Place Name Ambiguities in Urban Planning Domain Ontology
Yi-Pei Liao
and Feng-Tyan Lin
Department of Urban Planning, National Cheng Kung University, Tainan, Taiwan
College of International and Cross-Strait Education, Asia University, Taichung, Taiwan
Keywords: Urban Planning Domain Ontology, Spatial Ontology, Place Name Ambiguity.
Abstract: Integrating spatial information is a crucial step in construction of Urban Planning Domain Ontology
(UPDO), and taking spatial information from the web as the input of self-learning method are commonly
used in constructing ontology. In this case, the use of place names could be important indicators of
understanding the spatial information on the web. However, place names expressed in natural language
bring diverse ambiguities, which would bring great challenges to several research fields such as Geographic
Information System (GIS) and Geographic Information Retrieval (GIR). GIR has more contribution on
place name ambiguities than GIS. Nevertheless, from the perspective of the urban planning domain, it is still
lacking in application. This paper is a position paper that aims to bring out an argument of place name
ambiguities in UPDO, and introduce two kinds of ambiguity frequently appearing in the urban planning
domain. The paper also proposes a hierarchical structure of spatial ontology that allows constructors to deal
with ambiguities. We believe in that the ambiguity issue is critical for urban planning, and the argument is
worth discussing to all relevant domains.
In construction of Urban Planning Domain Ontology
(UPDO), the integration of geographic information
undoubtedly is an important task. In practice, UPDO
needs spatial information rather than geographic
information as spatial information involves
connections of locations, people, and activities (Lin
et al., 2013). In view of that, place names could play
an important role in integrating spatial information
especially when ontology constructors need to
retrieve spatial information from the web. However,
more and more place names have been created
rapidly and informally through various internet
activities, for instance, tagging function on
community websites. Matching a place name to a
real space therefore turns more ambiguous than
before as a place name is more likely to become a
vague concept instead of a geographic information.
Moreover, some of conceptual place names are
widely used in formal documents, such as press
releases and formal governmental reports. This
brings out a new challenge for UPDO to deal with
the ambiguity.
In fact, place name ambiguities are not a new
issue. The research field of Geographic Information
System (GIS) has studied on this question since the
1990s, and so did the field of Geographic
Information Retrieval (GIR), a technique combining
the information retrieval and spatial ontology. GIR
has contributed to derive the geographic information
from web documents automatically, as a result,
recognizing the place names from natural language
is one of the great challenges in GIR. Nevertheless,
the existing disambiguating technique in urban
planning domain remains insufficient. More efforts
are needed to be put for solving place names
ambiguities while constructing UPDO which is
grounded on robust spatial ontology.
This paper is a position paper bringing out an
argument over place name ambiguities. It presents
two kinds of ambiguity that are commonly seen in
urban planning domain, yet have not been taken into
consideration in GIR. In addition, it proposes a new
hierarchical structure of spatial ontology which is
able to deal with the ambiguity. The paper is
organized as follows. Section 2 will review works
with regards to place ambiguities in GIS and GIR.
Section 3 introduces two kinds of place name
ambiguity that have not been dealt adequately in
terms of urban planning practices. Section 4 brings
out a new structure of spatial ontology which
considers the place name ambiguity discussed in
Liao, Y. and Lin, F..
Place Name Ambiguities in Urban Planning Domain Ontology.
In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - Volume 2: KEOD, pages 429-434
ISBN: 978-989-758-158-8
2015 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
Section 3, and proposes a brief outline for
proceeding to construct the spatial ontology. Finally,
conclusion is given in Section 5.
In the following are reviews of works regarding
place name ambiguities. The first part will firstly
focus on the field of GIS, and then shift the focus to
the spatial ontology and GIR.
2.1 Place Ambiguities in GIS
Name of place is a basic attribute of location
information in common spatial database,
accompanied with other basic attributes like latitude,
longitude, altitude, coordinates, area, etc. Most of
spatial databases advocate an entity-oriented view of
space, which means that the space data which could
be in the form of a point, a line, or an region is an
exact object. Some difficulties are discovered when
it comes to defining an area with indeterminate
boundaries (Burrough and Frank, 1996; Wang and
Hall, 1996). One of difficulties is a vague region or
fuzzy spatial data types (Erwig and Schneider, 1997;
Schneider, 2008). Fortunately, many researches and
tools have advanced in dealing with the problem of
indeterminate boundaries and vague regions.
