Architectural Heritage Ontology

Concepts and Some Practical Issues

Francesca Noardo

Politecnico di Torino, DIATI, c.so Duca degli Abruzzi, 24, 10129 Torino, Italy

Keywords: Semantics, Standard, Ontologies, 3D Model, CityGML, Interoperability, ADE, Architectural Heritage.

Abstract: Interoperability has become fundamental to the management and sharing of the data. For this reason,

international standards are published and ontologies are proposed and used for structuring databases in order

to assure information retrieval, improved analysis and correct interpretation of the data, besides the

interoperability of compliant databases. For thematic data about cultural heritage, standards vocabularies and

ontologies EXIST, but are not fully suitable to represent some aspects of architectural heritage. In fact,

complex spatial data have to be equally managed using these technologies, for enabling analysis empowered

by the inclusion of the spatial and geographical dimension. This could undoubtedly enrich the documentation

of architectural heritage. However, few spatial ontologies exist, which are able to correctly represent the

complexity and richness of such data. In the paper, an existing ontological model for cartographic urban

themes, OGC CityGML, is extended, in order to propose a data schema for the management of architectural

heritage multi-scale, multi-temporal and articulated data. The extended parts of the model are explained in

the paper. Moreover, some implementation aspects are considered both for the definition of the ontological

schema extension and for the management of the data using it.

1 INTRODUCTION

The management of spatial and geographic

knowledge is becoming more and more discussed,

since informatics technologies permit new advanced

analysis and possibilities in information sharing.

Contextually, some connected principles and

concepts are highlighting new requirements for the

knowledge and new needs for the data management.

In particular, interoperability is a key issue, on which

the idea of the Semantic web, smart cities and

international standards are built (Barnaghi et al.,

2012, Chourabi et al., 2012, Schaffers et al., 2011).

A unique frame is therefore needed in order to

make the conceptualisations unambiguous. This can

be solved through the use of ontologies (Guarino,

2009, Laurini, 2015) in order to reduce the risk of

misinterpretation and possible consequent damages

or loss of information (Guizzardi, 2005). Moreover,

the definition of an explicit and shared data model

permits to produce and share open data, with all the

connected advantages (Janssen et al., 2012).

Therefore, the world of spatial knowledge

management and geographical intelligence is

developing tools for the realization of an effective

“geoweb” (Laurini, 2014). We can see the effort in

the directives of some national and international

institutions dealing with cartography or

environmental management: for example, the

INSPIRE (INfrastructure for SPatial InfoRmation in

Europe) European Directive is developed by the

European Parliament and the Council of 14

March

2007 (Directive 2007/2/EC)

(http://inspire.ec.europa.eu/). Equally, some

consortiums of major stakeholders and actors of the

sector are developing international industry

standards, becoming the base for interoperability and

open data. In this framework the OGC (Open

Geospatial Consortium) (www.opengeospatial.org/)

standards (among which the model for urban data

CityGML) are conceived.

CityGML (http://www.opengeospatial.org/

standards/citygml) is an open data model, an

application schema (XSD) for GML files aimed at the

representation, storage and exchange of 3D urban

objects. The original aim (its history begins in 2007)

was to foster the reusability of 3D city models. Its

semantic definition can be equally useful to manage

the semantics of the data with the tools offered by

informatics and artificial intelligence.

168

Noardo, F.

Architectural Heritage Ontology - Concepts and Some Practical Issues.

In Proceedings of the 2nd International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM 2016), pages 168-179

ISBN: 978-989-758-188-5

Some more examples can be seen in the opposite

direction, that is, the effort of the world of semantic

thematic data to include geographic information. For

this reason, GeoSPARQL (http://www.opengeospatial.

org/standards/geosparql) is developed by OGC as an

extension of the W3C (World Wide Web

Consortium) (www.w3.org/) SPARQL (SPARQL

Protocol and RDF Query Language)

(http://www.w3.org/TR/rdf-sparql-query/), which is

the designed language to query RDF-structured data.

It is considered for the inclusion of spatial data in

RDF-OWL information.

