GEOPROFILE

UML Profile for Conceptual Modeling of Geographic Databases

Gustavo Breder Sampaio, Filipe Ribeiro Nalon and Jugurta Lisboa-Filho

Departamento de Informática, Universidade Federal de Viçosa (UFV), 36570-000 Viçosa, MG, Brazil

Keywords: UML profile, Conceptual model, GIS, Geographic database.

Abstract: After many years of research in the field of conceptual modeling of geographic databases, experts have

produced different alternatives of conceptual models. However, still today, there is no consensus on which

is the most suitable one for modeling applications of geographic data, which brings up a number of

problems for field advancement. A UML Profile allows a structured and precise UML extension, being an

excellent solution to standardize domain-specific modeling, as it uses the entire UML infrastructure. This

article presents the metamodel of a UML profile developed specifically for conceptual modeling of

geographic databases called GeoProfile. This is not a definite proposal; we view this work as the first step

towards the unification of the various existing models, aiming primarily at semantic interoperability.

1 INTRODUCTION

For the past 20 years, a number of research groups

have been studying the requirements for conceptual

modeling used in GIS applications (Bédard et al.,

2004). A large number of conceptual models

specific to this area were proposed. OMT-G (Borges

et al., 2001), MADS (Parent et al., 2008), GeoOOA

(Kösters et al., 1997), UML-GeoFrame (Lisboa

Filho and Iochpe, 2008) and the Perceptory's model

(Bédard, 1999) are important among these models.

Despite the maturity of this research field, to

date, there is no consensus among designers and

users as to which model best meets the requirements

for modeling a geographic database (GeoDB). The

lack of a standard model brings up serious problems

in the development of the field, as for instance,

communication difficulties among different projects.

For example, considering CASE tools that support

conceptual models specific to GeoDB, data

conceptual schemas cannot be migrated between

different tools, as it happens with conventional

database designs.

These problems would not exist if there were a

standard for modeling such applications that

incorporated the main features of the existing

models. The creation of a UML profile is one option

to standardize this type of models. UML profile is a

feature that allows for a structured and precise

extension of the UML elements so that it can fit into

a specific domain (Fuentes and Vallecillo, 2004).

This paper aimed to initiate the specification of a

UML Profile for the conceptual modeling of GeoDB

taking into account the requirements imposed on this

application domain. Some models in the literature

provided the basis for this task.

The remaining of the paper is structured as

follows. Section 2 describes the GeoDB conceptual

modelling and the main current models, while

Section 3 details the proposal to the GeoProfile.

Section 4 presents the conclusions and future work.

2 CONCEPTUAL MODELING OF

GEOGRAPHIC DATABASE

The profile proposed in this paper is based on

contributions from a number of models existing in

the literature, as well as the concepts defined in

Goodchild et al. (2007). The models that have

contributed most significantly to the GeoProfile

development are cited below, but certainly other

predecessor models also had their contribution.

The OMT-G (Object Modeling Technique for

Geographic Applications) model (Borges et al.,

2001) has a rich collection of conceptual

constructors, the strong point of which is modeling

spatial relationships, including spatial aggregation.

The GeoOOA model (Kösters et al., 1997) supports

the abstraction of spatial classes, whole-part

topological structures, network structures and

409

Breder Sampaio G., Ribeiro Nalon F. and Lisboa-Filho J. (2010).

GEOPROFILE - UML Proﬁle for Conceptual Modeling of Geographic Databases.

In Proceedings of the 12th International Conference on Enterprise Information Systems - Information Systems Analysis and Speciﬁcation, pages

409-412

DOI: 10.5220/0002854004090412

 SciTePress

temporal classes. MADS (Modeling of Application

Data with Spatio-temporal Features) (Parent et al.,

2008) approaches objects and relationships in its

diagram, with structures very similar to the Entity-

Relationship model. The Perceptory’s model

(Bédard, 1999) was the pioneer in the use of

pictograms. These pictograms are grouped into the

languages Spatial PVL and Temporal PVL (Plug-in

for Visual Languages), which allow the addition of

spatial-temporal characteristics not only to UML,

but also to other visual modeling languages. The

UML-GeoFrame model is based on a structured

hierarchy of classes that make up the GeoFrame,

providing the basic elements present in any

geographic database (Lisboa Filho and Iochpe,

1999).

Finally, Clementini et al. (1993) formally

describe a small set of relationships capable of

reproducing all the possible topological relationships

that can occur between spatial elements with the

representation of point, line or area. This work has

considerable importance in the scope of the

GeoProfile design. Defining a minimum set of

relationships, one eliminates the possible use of two

relationships with different names, but having the

same meaning. This set includes the following

relationships: touch, in, cross, overlap and disjoint.

3 GEOPROFILE

GeoProfile is a UML profile built for the conceptual

modeling of geographic databases. According to the

proposed methods to guide the construction of a

UML Profile (Fuentes e Valecillo, 2004) e (Selic,

2007), two artefacts are generated during profile

development: the domain metamodel and the profile

itself. While the first is useful to understand the

addressed problem, the second presents the

extensions received by the UML metaclasses.

Section 3.1 defines a metamodel for the

geographical domain and section 3.2 proposes a set

of stereotypes for the proposed profile.

3.1 Defining a Metamodel for

Geographical Domain

At the beginning of the metamodel specification,

elements are identified in a conceptual schema,

observing the requirements of this type of

conceptual modeling.

