=Paper=
{{Paper
|id=Vol-1329/papersmile_2
|storemode=property
|title=Towards emergency vehicle routing using Geolinked Open Data: the case study of the Municipality of Catania
|pdfUrl=https://ceur-ws.org/Vol-1329/papersmile_2.pdf
|volume=Vol-1329
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==Towards emergency vehicle routing using Geolinked Open Data: the case study of the Municipality of Catania==
https://ceur-ws.org/Vol-1329/papersmile_2.pdf
Towards emergency vehicle routing using
Geolinked Open Data: the case study of the
Municipality of Catania∗†
Sergio Consoli1,2 , Aldo Gangemi1,3 , Andrea Giovanni Nuzzolese1,2 , Silvio
Peroni1,2 , Valentina Presutti1 , Diego Reforgiato Recupero1 , and Daria
Spampinato1
1
National Research Council (CNR), Institute of Cognitive Sciences and Technologies,
Semantic Technology Laboratory, ITALY {firstname.lastname}@istc.cnr.it
2
Department of Computer Science, University of Bologna, ITALY
{nuzzoles,speroni}@cs.unibo.it
3
LIPN, University Paris 13, Sorbone Cité, UMR CNRS, FRANCE
aldo.gangemi@lipn.univ-paris13.fr
Abstract. Linked Open Data (LOD) has gained significant momentum
over the past years as a best practice of promoting the sharing and publi-
cation of structured data on the semantic Web. Currently LOD is reach-
ing significant adoption also in Public Administrations (PAs), where it is
often required to be connected to existing platforms, such as GIS-based
data management systems. Bearing on previous experience with the pi-
oneering data.cnr.it, through Semantic Scout, as well as the Agency for
Digital Italy recommendations for LOD in Italian PA, we are working on
the extraction, publication, and exploitation of data from the Geographic
Information System of the Municipality of Catania, referred to as SIT
(“Sistema Informativo Territoriale”). The goal is to boost the metropolis
towards the route of a modern Smart City by providing prototype inte-
grated solutions supporting transport, public health, urban decor, and
social services, to improve urban life. In particular a mobile application
focused on real-time road traffic and public transport management is
currently under development to support sustainable mobility and, espe-
cially, to aid the response to urban emergencies, from small accidents
to more serious disasters. This paper describes the results and lessons
learnt from the first work campaign, aiming at analyzing, reengineering,
linking, and formalizing the Shape-based geo-data from the SIT.
Keywords: Geo-Linked Open Data applications; Linked eGovernment Data
extraction and publication; sustainable mobility; emergency vehicle routing.
∗
This work has been supported by the PON R&C project PRISMA, “PiattafoRme
cloud Interoperabili per SMArt-government”, ref. PON04a2 A Smart Cities, under the
National Operational Programme for Research and Competitiveness 2007-2013.
†
Authors are listed in alphabetical order as their contributions are equally
distributed.
32 Consoli et al.
1 Preliminary discussion
In a currently on-going project we are investigating the extraction, enrichment,
publication and reuse of Linked Open Data (LOD) [1, 2] for the Municipality of
Catania (MoC), Italy, by means of the application of latest semantic technolo-
gies and software components [3]. The main motivation of the work consists of
experimenting social eGovernment systems aimed at optimizing the performance
of the Public Administration (PA) of the MoC for the provision of intelligent
ICT services to citizens and businesses, supporting the external evaluation of the
PA by the detection of the community trust. The work falls within the spirit of
the Smart Cities initiatives of the European Commission, which aims at bringing
together cities, industry and citizens to improve urban life through more sustain-
able integrated solutions. Although the methodology has been designed for the
case study of the city hall of Catania, the approach is completely generalizable
and can be replicated to any PA worldwide. One of the main development objec-
tives of the project consists in conceiving, designing and prototyping applications
for the MoC related to certain areas of experimentation, such as online social
services and health, traffic management and transport, and urban decor. With
the aim of detecting and collecting the required data and processes for these
applications, meetings with the Leadership of the Directorate of Information
Systems Service of the MoC were carried out.