These languages are defined by the cited

organizations, and represent the crucial technology

for the application of the theories of open-data and

interoperability. Among these, markup languages

allow to write content and provide information about

which role the content plays using a both human and

machine-readable format. In particular, XML

(eXtensible Markup Language)

(www.w3.org/XML/) is used as a metalanguage for

markup: it provides a uniform framework, and tools

for the interchange of data and metadata among

applications. This is why XML is the base of most of

languages born to structure open and application-

independent data and exchange them through

application or through the web. Some of relevant

XML – based languages are for example RDF

(Resource Description Framework)

(www.w3.org/RDF/), which permits to manage

semantic data (through a triple mechanism), OGC

GML (Geographic Markup Language)

(www.opengeospatial.org/standards/gml) to archive

geographical objects, COLLADA (Collaborative

Design Activity)

(https://it.wikipedia.org/wiki/COLLADA), which is

an interchange format for 3D models, and so on. The

structure of the XML-based files is defined in equally

XML-based formats, such as simple XML Schema

Definition (XSD), which is the one used by GML

format, or extended ones such as RDFS (RDF

Schema) - OWL (Ontology Web Language)

(www.w3.org/2004/OWL/).

An example of geographic issues managed on the

web using the described technologies is GeoNames

(http://www.geonames.org/) which is a database

including toponyms gazetteers and information

related to the included named places.

Looking at the Cultural Heritage field, database

interoperability and information retrieval have

always been crucial aims for its documentation

(http://www.icomos.org/en/charters-and-texts). It is

indispensable the data to be unambiguous for

permitting correct interpretation, and to be

contextualized with metainformation.

The CIDOC (International Committee for

Documentation) conceptual reference model (CRM),

developed by the Commettee of the ICOM

(International Council of Monuments) is considered

the core ontology for Cultural Heritage (Doerr, et al.,

2007). It uses RDF-OWL for the management of

thematic data. It became standard ISO 21127.

A further existing database exploiting the

described theories and technologies are a set of

vocabularies developed by the Getty Institute

(http://vocab.getty.edu/). These are oriented to

structure Cultural Heritage related terms and items,

and are divided in four vocabularies. Art and

Architecture Thesaurus (AAT), structures

hierarchically the terms linked to the description of

the works of art and architectures. The Getty

Thesaurus of Geographic Names (TGN) differently

from GeoNames, includes also historical

denominations. The Union List of Artist Names

(ULAN) contains the names and synthetic

information about the cultural heritage authors; and

the Cultural Objects Name Authority (CONA),

describes the different denominations of a cultural

item over the time. In them the spatial component is

not present, but they can be the reference for the

denomination of parts which unequivocally have a

spatial connotation (e.g. all the architectural parts or

toponyms), or for related information (such as authors

or object names).

Recently some effort has been done also to

include geographic information in cultural heritage

descriptions. Some localisation data is tried to be

included in semantic structures: the Getty project

ARCHES (http://archesproject.org, Myers et al.,

2013), based on CIDOC-CRM structure integrates

some WebGIS function; the CRMgeo project (Doerr

et al., 2013) includes spatio-temporal representation

potentiality in CIDOC-CRM.

However, these geographic references are often

bi-dimensional and have little defined geometry

(points, lines or approximate polygons), since the aim

is not the analysis and reading of the artefact

geometry, but its localisation for a territorial reading.

Recently, another extension of the CIDOC CRM was

realized: the CRM

BA. It is expressly realized for the

documentation of standing buildings (Ronzino et al.,

2015). However, the gap in this research could be

found in the management of complex 3D models in

connection with other parts of the city and the

landscape, which is a topic treated by CityGML.

For the particular needs of architectural heritage

information management, 2D (often small-scale) data

are not sufficient. 3D dense data have to be exploited

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with higher levels of detail (high measurements and

georeferencing accuracies) and complex semantic

definition (object-oriented structures) (Laurini,

Thompson, 1992).

The availability of the 3D dense models is a

reached aim of survey and geomatic discipline

(Chiabrando, Spanò, 2013). However, the potentiality

of management, analysis and editing typical of

traditional GIS (Geographical Information Systems)

are at present moment reduced for this kind of data.

The development of new software structure or user

interfaces are needed, based on adapted or new

theoretical framework (Brahim et al., 2015,

Solovyov, 2012), which again permit the usability of

the systems in a real effective way.

