OpenStreetMap is one of the best examples of Volunteered Geographic Information. Its success relies on the ease of use and the freedom it provides. Users are supposed to geolocate their Points Of Interest and annotate them with a tag. There is no certain vocabulary or ontology of the tags that users have to commit to. The whole tagging process is done in a bottom-up manner in which the community on a wiki basis discusses this issue. Allowing users to use tags freely increases the usability of OpenStreetMap but at the same time causes semantic interoperability problems. What is needed, is a way to structure the tags while satisfying the freedom criterion. As a solution, we suggest the alignment of the tags to well structured top level ontologies. A middle layer approach for bridging the gap between the bottom-up tags of the users and the top level Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) is proposed. The idea of \games with a purpose" is utilized to assists non-expert users in aligning their tags to DOLCE.
User generated content is an important emerging research area. Engaging the
crowd in performing new tasks brings about new opportunities and new
challenges. In the geographic domain, the term Volunteered Geographic Information
(VGI) was coined by Goodchild [
OpenStreetMap o ers an open and easy to use platform that enables
contributors to upload geographic information collected from mobile devices or aerial
images. The data model is simple and consists of nodes, ways and relations.
Each mapped entity is accompanied with a tag. There is no formal ontology
or vocabulary of prede ned tags that have to be adopted by the users, because
as argued by Steve Coast, the founder of OpenStreetMap: \no individual could
design such an ontology that would be all-encompassing, and even if they could
start no two individuals would agree on it[
Tags that facilitate the annotation of Points of Interest (POIs) in OpenStreetMap come in key-value pairs 1 for instance, amenity=bar, natural=beach, landuse= forest. There is no standardized way on how users shall annotate their POIs neither on the naming level nor on which entities shall be tagged under a certain name.
On a wiki 2 and mailing list 3 basis, the community exchanges opinions about the tags proposing new tags or tags that should be abolished. The most common tags in use, can be looked up in Taginfo 4. The tags (or Map Features as found in the wiki) are listed in some kind of loose hierarchy.
Although the freedom and openness provided eases the tagging procedure, it
causes semantic interoperability problems. User generated content is
heterogeneous which leads to ambiguity, redundancy and inconsistency of the tags. As a
result, ndability of the correct tag for annotating a POI as well as information
searching and retrieval is ine ective, an issue that has already been described
for instance in [
What is needed, is the combination of this loose hierarchy with well
structured, organized, formalized top level ontologies and speci cally the alignment
of users' tags to concepts of a top level ontology. Top level ontologies can be seen
as a structured collection of semantic primitives or meta level concepts that are
used to further de ne domain concepts [
OpenStreetMap is open to non-expert users of geographic data and thus, the
tagging attitude is rather intuitive than based on scienti c methodologies and
knowledge. This calls for an alignment to a top level ontology, which
underlying design principles are prescribed by common sense. As has been argued by
its creators, the Descriptive Ontology for Linguistic and Cognitive Engineering
(DOLCE) [
Aligning the tags to the top level ontology in a top-down approach with the aid of knowledge engineers would have been accurate but time consuming. Concerning maintenance, the dynamical nature of OpenStreetMap with the option 1 We use true type fonts to refer to tags 2 http://wiki.openstreetmap.org/wiki/Map_Features, last accessed 27.07.2012 3 http://lists.openstreetmap.org/listinfo, last accessed 27.07.2012 4 http://taginfo.openstreetmap.org/tags, last accessed 27.07.2012 5 http://www.loa-cnr.it/ontologies/DUL.owl, last accessed 05.09.2012 of new tags being introduced or old removed, would demand the repetition of the alignment procedure very often which is resource ine cient.
Our research question is \How to nd a user friendly way to align the tags to top level ontologies?". We aim at de ning a methodology that will enable the bottom-up alignment of tags to top level ontologies.
For that, we propose the use of the well established idea of \games with a purpose" [34] applied to OpenStreetMap. Speci cally, we choose \question games", a certain type of \games with a purpose", for assisting users in aligning their tags to the concepts of the top level ontology. We use DOLCE Ultralite, an extension of DOLCE to align the tags to.
The contribution of this work is twofold: (a) it provides an analysis of the semantic inconsistencies that emerge from the current state of the tagging process in OpenStreetMap and (b) it proposes a way to combine top-down and bottom-up approaches by preserving the advantages of both that is, the freedom and easiness of the rst and the structure, organization of the latter. For that, a \question game" is designed. The main objective is to reuse existing methods in order gure out a methodology for overcoming the semantic inconsistencies of OpenStreetMap.