A particular field of experimentation is specially focused on the manage-
ment of mobility, i.e. road traffic and public transport. Within this context, the
scenario has identified the development of a prototype mobile application im-
plementing a real-time system to inform on the state of roads in urban areas
to support sustainable mobility and, in particular, to aid the response to urban
emergencies, from small scale accidents to more serious disasters. The system
aims at connecting drivers to one another, helping people create local driving
communities that work together to improve the quality of everyone’s daily driv-
ing. That might mean helping them avoid the frustration of sitting in traffic,
advising them on unexpected accidents or other traps, or just shaving five min-
utes off of their regular commute by showing them new routes they never even
knew about. But most importantly, the application may have any extremely im-
portant role on emergency logistics. Response to an emergency incident requires
careful planning and professional execution of plans, when and if an emergency
occurs [4]. During these events there is the need to find rapidly the nearest hos-
pitals, or to obtain the best way outs from the emergency zones, or to produce
the optimal path connecting two suburbs for redirecting the road traffic, etc.
Technically, this system should be able to locate the best path between source
and destination not only in a static environment, but particularly in a dynamic
one. That is, the user feedback serves at placing in the map some obstacles, or
inaccessible zones, coming from accidents or emergency events, and the system
responds in real-time producing the optimal path without these forbidden zones.
After typing in their destination address, users just drive with the application
open on their phone to passively contribute traffic and other road data, but they
can also take a more active role by sharing road reports on accidents, advising on
Emergency routing using Geolinked Open Data for MoC 33
unexpected traps, or any other hazards along the way, helping to give other users
in the area real-time information about what’s to come [5]. For the realization
of the app for our case study, it is necessary to process the data and diagrams in
the Geographic Information System of the MoC, referred to as SIT: “Sistema In-
formativo Territoriale” [6]. Therefore it was decided, by mutual agreement with
the chief officers and experts of the city hall of Catania, to process the data in
order to make them open, interoperable and compatible with the principles of
Linked Open Data.
The paper is structured as follows. Background on the state of the art on
the use of LOD for PA, often referred to as Linked eGovernment Data [7], is
reported in Section 2. Techniques and tools used to deal with LOD for the
MoC are introduced in Section 3, while the extracted ontology is described in
Section 3.3, along with the means used to consume the accessible data. Section 4
ends the paper with conclusions and the future research where we are directed.
2 Linked eGovernment Data
LOD are currently bootstrapping the Web of Data by converting into RDF
and publishing existing datasets available to the general public under open li-
censes [1, 2]. LOD offers the possibility of using data across domains or organi-
sations for purposes like statistics, analysis, maps and publications. These major
changes in technology and society are involving also the way of doing politics,
administration and the relationship between politicians, public servants and cit-
izens. Transparency, participation and collaboration are the main issues of the
integration of citizens in the paradigm of Open Government [8]. Because PAs
have large amounts of data which could be made accessible for the purpose of the
LOD movement, research on the opening process, data reengineering, linking,
formalisation and consumption is of primary interest [9].
The Digital Administration Code incorporates a wide range of best-practices
in the usage of Linked eGovernment Data, which can be synthetized as: por-
tals for the supply of the Linked eGovernment Data sets; portals providing raw
data sets of LOD for PAs along with technical tools or developer kits for under-
standing, interpreting, or processing the provided data; existing portals acting
as showrooms for best practices for Linked eGovernment Data; mobile apps for
smartphones using LOD for PAs [7].