The way each considered conceptual model in

this proposal (GeoOOA, MADS, UML-GeoFrame,

OMT-G and Perceptory’s model) meets the found

requirements was examined. The inclusion of the

main mechanisms present in each of these models

into the GeoProfile allows it to meet most

requirements of a geographic database (GeoDB).

Among the discussed conceptual models, the

UML-GeoFrame shows the closest organization to a

metamodel. GeoFrame is defined in a class

hierarchy representing the elements present in a

GeoDB. Thus, the metamodel development started

from a GeoFrame adaptation (Figure 1).

A GeoDB comprises a number of themes, which

is characterized by the metaclass Theme. A theme

can be formed by the aggregation of other themes or

objects with or without spatial representation,

characterized by the classes GeoPhenomenon and

ConventionalObj respectively.

When one chooses to associate a spatial

representation with objects of a class, it is possible

that the phenomenon is perceived in the geographic

field view (GeoField) or object view (GeoObject).

Depending on the technique used in geographic

information acquisition in the field, its representa-

tion be selected from six options as described in

Goodchild et al. (2007): AdjPolygons, Isolines, TIN,

GridOfPoints, GridOfCells or IrregularPoints.

Representation of geographic objects can be of the

types point, line, polygon or complex (the object

geometry consists of other geometries).

With basis on GeoOOA and OMT-G models,

which provide more detailed solutions for network

representation, Stempliuc et al. (2009) proposed an

extension of GeoFrame to address the requirement.

This extension was incorporated into the metamodel.

The classes in charge of storing alphanumeric

data and information on which elements participate

in the network are represented by the metaclass

Network. Since this metaclass does not have spatial

information, it was defined as a ConventionalObj

specialization. The networks are formed by network

objects (NetObject), which can be nodes (Node),

unidirectional arcs (Unidirectional) or bidirectional

arcs (Bidirectional).

For temporal aspects, the solution proposed by

GeoProfile is to indicate only whether a class is

considered temporary or not, as in the GeoOOA

model. In this way, the metaclass TemporalObject

was added to the metamodel. This metaclass has two

attributes that characterize temporal information.

One of these attributes indicates the temporal type

(validity time, transaction time or bitemporal time),

whereas the other defines the used temporal

primitive type (instant or interval). There are two

enumerations (TemporalType and TemporalPrimiti-

ve) for the possible values these attributes can

assume.

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Figure 1: Metamodel for the geographical domain.

3.2 GeoProfile Stereotypes

After creating the domain metamodel, the next step

is to extend the UML metaclasses to create the

profile itself. Figure 2 illustrates the stereotypes of

GeoProfile.

It is worth noting that not all metaclasses of the

domain metamodel have a corresponding stereotype,

as it happens with Theme and ConventionalObj.

Themes can be represented by packages. Classes of

conventional objects are, however, modeled by

UML classes without addition of stereotypes.

Therefore, the UML constructors themselves can

reproduce these two concepts.

Geographic phenomena, extending the metaclass

Class, are defined in a similar hierarchy to that

found in the domain metamodel. The stereotype

Network directly extends the metaclass Class, since

there is no stereotype defined for representation of

conventional objects.

To deal with temporal aspects, the stereotype

TemporalObject was added to GeoProfile, as well as

two enumerations (TemporalPrimitive and Tempo-

ralType). In addition, designers are allowed to

indicate that an association between two objects is

only valid for one period and this history should be

kept in the database.

This is done by simply assigning the stereotype

Temporal, which extends the metaclass Association

to an association of the schema.

Finally, stereotypes were created to represent the

topological relationships that were not considered

during drawing up of metamodel. We chose to use

the set of five relationships proposed by Clementini

et al. (1993), as they are capable of representing any

topological relationship between objects of type

point, line or polygon. Thus, the stereotypes Touch,

In, Cross, Overlap and Disjoint, all extending the

metaclass Association, were added.

4 CONCLUSIONS

This article showed a standard conceptual model for

geographic database modeling to be feasible. The

existence of several alternative conceptual models of

geographical databases prevents users and designers

to migrate their projects from a CASE tool to

another. Other major problem brought up by the lack

of standardization is the difficulty in training

designers, since although the models have been

produced for the same purpose; each one has its

differences and particularities. Users who are

familiar with a model (and its respective CASE tool)

show strong resistance to accept a new one.

The use of a UML profile will solve these

problems. Besides the wide UML acceptance by

software developers, the availability of CASE tools

with support for profiles rule out the need for

implementing specific tools for a particular model.

GEOPROFILE - UML Profile for Conceptual Modeling of Geographic Databases

411

Figure 2: GeoProfile Stereotypes.

A subject for future work is the logical-

conceptual transformation of schemas produced with

GeoProfile. The existence of logical standards, as

defined by OGC and the series ISO 19100, will have

a strong link with the level of conceptual modeling.

Finally, the great challenge is to make authors of the

existing conceptual models contribute to improve

the GeoProfile. Moreover, to know the opinion of

the users is important, because in many cases the

database of a GIS application is designed by then.

Thus, it is also important to measure the GeoProfile

use’s facility and its learning curve.

ACKNOWLEDGEMENTS

This project was partially funded by CAPES,

FAPEMIG and CNPq / MCT / CT-Info.

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