The remainder of the paper is organized as follows. Section 2 provides information on the related work. Section 3 investigates some semantic inconsistencies that were found in the OpenStreetMap tags. Section 4 describes the proposed methodology for aligning the tags to the top level ontology and Section 5 concludes the paper and discusses possible future directions. 2
With the increase of user involvement in the web and the rising amount of user generated content, tagging was introduced for annotating purposes. Flickr 6, del.icio.us 7, citeulike 8 and youtube 9 are just few examples where users added tags to describe their content.
The tagging behaviour has been examined in multifarious ways with several methods in order to understand the commonsense ground of user generated content. Thomas Vander Wal introduced the term folksonomy for describing this collaborative tagging [33]. Clustering methods have been used to investigate in a bottom-up manner kinds of tags people use in their annotations.
Ontology learning has substantially bene ted from these kind of studies as they unfolded the way people perceive and use di erent tags. As a result, ontologies can be designed more e ciently.
The need for combining well structured ontologies with hierarchically loose
folksonomies has already been acknowledged. Especially the problem of the
missing relations between tags in folksonomies has been addressed in [
Data mining techniques and ontologies are combined in [29] to make the semantics of the tags explicit. Tags are preprocessed, clustered and related to concepts in di erent ontologies. Swoogle 10 is used as a search engine for nding appropriate ontologies.
In [
Aligning folksonomies to domain ontologies is utilized in [
WordNet is used in [
Concerning OpenStreetMap, important research has been conducted in
analysing the tagging behaviour of users i.e. which the most edited entities are and
how they change over time [
The power of enriching OpenStreetMap with other sources has been
demonstrated in the LinkedGeoData project [
The problem of missing relatedness between geographic entities is addressed
in [
OSMonto13 has been developed as an OWL ontology of OpenStreetMap tags
[
owl, last accessed 27.07.2012
14 http://planning.do-roam.org/, last accessed 27.07.2012
the search capabilities not only to the POIs but also to the activities that can
be performed at a certain location [
Scheider et al. [26] argue for the need of more functional or a ordance oriented representation of OpenStreetMap tags. They underline the fact that the current tagging practise in OpenStreetMap is not e cient enough for representing the identity of the POIs. As they mention, tagging a cafeteria which is also open at night serving alcohol with amenity=cafe may exclude the alcoholserving functionality. They suggest that tags should be grounded in a ordances. Accompanying the tags with richer descriptions on the a ordances of the POIs, may harden the annotation process but will make the querying process more e cient. 3
Semantic Inconsistencies of OpenStreetMap Tagging
The freedom and easiness of assigning tags to POIs is a hallmark of the
success of OpenStreetMap. But, on the semantics of the tags, it leads to several
interoperability problems. As this tag collection is a result of a bottom-up user
generated e ort, it lacks some proper semantic structure. Especially the absence
of relations like the hypernymic relation which describe the is-a relation between
a concept and its genus and the meronymic relation that is the part-of relation
both acting \as the cement that links up concepts into knowledge structures"[
In contrast to geographic ontologies, vocabularies, taxonomies created by domain experts, the key-value pairs are organized in a loose way. Although there is some type of clustering or thematic grouping of the tags in the wiki, which di erentiates it from traditional folksonomies where hierarchical information is missing, conceptual inconsistencies still exist. This section aims at providing some examples of the semantic inconsistencies that arise from the tagging strategy of OpenStreetMap.
To start with, there is no common criterion according to which the tags are organized. As a result all keys are in the same hierarchical level. That is, all primary features as listed in the wiki i.e. amenity, aeroway, historic, landuse, manmade, craft, sport, tourism, power, shop etc. are treated equally, which results in conceptual vagueness and inconsistency. For instance, the nature of office or shop is manmade. By not relating these tags to the tag manmade with the class-subclass relation, important inheritance information gets lost. Same applies to i.e. shop, office, building which could be subclasses of amenity.
On a more sophisticated level, a disadvantage of the at structure of the tags is the fact that no deeper associations between geographic entities can be established. For instance, in the current tagging procedure there is no way of explicitly stating that within landuse=commercial, geographic entities like shop=bakery, office=architect are located.