The main thrust on the publication of LOD for PA is coming from big
initiatives in the United States (data.gov) [10, 11] and the United Kingdom
(data.gov.uk) [12], both providing thousands of raw sets of LOD within their
portals, but there are also some other experiences and notable initiatives that
are in line with the international state of the art. In Germany, one of the first
examples for a LOD portal is the one from the state of Baden-Württemberg
(opendata.service-bw.de), divided into three main parts: LOD, applications,
and tools. In addition to their potentials, Linked eGovernment Data can pro-
vide great benefits in the matter of accountability, as shown in the LOD portal
example of Kenya (opendata.go.ke).
34 Consoli et al.
In addition, LOD have been published in Italy by the city hall of Florence4 ,
Agency for Digital Italy5 , from the Piedmont region6, the Chamber of Deputies7 .
Beside these initiatives, another notable for the Italian PA is “data.cnr.it” [13,
14], the open data project of the National Research Council (CNR), designed and
maintained by the Semantic Technology Laboratory of ISTC-CNR, and shared
with the unit Information Systems Office of CNR.
3 Extraction of Linked eGovernment Data for the MoC
In this section we present the methodology used for the extraction and pub-
lication of LOD for the Municipality of Catania. The methods are based on
the standards of the W3C8 , on good international practices, on the guidelines
issued by the Agency for Digital Italy [15, 16] and those by the Italian In-
dex of Public Administration9 , as well as on the in-depth experience of the
research participants on this field, in particular related to the development of
the “data.cnr.it” [13, 14] portal.
3.1 Scenario analysis
During the phase of selection of the source data, a thorough analysis of the ref-
erence domain was made. Thanks to the close interaction with the PA experts
of the MoC, the Geographic Information System, SIT [6], was identified as the
source dataset for the enrichment and publication of data. The SIT is a data
warehouse used for reporting and data analysis, and consisting of databases,
hardware, software, and technicians, which manages, develops and integrates in-
formation of the province of Catania based on a geographical space [6]. The vari-
ous territorial levels (hydrography, topography, buildings, infrastructure, techno-
logical networks, administrative boundaries and land, ...) form the geo-localised
common part of the information flow of the MoC, according to which all the
constituent parts are related to each other.
The SIT is designed to contain all the available data of the PA in Catania
for the purpose of in-depth knowledge of the local area. Basically tit contains
three types of data: register base, registry office, and toponymy, provided in the
form of Shape-based files [17] for each data record, i.e. files with extensions: .dbf,
.shp, .shx, .sbn, .sbx, .xml. Through the consultation platform on the web it is
possible to display the following information: basic cartography; ortho-photos;
road graph; buildings with a breakdown by main body of some areas of the
city; cadastral sections; data from the 1991 and 2001 census of the population;
last Master Plan; gas network on-going works; resident population in selected
4
Available at: http://opendata.comune.fi.it/linked_data.html
5
Available at: http://www.digitpa.gov.it
6
Available at: http://www.dati.piemonte.it/rdf.html
7
Available at: http://dati.camera.it
8
Available at: http://www.w3.org/standards/semanticweb/
9
Available at: http://spcdata.digitpa.gov.it/data.html
Emergency routing using Geolinked Open Data for MoC 35
areas (municipalities, entire street, polygonal, circular area); total population,
distributed into bow street, house number, etc; breakdown of the population by
municipality, blocks, nationality, gender, family components, age, marital sta-
tus, etc; extraction and search of resident persons, and their location on the bow
streets; competence areas of pharmacies; location and alphanumeric information
of: municipality, hospitals, universities, schools, pharmacies, post offices, areas or
emergency, public safety, fire departments, public green areas, public community
centres, institutions for minors and orphanages. The SIT also includes maps con-
taining geo-referenced information related to: sub-services (electricity-gas-water
pipes); data on stoppage areas; occupation stalls; stalls for disadvantaged peo-
ple; occupation of public land; public transport fleet; management and working
state of the fleet; data on lines and stops of public transport; accident traffic
data; road signs and markings; maintenance state of roads and sidewalks; man-
agement of roadway construction; data of the municipal police; the accounting
of the Municipality. Note that the information contained in the SIT are in Ital-
ian language, therefore the produced Linked Open Data will be in Italian too
(although the whole generation process is completely language-independent).