Fuzzy region problem has been handled in GIS,
however, the spatial data representing through the
open-data and internet platform is still based on the
traditional view of space, for example, Google Map
and Open Street Map (OSM). Furthermore, many
map tools commonly used by users and netizens
display the place data through a standard format,
such as KML or GML, yet the simplicity will bring
difficulties in recognizing the place from expression.
2.2 Place Ambiguity in Spatial
Ontology and GIR
Despite of the advancement in GIS, spatial ontology
development and knowledge management in dealing
the ambiguity problem remains in a primary state.
Numerous works have put efforts on constructing
ontology, but few of them have focused on the time
and space dimension of thematic ontology. Peuquet
(2001) worked on an ontology framework which
could derive effectively the what/when/where
information with robust space-time data structure.
Also, he developed the query language, the
operation, and the users interface. Perry et al. (2006)
drew an outline of basic classes and relationships for
a spatial upper-ontology, which brought spatial
dimension into other ontology and allowed spatial
query operation.
The technique of Geographic Information
Retrieval (GIR) has focused on the spatial relations
between any kinds of knowledge, where information
is described with geographic metadata. GIR is user-
oriented applications including spatial query, search
and display functions. For example, the Spatially-
Aware Information Retrieval on the Internet
(SPIRIT) (Jones et al., 2002; Jones et al., 2004) is a
search engine for geographic information. SPIRIT
advocates that most of the web resources refer to
geographic space, which means that the event was
recorded once when it reveals or happens in a certain
place. SPIRIT regards each entity as a geography
entity with geographic information. In the part of
query method, SPIRIT intelligently understands the
users’ searching language and tells any possible
event that has relation with geographic information.
Mata and Claramunt (2011) rested on the
contribution of SPIRIT and gave an approach for
retrieval of geographic entities according to its
spatial, temporal, and thematic information. The
approach extracted diverse dimension of information
from the gazetteer, which has its own XML format
of geographical entity (eg. Wikipedia).
Several challenges in GIR demand further
significant researches (Jones and Purves, 2008),
including (1) detecting geographic reference in the
form of place names and spatial natural language, (2)
disambiguating the place names, (3) indexing
documents respecting to their geographic context, (4)
ranking relevant documents with respect to
geography as well as theme, (5) developing effective
user interfaces, and (6) developing methods to
evaluate the success of GIR. The research
introducing in this paper focuses on the first two
challenges, the place names detecting and place
names disambiguating. This research also faces
another difficult but critical challenge of the
language characteristics in Chinese.
In summary, GIS and GIR are both very
fundamental tools in the domain of urban planning.
In GIS, there is advancement in representing places
even though data might be either specific or vague.
The problem of vague region is much like a
semantic problem of space, and ontology is
considered as a major method to deal with the
semantic problem. However, it is still in a primary
stage in terms of spatial ontology and GIR.
KEOD 2015 - 7th International Conference on Knowledge Engineering and Ontology Development
The nature language problem in different languages
is important to GIR, and the place name ambiguities
is one of top priorities needed to be dealt with, and a
lot of researches have put efforts on it. Nevertheless,
only a few of place names ambiguity researches
have dealt with the problem that would happen in
using Chinese language. Chinese characters,
different from English word, is defined separately by
intrinsic meaning rather than by visible space,
resulting in that a character cannot be recognized by
a normal pattern. Furthermore, in Chinese the
meaning of a character could become very different
when combining with other characters. Thus,
defining a character and a term is a critical task in
Chinese as its meanings are strongly dependant on
the grammar analysis system. The follows are going
to introduce two kinds of Chinese place name
ambiguity that often appear in urban planning
3.1 The Place Name as a Concept of
Spatial Distribution
A planner may need to query for location
information of specific spatial events, such as
“flooding area” and “potential flooding area”. In this
case, there are at least two ambiguity problems that
make “flooding area” unable to be identified: (1)
how can the character “flooding” be recognized as a
part of a place name? It is more likely to be
identified as an adjective. How to distinguish an
adjective for a place name from an adjective in
normal would then become a problem. (2) The term
“flooding area” refers to a concept of geographic
distribution instead of a certain location. However,
according to the assumptions of normal GIR, there
could be only one focusing place in a single place
name entity, hence “flooding area” is unrecognized
because it is a description of a spatial event in name
yet without a continuous distribution in space.