1.1 Proposal Aims

In this research, a solution to the need of a data model

for architectural heritage 3D high-level-of-detail data

is proposed, by extending the existing structure OGC

CityGML using its ADE (application domain

extension) procedure.

CityGML was chosen as a base since it is a

standardized model already dealing with buildings in

their double dimensions: as a part of the city and as a

higher detailed 3D object. It is important to consider

this double nature also in architectural heritage

emergences, because they are often both meaningful

to the definition of the cultural values of the

considered buildings. Moreover, CityGML includes

the possibility to have multi-scale representations.

The integration of the monument in wider maps of the

city or the landscape, permits to perform strategic

analysis in a broader context.

CityGML is shared as a data model, already in a

potentially implementation-ready format. The UML

(Unified Modelling Language) diagrams are

published in the OGC encoding standard (OGC,

2012). They are already in an advanced phase of the

data modelling process, since the database design

details are specified as in a logic-level model (e.g. an

object-oriented approach is envisaged and types of

data and code-lists are defined). Moreover, the XSD

files are shared and available for the direct use for

implementation. However, for its generality in

representing urban models, it can be considered an

ontology (Métral et al., 2009, Kolbe et al., 2008). It is

in fact independent from the specific applications for

which it can be used and aims at representing a

common frame for urban 3D maps data.

Therefore, for extending CityGML including

structures for the management of spatial data

complexity of architecture and monuments, some

preliminary general reflections are reported, which

can be valid as ontological-level thinking. However,

the extension is then realized in accordance with the

formats and structures used in CityGML

(implementation-oriented), to be coherent with the

extended model and for permitting the test also in the

implementation.

However, some considerations and necessities of

representation remain at present unimplemented,

about more evolved constrains to be imposed to the

model.

In a second part, the procedure followed for the

implementation of the model is presented,

highlighting some possibilities of use of the schemes

for data archiving.

In the end, some part dealing with the kind of data

to be managed is presented, taking in consideration

the processing phases to be followed (from the

processing of the 3D model to its semantic

visualisation).

2 CITYGML CHADE (CULTURAL

HERITAGE APPLICATION

DOMAIN EXTENSION)

CityGML model can be extended in order to model

further aspects linked to specific application domains.

The so-composed extensions use specific

characteristics and procedures of CityGML, being

defined as ADE (Application Domain Extension).

Some official ADEs exist (http://www.

citygmlwiki.org/index.php/CityGML-ADEs). They

regard especially some urban-scale themes, such as

the noise, or the inclusive routing. Some of these are

specific on buildings, for example GeoBIM integrates

some classes derived from IFC (Industry Foundation

Classes) (https://en.wikipedia.org/wiki/Industry_

Foundation_Classes) standard used in BIM (Building

Information Modelling) (de Laat, van Berlo, 2011).

However, even if in the future probably the field of

BIM (born to project new buildings) will meet GML

models, at present it’s too rigid for describing

Cultural Heritage buildings, which need more

flexibility.

A further research has been performed for the

extension of CityGML model in order to include

some information about the CH (cultural heritage)

nature of the building and some surface

characteristics, such as the deterioration

(Costamagna, Spanò, 2013). In the model proposed in

this paper, the characteristics of surface complexity

are tried to be included. Moreover, some attention is

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drawn to the traceability of the stored information, in

order to include in the data the elements useful to

technicians for interpreting the stored information

and evaluating the degree of fuzziness of the data.

In Figure 1 the CityGML Cultural Heritage

Application Domain Extension (CHADE) for the

building module of CityGML is summarized. It is

then analysed in detail in the following subsection.

The extension has been developed and will be tested

on the building module; anyway, once its validity will

be proved, its concepts and classes can be applied also

to the other CityGML modules.

Figure 1: Synthesis of the CityGML CHADE in UML

diagram. In white the CityGML classes, in grey (black for

the whole class) the CHADE extensions and the inserted

relations.