Redundancies of tags provide us with evidence about the di erent conceptualizations of certain POIs that users have. For instance, hotel, hospital, school are tagged as tourism=hotel, building=hotel, amenity=hospital, building=hospital, amenity=school, building=school. Users assign the same value (be it hotel, hospital or school), to two di erent keys namely tourism and amenity.
Another nding is that tags related to activities are used to describe POIs i.e. sport=climbing, sport=basketball, leisure=dance, leisure=fishing. While describing the activity that can be performed at a certain POI, they are used to annotate the POI itself. This may be confusing in terms of information search as it perplexes the geographic entity with its function.
The primary tag amenity also creates confusion since it is used to represent a wide variety of heterogeneous features (e.g., schools, parking lots, bus stations, banks, hospitals, nightclubs, etc.). Although di erent subcategories of amenities are de ned in the wiki (such as sustenance, education, transportation, nancial, healthcare, etc.) to further classify di erent types of amenities, their possible values (such as school, bar, embassy, etc.) directly refer to the general tag amenity, e.g., amenity=school, amenity=bar, amenity=embassy.
The above cases are some examples of the semantic problems caused by a
bottom-up, intuitive approach. Furthermore, although the proposed tags have
resulted from consensus, they do not necessarily represent a common and wide
conceptualization of geographic concepts. For this reason, although such
approaches have stimulated considerable interest and resulted in the collection of
huge volumes of geospatial data, they are accompanied by problems, such as the
creation of arbitrary attributes or attribute values, multiple tags for the same
geographic features, disagreement on the name of features, etc. [
Question Game for Aligning OpenStreetMap Tags to
DOLCE Top Level Ontology
4.1 Introduction to the DOLCE Ultralite Top Level Ontology
DOLCE [
In the present work, the DOLCE Ultralite was chosen because its categories and organization is simpler and more intuitive than the other versions as argued by its authors. The top concept entity is categorized into abstract, event, information entity, object and quality. For the alignment, the class object and especially its subclasses physical and social object are of high interest. For further information on the ontology we point the reader to the related links. 15 http://wonderweb.semanticweb.org/, last accessed 27.07.2012 16 http://www.loa-cnr.it/ontologies/DLP397.owl, last accessed 05.09.2012 17 http://www.loa-cnr.it/ontologies/DUL.owl, last accessed 05.09.2012 4.2
\Games with a purpose" were introduced by Luis von Ahn [34] as a way to make use of the human computation for solving complicated tasks. As he argues, machine capabilities are limited in contrast to human reasoning capacities. As a result, there is a need for human involvement. The core idea is that this involvement be easy and motivating for users but at the same time e cient.
Two examples described by Luis von Ahn are the ESP game [35] where users
are labelling images in a simple web based game and the Peekaboom 18 game
for adding location information to the images. Further examples are the Listen
Game for the annotation of music [32] and the Phrase Detectives 19 game for
the annotation of text [
A detailed collection of di erent \games with a purpose" can be found in [31].
Also health sciences bene t from \games with a purpose". For instance, the game
Foldit was developed for engaging the crowd in protein unfolding [
In the context of the semantic web, \games with a purpose" are used for building ontologies such as the OntoGame [27]. Similarly to the annotation of images game, wikipedia articles are shown to users who have to evaluate the content of the text and summarize the content on a common way. A wider range of \games with a purpose" for the semantic web can be found in [28].
For ontology alignment, SpotTheLink was designed as a continuation of the OntoGame framework [30]. In this game, users are shown concepts and pictures from DBpedia and then have to agree on one concept from the PROTON 20 ontology.
\Question games" (also seen as \question driven games"), is a type of \games
with a purpose" rooted back to the 20q 21 game where the computer tries to
guess the concept that a player has in mind based on his/her answers to certain
questions. This rational has been successfully used in [
The current work, proposes the use of an interactive \question game" for aligning OpenStreetMap tags to the DOLCE Ultralite ontology. The main prerequisite is to hide the complexity of ontology from the users while designing a smart way to align the tags to it. It would have been of little bene t to directly confront users with concepts from the ontology like information object, designed artifact etc. and ask for the direct alignment of their tags to them. 18 www.peekaboom.org, last accessed 27.07.2012 19 http://www.phrasedetectives.org, last accessed 27.07.2012 20 http://proton.semanticweb.org/, last accessed 27.07.2012 21 20q.net/, last accessed 27.07.2012
The \question game" plays this mediation role between the tags of the nonexpert and the well structured and formalized ontology. In such a way, users' freedom of choosing tags is preserved. Anchoring the tags in the top level ontology is catalytic for knowledge sharing and tag reconciliation and disambiguation.