3.2 Geo-data modelling and reengineering
To reengineer the dataset according to the target conceptual model we used
Tabels10 , a software tool developed by the research foundation CTIC, which, us-
ing the GeoTools libraries11 , is capable of transforming the information encoded
in the shape files into RDF representations. From the shape files supplied for
each data record (in particular, the files with extensions .dbf and .shp), Tabels
encoded the shape files into RDF triples related to the designed ontology, that
it will be described in more detail in Section 3.3. On the one hand the character-
istics of the table are stored as RDF representation, and, on the other hand, the
spatial geometry is modelled on the standard KML representation [18]. At this
Fig. 1: Example of a geo-localised entity of “pharmacies”.
10
Available at: http://idi.fundacionctic.org/tabels/
11
Available at: http://geotools.org
36 Consoli et al.
stage we are mapping to existing vocabularies, in particular NeoGeo12 , suitable
for geo-data. The geometric coordinates in KML are expressed according to the
Geodetic reference system Gauss-Boaga (or Rome 40). By means of different
conversion tools publicly available on-line (e.g. http://www.ultrasoft3d.net/
Conversione_Coordinate.aspx), it is possible to produce the coordinates of lat-
itude, longitude and altitude in meters using the Geodetic system WGS84 [19].
In particular, the application of Tabels to each pair of files, .dbf and .shp, of the
data tables is able to produce a set of RDF triples stored in a repository with
other geometric resources contained in a public server. For example, from the
information stored in the database of the SIT representing an entity of “phar-
macies” (Figure 1), Tabels produces the related RDF triples, shown in Figure 2,
and the file with the geometric KML coordinates (Figure 3).
Fig. 2: RDF triples produced by Tabels for the example of entity in “pharmacies”.
Fig. 3: KML coordinates produced by Tabels for the example of entity in “phar-
macies”.
12
Available at: http://geovocab.org/doc/neogeo.html
Emergency routing using Geolinked Open Data for MoC 37
Tabels is able to import common file formats, such as XLS or CSV, including
shape files. Afterwards it generates automatically a transformation program from
the input data files. The generated program is able to transform each row of
the input data into a new instance of a RDF class ad-hoc. In addition, each
value in the column of the input tables is converted into a new triple where
the subject is the instance mentioned, the predicate is a property based on the
name of the column header, and the object is the value of the column as a
rdfs:Literal. It is worth noting that the transformation program automatically
generated, is a SPARQL-based script completely customisable by the user. Thus
it is possible to change classes, names and associated properties, and then to
annotate them appropriately. Once the transformation program is defined, the
execution of Tabels generates the corresponding RDF in output, which we make
publicly available online through a dedicated SPARQL endpoint. In addition,
information regarding each resource object of the ontology data can be obtained
through negotiation mechanisms of the content (content negotiation) based on
HTTP REST that make them accessible, for example, through a browser or as
REST web service. Data consumption is described in more detail in Section 3.5.
3.3 Resulting ontology for the SIT
Starting from the definition of the tables of the SIT, a first version of OWL
ontology was developed. This provides classes and properties representing the
database entities of the SIT, and is publicly available at the following URI:
http://ontologydesignpatterns.org/ont/prisma/ontology.owl
having the namespace (i.e. the default address of the entities in the ontology):
http://www.ontologydesignpatterns.org/ont/prisma/.
The creation process of this ontology was divided into two main phases and
has followed the good practice of formal representation, naming, and seman-
tic assumptions in use in the domain of the Semantic Web and Linked Open
Data [15, 16]. In the first phase, the entire structure of the tables was con-
verted into a draft OWL ontology, where each table (i.e. each entity type de-
scribed by the supplied data) is represented by a class and each field of the
table by a data property. This translation was carried out in a fully automatic
way from the sources provided in XML format (extension .shp.xml ) by means
of the use of an XSLT transformation. Note that fields with the same name
but belonging to different tables have been provided with distinct properties.