3.2 The Place Name as a Concept of
Social Phenomenon in Space
Another place name ambiguity is caused by
conceptualized social phenomena. This kind of place
names could be a proper noun individually that is
easy to be recognized by pattern. Nevertheless, it
also has a very fuzzy boundary or even has no
boundaries on a map. The reason is that these place
names are created for describing particular social
development phenomena such as poverty gap and
real estate. In other words, the phrases have been
named before being indicated in space. In addition,
these place names could be unprofessionally defined
as they may be created by the public, especially the
One of typical examples for this type of
ambiguity is a compound term called “Tyan-Long
Nation”, which is firstly created by some netizens
and is now frequently used by news media in
Taiwan. “Tyan-Long Nation” has an ironic meaning
initially that indicates a place where its residents are
self-centered and ignorant about anything happened
in other places. Yet nowadays the meaning has
evolved into a phrase describing a place with high
commodity price and extreme high housing price.
Moreover, verbally “Tyan-Long Nation” refers to
the Taipei City, the capital of Taiwan, however, they
are not exactly matched geographically.
In planning domain ontology, it is necessary to
understand this type of place names. Remind that it
is probably hard to find “Tyan-Long Nation” on the
Google Map because it is a phrase for a specific
concept rather than a location. Furthermore, it is a
name created by the public rather than by the official.
Therefore, in order to reveal the fuzzy boundary of
“Tyan-Long Nation”, we collect all locations with a
name “Tyan-Long Nation” from the Facebook
places, in which locations are allowed to be created
by all users, and check how much Facebook users
have checked in at each location. The more the
location has been checked, the higher score as well
as the possibility is assigned to the location. Figure 1
shows the result of this survey. The boldest black
line is the boundary of Taipei City, and the grey
circles are all locations that are named with “Tyan-
Long Nation” each circle has the radius about 1.2
km, and with shade degree base on the number of
Figure 1: A map displays the “Tyan-Long Nation
according to the mass Facebook users.
Place Name Ambiguities in Urban Planning Domain Ontology
checked users. Figure 1 clearly reveals that “Tyan-
Long Nation” is concerned with some places in
Taipei City but not all. In this survey, the place
name was created basing on the social phenomenon
with a vague region, and we display the region on a
map according to the diverse understandings of mass
Facebook users.
In order to develop a spatial ontology for urban
planning GIR and UPDO, we need a new structure
of spatial ontology that is able to handle the
ambiguity problems identified in Section 3. In the
following part will firstly introduce the source of
place names, then a new structure for spatial
ontology, and finally a framework of semi-automatic
construction of this spatial ontology.
4.1 Place Names from Facebook
Facebook is the major sources of place name
collection in this research. The contents are
generated from the users’ perspectives, thus how to
take these informal contents into scientific and
theoretical research becomes a critical point, which
could be a very fundamental question. In the case of
collecting place names from Facebook, it’s obvious
that not every check-in name could be regarded as a
place name, and in contrary, it’s also expected that
some informal check-in name should be identified as
a place name. The critical and fundamental question
is “what is a place name?”
Cresswell (1996) aimed that the concept of place
should be scrutinized to both geography and human
everyday life. A place name is created only when the
place have some relations with some human
activities. In the domain of urban planning, the
rethinking of the relation between space, human, and
symbols (names) is quite associated to the concept
of “City image,” which was brought out by Lynch
(1960). City image argues that a city’s space is not
defined by its structure design but by the feeling of
the people living in it. City image is a mental map of
a person, and it might be very different to each
person even though they are experiencing in the
same city. Based on the concepts above, it’s
interesting to look through the Facebook place
names and analysis the reason of why the name is
created, is it related to “what people feel about the
place?” or “what people do at the place?”