2.1 The CHADE Components:

Research of Granularity, Flexibility

and Traceability

From the general to the particular, the first problem

was to include some attributes useful for the

identification of the monument and some related

information (if a CH declaration exists, what are the

related documents, who are the owners and what is

the preservation authority). Some of these have been

borrowed from previous researches (Costamagna,

Spanò, 2012), and extend the Core class

“AbstractCityObject”. It is possible to include this

kind of extensions by means of composite attributes

also in following phases, that is, the implementation

of the model, since the XSD format permits to include

complex attributes in the form of DataType,

composed by a series of further attributes. Another

interesting possibility for this case is the

“ExternalReference” class, already in CityGML,

which permits to relate the model with further

databases managing data about the same object. For

example, considering the management of the

Versailles castle, the reference can be realized to the

instance having ID:700000350 of the CONA

vocabulary of the Getty Institute which describes it

(http://www.getty.edu/cona/CONAFullSubject.aspx?

subid=700000350).

The second issue is the extension of the attribute

list for the “AbstractBuilding” class. In particular, its

function and its denomination. Both these values are

complex when regarding a historical item, since both

can change over the time, and must be archived as a

reference for researches and as an element for

understanding the history of the building. Therefore,

in implementation phase, for both a DataType is

included. The BLDG_Function data type includes at

first the function name (at present in English, specific

future works with historians could further evaluate if

considering different languages in order not to lose

meaning nuances). The reference to the URI of the

Getty Institute vocabulary AAT (Art and Architecture

Thesaurus) follows, which includes the terms linked

to the buildings function as subclasses of “single built

works by function”. The last two attributes are present

almost everywhere in the detailed added data types,

because they are of fundamental importance for

historical data connotation. The time attribute is

defined as a time object defined in the same GML

general schema. It also could be defined as a

TM_Object (time object) as stated in ISO TC211 ISO

19108:2006 Temporal Schema, but some

incompatibilities among some ISO TC211 definitions

and GML requirements persist

(https://en.wikipedia.org/wiki/Geography_Markup_

Language). Anyway, both schemas have issues for

detailing the time considered, as a date, as a period,

with different degree of fuzziness and with the

possibility to establish a sort of topology for temporal

data, in a temporal reference system. It is of obvious

importance for managing historical data. The second

attribute is “Source”, which is detailed, in turn, in a

data type, including metadata, reference to the source,

codes for its identification and retrieval and the same

attribute “time”.

Similarly, the attributes of the class “Room” are

extended, adding “RoomClass”, “RoomFunction”

and “RoomUsage”, all with reference to the Getty

AAT vocabulary URI. The “RoomUsage”, which can

change over the time, is detailed in a dedicated data

type.

The, may be, more interesting part of the model is

the extension of the CityGML class

“AbstractBoundarySurface”. In the original model it

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has no attributes, and can be specialized as belonging

to the main parts of the buildings (e.g. RoofSurface,

CeilingSurface, WallSurface…). The change of this

class can permit to follow with a major flexibility the

description of the parts of the buildings, which are

stratified and articulated and even small portions can

have different meanings. With “portions” also “fiat

parts” (without “bona fide”, that is defined,

boundaries) are intended. Therefore, a recursive

mereological “part of” relation is added from

AbstractBoundarySurface to the same

AbstractBoundarySurface. This permits to articulate

the surfaces in hierarchical, semantically well-

defined, multiscale and possibly topologically

defined parts. Several attributes are added and

defined following the already explained criteria.

Among these, the “LevelOfSpecialisation” (LOS)

attribute deserves an explication. The 3D models are

usually considered for the geometric accuracy, which

mainly derives from the production methods and

measurements systems. This characteristic is stored in

GML models as LOD (Level of Detail) associated to

each geometry. Even if it implies some consequence

on the level of semantic definition, it’s mainly linked

to the possibilities of representation offered by the

available data, and thus to the accuracy and data

density. The Level of Specialisation, in inserted in

order to manage the possibility to define parts and

subparts which can be recognisable on the same

model (with homogeneous accuracy and LOD) but

need to be separately specified because of the

different meaning they assume if considered in the

whole or as a singular part (Figure 2).

Figure 2: Examples of consecutive LOS specified on parts

of a homogeneous-LOD 3D model. The colours represent

the parts in which the object is divided.