For example, the fields “Name” of the tables “Nursing Homes” (“Case Riposo”)
and “Pharmacies” (“Farmacie”) have been translated with two different data
properties, respectively “Name-of-CATANIA.SDO NursingHomes” and “Name-
of-CATANIA.SDO Pharmacies”.
From this interim draft ontology and from the available data, a first version
of the ontology in OWL was produced. At this stage we have followed the sug-
gestions of the W3C Organization Ontology13 , a set of guidelines for generating,
13
Available at: http://www.w3.org/TR/2014/REC-vocab-org-20140116/
38 Consoli et al.
publishing and consuming LOD for organizational structures. In this respect we
have named the graph nodes as URIs and pursued the following principles:
– The name of all the classes was taken to the singular (e.g., from “Pharmacies”
to “Pharmacy”);
– The names of the data properties were aligned when they were clearly show-
ing the same semantics. For example, the properties
“Name-of-CATANIA.SDO NursingHomes” and
“Name-of-CATANIA.SDO Pharmacies” ended in the same property “name”,
assigned to “NursingHome” and “Pharmacy” as domain or entity class;
– The data properties that seemed to refer to individuals of other classes,
probably having foreign key functions on the data base, were transformed
into object properties. For example, the property
“MUNI-of-CATANIA.SDO NursingHomes” became “municipality” in order
to connect individuals of class “Nursing Home’ with individuals of class
“Municipality”;
– The data properties having values clearly assigned to some resources were
transformed into object properties and their values were reified as individuals
of specially created classes.
All changes made to the intermediate draft ontology for the implementation
of the first version of the ontology have been documented in the form of SPARQL
CONSTRUCT. This allowed us to create a simple script to convert the data
extracted by Tabels in order to make them fully compliant with the final expected
ontology, produced as output in RDF format.
3.4 Example of conversion from the geo-data to the final ontology
In this section we want to focus on the phase of transformation from shape files
to the final RDF ontology by reporting an example. Consider as reference the
data record “Traffic Lights” (“Semafori”). The SQL schema of this table includes
the fields:
– ObjectID - unique number incremented sequentially;
– Shape - type Geometry that represents the coordinates defining the geometric
characteristics of the entity;
– Id - Identification number of type Double;
– name - String type name of the entity;
– Sde SDE se - integer number;
– Se ANNO CAD DATA - blob representing the date.
Passing the .shp and .dbf files to Tabels, this generates the transformation
program, that is the SPARQL-based script used to import the data (see Fig-
ure 4). As already mentioned, it is possible to edit the script to suit custom
requirements. Once any change in the transformation program is completed, it
is possible to save and run it, which generates the RDF triples from the table
data given as input. Figure 5(a) shows the RDF/Turtle produced by Tabels by
Emergency routing using Geolinked Open Data for MoC 39
using the methodology already described for a single ‘Traffic Light” entity as ex-
ample. Figure 5(b) shows the corresponding final ontology of this entity obtained
Fig. 4: A view on the transformation program used by Tabels to convert the shape
files to RDF for the table “Traffic Lights” (“Semafori”).
(a)
(b)
Fig. 5: Top panel (a): RDF/Turtle produced by the transformation program of
Tabels for a single entity of the table “Traffic Lights” (“Semafori”). Bottom panel
(b): Corresponding final RDF/Turtle ontology obtained through SPARQL CON-
STRUCT conversion to fully match the designed ontology.
4
10 Consoli et al.
by conversion through SPARQL CONSTRUCT of the related data extracted by
Tabels, in order to fully match the designed ontology.
This example further shows the ability and simplicity of the proposed method-
ology to gather the complex structure of a non-structured database, allowing a
rapid analysis, retrieval, and conversion of the data into a structured RDF for-
mat, and the publication in the form of Linked Open Data.
