines Static Data Sources from different cities
using Linked Data:
– La Rioja city Energy Efficiency Certificates19 : They provide an API to consult de
database of certificates of buildings and projects located in the city, providing the
rating, the consum, the emission and the address of the buildings.
– Navarra city Energy Efficiency Certificates20 : They provide a web search service to
obtain the Energy information associated to new projects, new buildings and existing
buildings. Filters by ranking and type of building are available.
Data Conversion Services. In this particular case, we transform the Static Sources
by ETL processes (Extract, Transform and Load), generating data in RDF format.
Exploitation Use Case - Navarra Energy Efficiency Certificates
In this use case21 we show the statistics of the different Spanish provinces, which publish
these certificates in Open Data portals.
We display a comparison of the provinces of La Rioja and Navarra, thereby the
citizens can consult the energy performance certificates and check the number of available
certificates with each rank, from A to G, where A means the most efficient buildings,
and G means the least efficient buildings.
For instance, if the citizen choose the province of Navarra in the “Province” pull-
down menu, the statistics of this city are shown. We can check that the most repeated
rankings are D and E, with 1075 and 2368 buildings respectively.
3.4 City Data
Specification. The City Portal22 combine Static Data Sources and Streaming Data
Sources, disambiguating and publishing those sources under the Linked Data paradigm.
Streaming Data Sources. Twitter API23 . We collect the tweets geolocated in the city
of Saragossa and published during the first trimester of 2014.
Data Conversion Services We extract the named entities from Saragossa tweets.
Once we get these named entities, we disambiguate them using the NERD tool 24 . We
associate a Dbpedia25 resource to each entity. We use the domain and semantic data
ontology for disambiguating purposes. Finally, we generate RDF, we publish it and for
the exploitation we use Flot Charts 26 to display the graphics associated to the statistics.
Regarding the publication activity, note that we cannot publish the tweet text, since the
API Terms of Twitter specify that we may only return tweet IDs and user IDs.
18
http://energia.linkeddata.es/
19
http://www.larioja.org/npRioja/default/defaultpage.jsp?idtab=772883
20
https://administracionelectronica.navarra.es/webCertificacionesEnergeticas/
BuscarCertificado.aspx
21
http://energia.linkeddata.es/browser.html
22
http://ciudad.linkeddata.es/
23
http://www.twitter.com/
24
http://nerd.eurecom.fr/analysis
25
http://www.dbpedia.org/
26
http://www.flotcharts.org/
Exploitation Use Case - Zaragoza Tweets This use case27 aims to show to the
citizens a graphical visualization of statistics for the named entities in tweets geolocated
in the city of Saragossa, during the first quarter of 2014, disambiguated and published
in Linked Data. In this period, we observe that some of the most repeated entities
named in the city are Bands, Zaragoza city, Spain, Physical exercise, etc. Each of these
entities has an associated DBPedia resource. DBpedia defines an unique global identifier,
including natural languages definitions and relations to another resources. For instance,
the Zaragoza entity has the associated resource http://dbpedia.org/resource/Zaragoza.
4 Conclusion and Lessons Learned
In this paper we have presented (1) a small survey on research efforts related to applying
Linked Data to Smart Cities, and (2) an ongoing work of applying Linked Data Lifecycle,
i.e., generating, publishing and consuming Linked Data, within the vertical domains of
the Ciudad2020 Spanish project.
The implementation of the use cases using RDF and Linked Data Principles has
many benefits: (1) data interoperability (URI-based data integration), (2) flexibility
(not fixed schema and no need to adapt SPARQL queries to a new schema, facilitating
the incorporation of new datasets), (3 ) web-compatibility and (4) web-scalability (RDF
unique identifiers). In contrast, the costs: dependence on the availability of data sources
and license of data.
Regarding the future work we plan to (1) implement a Linked Data Platform within
the project, following the W3C LDP Working Group28 recommendations, (2) include
and integrate new application domains, and (3) develop on top of the LDP a set of added
value services, such as, recommender systems and analytics.
Acknowledgments This work is partially supported by the Ciudad2020 INNPRONTA
project (IPT-20111006). We would like to thank Ontology Engineering Group-UPM.
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http://ciudad.linkeddata.es/browser.html
28
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