Figure 2 shows the procedure of Facebook place
names Extraction. There are four parts between the
extraction from web and the storing to database: (1)
API is a tool to collect data from Facebook by using
the Graph API. So far there are about 10,000 place
names in Taiwan have already collected from
Facebook. The metadata has 10 items: name,
category, street, city, state, country, zip, latitude,
longitude, and check-in. The check-in is the count
number of users who checked in with that place
name. (2) Potential place name extraction is working
on analysing the name and deciding whether it is
possible place name or not. There are several kinds
of situation that make the name none potential, for
example, there’s a name called “on a moving train”
or “car racing.” None potential place names are
regarded as unidentifiable names which will leave to
(3) place name re-identification process. In this
process, several algorithms are developed for
different unidentified situations. (4) Place name
formalization is the last step before storage.
Formalization will deal the structural ambiguity
problems, such as shortened names and alternated
names. It’s based on the previous work by Deng et al.
(2012), which has developed an algorithm to extract
Chinese place name by using natural language
processing (NLP) method.
Figure 2: The procedure of Facebook place name
4.2 A Structure of Spatial Ontology
An ontology-based model is utilized in the new
defined spatial ontology. Figure 3 shows the UML
class diagram of the hierarchical spatial ontology,
which allows the situations mentioned in Section 3.
The place is divided into three levels. The place
class at the first level refers to a general concept.
Following the place class, normal place and
distribution area, stand at the second level. The
normal place bases on the prototype and algorithm
in previous research of GIR. The distribution area is
separated in two sub-categories, namely, spatial
event and social event, which are both learned from
KEOD 2015 - 7th International Conference on Knowledge Engineering and Ontology Development
UPDO. The distribution area could have
distribution rate relations with several normal
places, where each distribution rate describes the
frequency of the distribution area has distributed in
that normal place. The distribution rate relation has
a value Di, 0in, where n is the number of total
normal place that have distribution rate relations
with that distribution area.
Figure 3: The class diagram of spatial ontology.
Figure 4: Instance diagrams of two kinds of distribution
area, where “flooding area” is a spatial event and “Tyan-
Long Nation” is a social event.
Figure 4 are instance diagrams of two examples
mentioned in Section 3.1 and 3.2. The “flooding area”
is a spatial event and “Tyan-Long Nation” is a social
event, yet both of them are belong to distribution
area. “Flooding area” distributed in “Yunlin”,
“Chiayi”, “Tainan”, “Kaohsiung”, and “Pingtung”,
while “Tyan-Long Nation” is dispersed to “Taipei
City”, “New Taipei City”, “Xinyi District”, “Da’an
District”, and “Shilin District”. The distribution
relations are recorded respectively as symbols D
. These distribution rate values can be calculated
by spatial analysis methods such as proportion of
area, or by textual analysis methods such as co-
occurrence rate, or by integrating the former two
4.3 Semi-automatic Spatial Ontology
Based on the class hierarchy of place in Figure 3, we
construct a spatial ontology with three parts, the
normal place database, the distribution area database,
and the distribution relations database. Figure 5 is
an outline of semi-automatic construction procedure
of spatial ontology, in which the rectangle with bold
dotted line describes the spatial ontology.
Figure 5: Semi-automatic spatial ontology construction
framework in UPDO.
Figure 5 shows the procedure of semi-
automatically constructing spatial ontology, and
there are three points worth being mentioning: (1) A
Chinese grammar analysis tool called CKIP,
developed by Academia Sinica in Taiwan, would
fragment terms into sub-terms according to their part
of speech (Ma and Chen, 2003). CKIP involves in
the process of determining the category of place
from the first level to the second level. (2) The
existing UPDO is able to assist in identifying any
relevant spatial or social event that are embedded in
the place name, and thus would help to decide the
category of distribution area from the second level to
the third level of spatial ontology. (3) The
distribution rate is calculated according to both
spatial analysis and textual analysis methods.
This paper is a position paper that brings out an
Place Name Ambiguities in Urban Planning Domain Ontology
argument of place name ambiguities. Although some
ambiguities have been taken into account in GIS and
GIR researches, the domain of urban planning,
which especially needs to integrate all knowledge
existing in a particular space, still lacks for the
consideration. Two types of ambiguities in Section 3
are the evidences indicating a wide gap between the
place name and the physical space. We also propose
a new defined structure of spatial ontology that will
be utilized in UPDO in further researches. The
spatial ontology presented in Section 4 is a
fundamental framework for urban planning GIR and
UPDO. We believe that the contribution of this
research in further can serve in several tasks such as
Decision Support System (DSS), knowledge
understanding, and the automatic learning of
relevant domain ontology.
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