3.5 Data consumption
The produced ontology consists of 854,221 triples and can be publicly queried by
selecting the RDF graph called on the dedicated SPARQL endpoint
accessible at http://wit.istc.cnr.it:8894/sparql. Queries can be made by
editing the text area available into the interface for the SPARQL query. The
SPARQL endpoint is also accessible as a REST web service, whose synopsis is:
– URL ⇒ http://wit.istc.cnr.it:8894/sparql
– Method ⇒ GET
– Parameters ⇒ query (mandatory)
– MIME type supported output ⇒ text/html ; text/rdf+n3 ; application/xml ;
application/json; application/rdf+xml.
Data are also accessible through content negotiation. The reference names-
pace for the ontology is http://www.ontologydesignpatterns.org/ont/prisma/
which is identified by the prefix prisma-ont. The namespace associated with
the data is, instead http://www.ontologydesignpatterns.org/data/prisma/
which is identified by the prefix prisma. These two namespaces allow content ne-
gotiation related to the ontology and the associated data. The negotiation can
be done either via a web browser (in this case the MIME type of the output is
always text/html ), or by making HTTP REST requests to one of the two names-
paces. The synopsis of the REST requests to the web service associated with the
namespace identified by the prefix prisma-ont is the following:
– URL ⇒ http://www.ontologydesignpatterns.org/ont/prisma/
– Method ⇒ GET
– Parameters ⇒ ID of the ontology object (mandatory the PATH parameter)
– MIME type supported output ⇒text/html ; text/rdf+n3 ; text/turtle; text/owl-
functional ; text/owl-manchester ; application/owl+xml ; application/rdf+xml ;
application /rdf+json.
Instead, the synopsis of the REST requests to the web service associated with
the namespace identified by the prefix prisma is the following:
– URL ⇒ http://www.ontologydesignpatterns.org/data/prisma/
– Method ⇒ GET
– Parameters ⇒ ID of the ontology object (mandatory the PATH parameter)
– MIME type supported output ⇒text/html ; text/rdf+n3 ; text/turtle; text/owl-
functional ; text/owl-manchester ; application/owl+xml ; application/rdf+xml ;
application /rdf+json.
Emergency routing using Geolinked Open Data for MoC 4
11
4 Conclusion
This paper presents an application of Linked Open Data for PA. The used
methodology was implemented by following the standards of the W3C, the good
international practices, the guidelines issued by the Agency for Digital Italy and
the Italian Index of Public Administration, as well as by the in-depth experi-
ence of the research participants in the field. The method was applied to the
case study of the PA of the MoC, in particular from their data stored in the
Geographic Information System, SIT. By using tools and technologies for the
extraction and publication of data, it was possible to produce an ontology of
the SIT according to the paradigm of Linked Open Data. The data are pub-
licly accessible to users through queries to a dedicated SPARQL endpoint, or
alternatively through calls to dedicate REST web services.
In currently on-going work a mobile application based on this LOD and
related to sustainable mobility and emergency vehicle routing is under develop-
ment and will be released soon. This will support the real-time management of
road traffic and public transport, informing citizens on the state of roads in ur-
ban areas, in particular during urban emergencies, from small accidents to more
serious disasters, and redirecting the road traffic by providing best alternatives
routes to find way outs, the nearest hospitals or other locations of interest. The
user will be able to contribute traffic and other road data, sharing road reports
on accidents, advising on unexpected obstacles or inaccessible zones, or any other
hazards along the way, helping to give other users in the area real-time infor-
mation about what is currently happening. Soon, when the mobile app based
on these LOD will be launched, user-centric tests and an experimental evalua-
tion will be object of investigation. Our work is a concrete step supporting the
Municipality of Catania to move into the paradigm of Open Government and
Linked Data, boosting the metropolis towards the route of a modern Smart City.
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