The \question game" is part of the annotation process and its strategy is as follows. Users who want to annotate a certain geographic feature, after deciding which tag they prefer, have to answer some questions in a simple user interface. These questions are simple and rather intuitive in order to be easily understood and quickly answered. Each ontology concept is represented by one question. Examples of these questions can be seen in Table 1.
1. Is it a (physical) object like a river or a stadium? 2. Is it a material, like sand or mud? 3. Is it a boundary of an area like an electoral division? 4. Does it imply some kind of action like swimming or dancing? 5. Can you observe and measure it? 6. Does it have a location? 7. ...
The questions refer to the values of the tags. By answering a question, the corresponding key of the tag is aligned as a class to the DOLCE Ultralite concept and the value of the tag as a subclass to the corresponding key. For the rst prototype only boolean answers (yes and no) will be required. When a positive answer is given, the tag is aligned to the DOLCE Ultralite concept related to the question. Negative answers, trigger new questions until a positive answer is given. Expected results of the alignment can be seen in Fig. 1.
As can be seen, the keys tourism, building, amenity, highway and leisure are aligned to the class Designed Artifact. That is, they are grouped according to their common criterion. As a result, their scattered listing in the OSM Features wiki is organized facilitating easier ndability of the tags and reference of their meaning.
The purpose of the game is to directly align the tags to concepts from the ontology. In this early stage, there is no interaction between users in order to agree on a common tag which is a common practise in games with a purpose. Moreover, the \question game" is not used in order to nd out whether tags are used correctly or how consistent they represent the POIs.
For motivating users, well known techniques such as ratings for top users
i.e. as seen in [25] or the geo-wiki project 22 are applied. This commonly used
technique is documented in [
Concerning the evaluation of the game possible options are usability test measuring the level of ease and fun of the game. Analysis of the aligned tags can 22 http://www.geo-wiki.org/login.php?menu=home, last accessed 27.07.2012 show agreement or disagreement between users i.e. for the same tag what kind of answers users provide and to which alignment it leads. Results can then be evaluated with the aid of domain experts.
By introducing the \question game" for the alignment process, a solution is found that allows users to keep the freedom of choice for their tags while at the same time it enables the anchoring of them in the top level ontology. 5
In this paper we have shown a way to bridge the gap between top-down ontological and bottom-up crowdsourcing practices. OpenStreetMap is chosen as a representative, widely used example of VGI. Although the freedom of assigning tags to OpenStreetMap is very appealing and encouraging for users to contribute their geodata, it humbles information search and retrieval. The community tries to stabilize a common agreement on tags and an appropriate way that they be used; however a proper order is missing. As a result, implicit knowledge (i.e. inherent characteristics between classes and subclasses) cannot be unfolded.
The need for ordering the OpenStreetMap tags and constraining their meaning, was ful lled with the alignment of the tags to the DOLCE Ultralite top level ontology. DOLCE Ultralite has a cognitive and linguistic orientation and was therefore preferable to other top level ontologies. A bottom-up method is used for the alignment process preserving the open and dynamic character of OpenStreetMap.
With the aid of a \question game", users are guided to align their tags to DOLCE concepts. Keys and values of OpenStreetMap are translated into classes and subclasses respectively and then anchored. Users are neither confronted with the concepts of DOLCE Ultralite nor the DOLCE Ultralite hierarchy so that the simple and common tagging procedure is maintained.
Opportunities for future work comprise the use of sophisticated reasoning mechanisms to derive the implicit knowledge from the alignment result. Especially the analysis of inconsistencies between tags would provide evidence about which geographic entities are perceived and used di erently among the users. For instance, if the alignment results show that the same tag is anchored in different DOLCE Ultralite concepts it can be inferred that the geographic entity it describes, is conceptualized in heterogeneous ways by each user.
With additional analysis of these ndings, new knowledge could be derived. On a higher generalization level, this would be a way to derive a better understanding of how users conceptualize geographic entities providing insights to spatial cognition.
Given the fact that OpenStreetMap is a multilingual project one research question to be further investigated, would be whether tags in di erent languages are aligned to the same DOLCE Ultralite concept or not. Such an analysis could assist in investigating if there are di erences in the conceptualization of the same POI in di erent cultures.
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