A further extension of this class regards the

associated geometric levels of detail: two more LODs

are added, a LOD5, for approximately 1:50 scale and

a LOD6 for bigger ones. The associated geometry

class must be defined as a “Geometric

complex::GM_CompositeSurface”, since it is

structured and hierarchical, in the same way as the

boundary surfaces must be also semantically defined.

Moreover, it has to be related to a “Topological

Complex::TP_Complex”, deriving from the

“Topology” part of the standard ISO TC211 – ISO

19107:2003 Spatial Schema or the GML specification

(they should be harmonised for the same issues

regarding time objects). This last described part is

complex to be used with current software and

requests some more efforts. Anyway, the inclusion of

the topological relations as schematized in Figure 3

should be useful for correctly set the models.

OGC has processed some topological and

mereotopological structure for helping to correctly

store the data, but they are already oriented to linked

open data formats, without regarding GML

(http://ows10.usersmarts.com/ows10/ontologies/).

Figure 3: Schema of Egenhofer Topological Relations to be

included in the model and verified. Some exception can

exist (for example, a pillar can be considered only for one

half as a component of a bay, admitted that they belong to

the same classification), these must be so analysed in order

to confirm or not the validity of this model. Egenhofer

relations are considered even if they deal with 2D geometry,

since an only reference surface is considered, although

being a 3D surface.

2.2 Implementation Issues

Ontologies exploit object-oriented structures and

systems, which are unusual in current and known GIS

management systems: some of the most spread ones

(PostgreSQL-PostGIS, ArcGIS Geodatabase tool,

Oracle) implement object-relational systems, which

are hybrid systems including some constructs of

object-oriented databases, but not the whole

potentiality. Some studies about the development of

some semantic GIS have been performed, beginning

in the mid-1990s (Mennis, 2003, Fonseca et al.,

2002). In these studies, an object-oriented approach

was used as an effective solution for expressing and

storing the data meanings (Scholl, Voisard, 1992). In

this way, even more powerful systems could be built

with significant data interoperability and a reduction

of any potential ambiguity. Anyway, at present

moment few similar systems are available, preferring

to use SQL-based implementations (Belussi et al.,

2011). This is due to the necessity to adapt the

exigencies to the available platforms and software

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systems and to the necessity to change the storing

methods to permit the production and management of

computationally heavy files. In next years probably

the object-oriented GIS will be developed again or,

some different interface from the GIS we know will

be improved to include spatial analysis and query

functionalities.

The described model has been implemented using

the method defined as best practise by OGC (van den

Brink et al., 2012). UML schemas are modified,

which use stereotypes defined by a GML UML

profile, so that their meaning can be understood by

the machine and the performed transformation can be

coherent and correct. In particular, for building the

system the proprietary commercial software Sparx

Systems – Enterprise Architect is used. Contrary to

the indications of using open source software for

managing public (and open) data, it is recommended

also in some official occasions (for example for the

management of INSPIRE schemas). The software

permits to import existing models (in this case,

obviously CityGML building module and some

general schemas such as GML are used; also ISO

19108 for temporal objects and ISO 19107 for spatial

issues could be considered). The classes, selected and

imported in the new extension model, maintain all

their characteristics and relations with the other parts

of the model they belong to. This is crucial for not to

create an isolated new model, but to be inserted in a

complex existing framework.

From this basis, new classes can be added, the

attributes can be defined and new relations can be

established.

In particular, following the OGC best practise, for

extending an existing class with further attributes, a

subclass having the same name of the class to be

extended and stereotype “ADEElement” should be

created. The specialisation relation is marked with

stereotype “ADE”. For adding a new class, a simple

subclass having stereotype “featureType” must be

added.

The so-formed model (Figure 4) can then be

exported in different formats, including XSD for

being used as a GML application schema. Other

interesting formats are OWL, ArcGIS workspace and

similar. From the XSD file also SQL (Simple Query

Language) relational or object-relational database

schemas could be generated, by passing through

different software, such as Altova XMLSpy, which

permits to manage XML documents. However, the

passage from an object-oriented model to a relational

one often requires some adapting transformations.

Contrary to what it seems, the passages are not so

easy, or, better, they have to be controlled and

corrected, since they need correct information or

reference files describing, in the specific software-

understandable language, how the transformation

must be done. Some specific applications and proper

UML profile exist for this aim, but they are not

always easily available and compatible in any

situation. Waiting for this progress, possibly planned

as future work, the resulting files have to be corrected

manually by editing the XML text following the rules

for the ADEs realization.

Figure 4: Synthesis of the UML model modified for

extending CityGML – Building module in the CHADE,

following the OGC best practise indication (Van den Brink

et al., 2012).

3 PREPARING THE 3D DATA

For processing and interchanging the data about the

paper case study, which is the medieval Staffarda

abbey church (in the north-west of Italy) some of the

previously described technologies are used. The main

problems along the whole workflow are often linked

to the inability of the software to manage some

functionalities and algorithms and/or formats at the

same time. For this reason, several passages in

specific software are needed.

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In this research, existing and available software

are used, being not the implementation of new

applications among the objectives. In particular, open

source solutions are preferred, when possible, for

interoperability and replicability issues.

When the schemas are ready, the dense high-

level-of-detail 3D models have to be prepared. Since

the managed surfaces are complex, being composed

by miles of triangles (stored in form of rings

composing a multiple composite surface), it’s

obviously not possible to store manually the singular

points, but they have to pass through a series of

phases which permit to export them in a GML format.

We will not describe here the acquisition and

processing phases, which exploit a series of

techniques for georeferencing the model in a known

reference system (Chiabrando et al., 2013, Dabove et

al., 2014), measuring points with various methods

and variable accuracy and density (Bryan, Blake,

2000), processing the models for finally obtaining an

integrated, correct, georeferenced and optimized 3D

model (Figure 5) (Bastonero et al., 2014). We

suppose then to start the process from this point.

Figure 5: Views of the 3D model (textured mesh) of the

Staffarda abbey church, processed using LIDAR

acquisitions integrated with photogrammetric data acquired

from UAV (Unmanned Aerial Vehicle) (Bastonero et al.,

2014).

The first editing phases to be performed on the

models regard on the one hand the reduction of its

points, caring the conservation of the original

definition (Figure 6). This process can be performed

using different algorithms, not always known in

proprietary software. Anyway, the topic should be

further analysed in order to establish the methods and

the limits of this practise.

On the other hand, the model must be segmented,

so that every part must be isolated from the other for

being suitably managed geometrically and

semantically (Figure 7); moreover, the temporal

connotation must be considered in the segmentation,

since it is essential for historical objects (Donadio,

Spanò, 2015). A surface can be eventually repeated if

it is part of more than one instance having different

LOS as attributes. Also this field can offer a quantity

of techniques which should be analysed for finding

the most suitable one.

Figure 6: 3D models of the church façade before (first

image) and after (second image) reduction.

Figure 7: 3D model of one segmented capital (a segmented

part is highlighted with textured representation).

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These phases can be performed in 3D model

processing and editing software, such as Hexagon 3D

Reshaper (proprietary software), which has the

advantage of managing coordinates, which have high

values such as cartographic ones, therefore

georeferenced models can be directly managed.

Moreover advanced editing tools are integrated in it.

At this point, two main alternatives are available

for translating the 3D model into a CityGML-

compliant format. The first one is the use of Safe

Software FME (again a proprietary software), which

is expressly dedicated to these operations. The second

option is the use of ESRI ArcGIS, which is equally a

proprietary software, but being widely spread, its

formats and procedures are often considered as de-

facto standards. This last one is used in this case for

this reason, even if the passage from an ESRI

shapefile format, which is based on a relational

model, doesn’t give the possibility to directly specify

the final structure of the data. Anyway, also the ESRI

processing integrates the FME algorithms in the

ArcGIS “Data Interoperability Toolbox” extension.

For using the processing integrated in ESRI

ArcGIS, some more passages are necessary. The

processed 3D model must be exported in COLLADA

format for the following transformation. This open

exchange format is not managed by some proprietary

software, therefore the model must be exported in 3D

model format (such as OBJ or PLY) and reimported

in further software able to do the exportation. For

example, the open source software MeshLab can do

that. The problem is that it has difficulties in

managing high coordinate values, so that the whole

model must be translated near the origin for this

passage. The exported COLLADA files can be then

reimported in ESRI ArcGIS, as multipatch shapefiles

(ESRI, 2008). Here they have to be retranslated to

their original position in georeferenced coordinates,

and can be exported, through the “Data

Interoperability” toolbox to a generic CityGML file.

The result is the inclusion of the geometry and the

attributes of the single parts of models in files

structured as CityGML and semantically classified as

“GenericCityObjects”. The GML file (readable as

XML structured text) has to be manually modified for

including in the description schema the CHADE and

to correctly define the semantics of each part.

In particular, the reference to the extension

namespace must be added in the heading of the file,

since there is no way of modifying the FME libraries

(used directly or through ArcGIS toolbox) for

including the extensions. Moreover, each segmented

part of the multipatch is exported as a distinct object

having a geometry attribute (in form of

gml::MultiSurface), but they are not hierarchically

structured and they haven’t a specific semantic yet

(being all “GenericCityObjects”). Therefore, the

hierarchy must be set and the correct labels must be

applied following the CityGML file format.

Moreover, all the textual attributes must be manually

filled in. In this phase it is obviously considered the

extended model CityGML+CHADE. Another

important issue is to add suitable identifiers, in order

to uniquely identify the objects for query performing

and information retrieval and for realizing some

connections, for which for example Xlink syntax

(which requires IDs for linking to specific objects) are

used. It is preferable if the IDs are composed in form

of URIs (Unique Resource Identifiers), following the

rules used in best practises also in linked data

environment (van den Brink et al., 2014). In this way,

the produced information could be more easily

translated to linked data for the effective sharing and

processing through the Semantic Web.

The Xlink syntax can also be considered and used

for the establishment of mereo - topological relations

among the parts.

XML processing softwares (some used

alternatives can be, for example, the proprietary

software ALTOVA XMLSpy or the open source

software Xpad) can validate the obtained GML file.

4 RESULTS: THE ARCHIVE IN A

GRAPHICAL INTERFACE

At this point, the GML file could be shared through

the web and read by several applications or interfaces

for being consulted and analysed.

In this case, an open source software was used and

tested in order to read the GML archive based on

CityGML CHADE. An open source software was

chosen for two main reasons: first, for the already

cited goals of interoperability and replicability of the

procedures; secondly, because the open source

software often permit to access the source code of the

libraries they use, and possibly modify them. This is

useful in order to include the CHADE schema for the

correct interpretation of objects that refer to it.

The FZK software (http://www.iai.fzk.de/www-

extern/index.php?id=2315) was used, which is one of

the more developed available CityGML viewers. It

includes the schemas of some versions of CityGML,

and also some official CityGML ADE (e.g. the Noise

ADE). Furthermore, it has an open structure, which

can be customized by adding, for example, other

CityGML schemas to be used. For this research the

Architectural Heritage Ontology - Concepts and Some Practical Issues

175

CHADE schema (in XSD) was added in the directory

of the reference files of the software for the described

data to be interpreted. This is unequivocally an

advantage of the open structure of the software.

At this point the software can read the processed

GML archive (Figure 8).

In the visualization platform the object inserted in

the archive can be read, including the relationships

among them (Figure 9), some measurements can be

directly made on the 3D model (Figure 10) and some

thematic visualization can be generated similarly to

GIS management software environments (Figure 11).

Moreover, statistics about the data are computed.

However, the application should be developed in

order to include the possibility to effectively manage

some elements introduced by the extension, for

example the inclusion of different addresses (referred

to the building but also to the owners, the authority,

etc.) gives sometimes problems in their visualization.

In the same way the links inserted in the GML file for

cross-referring the objects or for inserting references

to external resources (for example the Getty

vocabularies) don’t function in the software, because

probably some change in the reading of such

components should be done.

Equally, the levels of detail that can be visualized

are limited to the ones envisaged by CityGML. For

including the more detailed ones added in the

CHADE, the application should be modified not only

by adding the schemas but even in its tools and

interface code.

Figure 8: GML model structured using the CityGML

CHADE in the FZK software interface: on the left, the

objects in the model are listed, in the centre the 3D model

is visualized and, on the right, the properties can be read.

The attributes, which are, in turn, objects themselves or data

types (and are therefore composed by a set of attributes) are

highlighted by the frames. The level of detail to be

visualized can be chosen, since the data are multi-scale (in

the left part of the toolbar, framed in the figure).

Also the possible thematic visualizations are

limited to some attribute of CityGML and don’t

consider the ones introduced by the extension. The

same is for the statistics and analysis that can be

performed, which are limited to some pre-set

parameters and it would be interesting to enhance

them.

However, these limits are connected to the

visualization platform, while the previously

structured GML file is independent from them.

Figure 9: On the right box (“relations” window) it is

possible to select and visualize related objects (geometry

and thematic attributes). In the image, the result of the

relation of the whole object to one of its parts (the flying

buttress). They are selected in the representation and the

attributes are listed in the right part.

Figure 10: Example of direct measurements possibilities on

the 3D model: areas and distances. This can be extremely

useful for architectural heritage researchers and operators.

Figure 11: Example of thematic visualization (based on the

attribute “year of construction”).

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5 DISCUSSION AND

PERSPECTIVES

In the framework of interoperability established by

the Semantic web theories and the world of standards,

the establishment of reference domain ontologies

become critical. Since a model for architectural

heritage lacked, several standards dealing with

building, landscape or city representation and cultural

heritage management were considered as starting

point for an extension or for their reciprocal

integration. Finally, the OGC CityGML model was

chosen as ontology for representing buildings. It is

considered an ontology for being specific application

– independent, even if implementation issues are

proposed in the published standard.

An extension of the CityGML model has been

proposed and tested in order to manage complex and

multi-scale 3D models. This considers some

important aspects of the architectural heritage both

from the spatial and thematic points of view.

The conceptual definition was implemented using

some existing tools, proposed as standard best

practise. However, some passages result still difficult

and the products need to be refined manually by

editing the resulting XML file for obtaining a valid

XSD. Future improvements will deal with the major

control and automatization of the processes.

Similar considerations can be done for the

management of the 3D models, which requires

complex steps, possibly through different software

for being prepared. In the end, a final manual editing

of the GML file is equally necessary. This could be

generally due to the closed source of proprietary

software, which does not permit to modify the used

libraries for inserting the extension of the model. In

the meantime, there is little alternative to their use.

The fact that the editing of results is possible using

XML language is beyond doubt an advantage,

because it requires basic tools (even a simple text-

editor could be effective), on the other hand, the

required skills are not within everyone’s reach.

However, a solution is proposed for managing the

complex and multifaceted data about architectural

heritage. Important aspects are cared, regarding the

granularity of the information, its traceability, which

is essential when dealing with historical items, the

flexibility of the model, to adapt to the representation

of such unique artefacts as monuments are, and the

inclusion of thematic data with eventual reference to

external databases and vocabularies.

The realization of standardized datasets using

ontologies permits to perform automated reasoning

on the information, in particular if shared on the web.

Furthermore, the use of ontologies enables the

interoperability of databases and the information

retrieval through the semantic web. This represents

obviously a great opportunity for research and

preservation issues, but also for management,

tourism, risk analysis and further connected activities.

The archive at present can be used in applications

similar to the known GIS, for surfing the archive,

realizing queries, applying symbols, measuring the

model. However, also the available platforms should

be modified and improved in order to permit a wider

range of analysis and statistics and to include

enhanced visualisation options.

Future work will be aimed first at including the

real management of topology and mereo-topological

constraints in the models and in the data, for

enhancing the analysis potentialities and transversal

information retrieval.

A further improvement will affect the connection

with external reference to vocabularies (possibly

using methods similar to the use of gazetteers for

toponyms) and the inclusion or link to further data

models and ontologies: for example, the connection

to the CIDOC CRM is of primary importance.

Moreover, the translation of the model and of the

dataset as linked open data will be essential to better

exploit the Semantic Web technologies and to

connect to similar information. This also will be a

future development of the proposal.

When these aspects will be solved, it will be a

further step towards the world-wide management of

the architectural heritage data in an effective

framework for their preservation, retrieval and

analysis.

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