Identifying semantically similar elements in heterogeneous spatial databases using predicate logic expressions
Stock, K.M. and Pullar, D. (1999). Identifying Semantically Similar Elements in Heterogeneous Spatial Databases using Predicate Logic Expressions. In Andrej Vckovski, Kurt E. Brassel and Hans-Jorg Schek (eds), Interoperating Geographic Information Systems: Second International Conference, INTEROP '99, Zurich, Switzerland, 1999 Proceedings. Lecture Notes in Computer Science 1580, Springer, Berlin.
For data to be successfully integrated, semantically similar database elements must be identified as candidates for... more
For data to be successfully integrated, semantically similar database elements must be identified as candidates for merging. However, there may be significant differences
between the concepts that participants in the integration exercise hold for the same real world entity. A possible method for identifying semantically similar elements prior to
integration is based on cognitive science theory of concept attainment. The theory identifies inclusion rules as being the basis for the highest level of concept attainment, once concepts
have been attained at lower, perceptive levels. Predicates can be used to combine inclusion rules as a basis for semantic representation of elements. The predicates for different
database elements can then be compared to determine the similarities and differences between the elements. This information can be used to develop a set of semantically similar
elements, and then to resolve representational conflicts between the elements prior to integration.
OGC catalogue servicesOWL application profile of CSW
Stock, Kristin (2009) OWL Application Profile for CSW 2.0. Open Geospatial Consortium Application Profile 09-010.
Determining Semantic Similarity of Behaviour Using Natural Semantic Metalanguage to Match User Objectives to Available Web Services
Stock, Kristin (2008). Determining Semantic Similarity of Behaviour Using Natural Semantic Metalanguage to Match User Objectives to Available Web Services. Transactions in GIS, 12(6), 733-755.
Natural Semantic Metalanguage specifies a set of semantic primitives identified by linguists since the 1970s as being... more Natural Semantic Metalanguage specifies a set of semantic primitives identified by linguists since the 1970s as being present in all analysed languages and not capable of further reduction. In this article, the 63 semantic primitives are used to define the semantics of user objectives and web services in the form of semantic explications, which are then compared to determine whether the web services are likely to be helpful in meeting the user objective. The comparison of the user objectives and web services is a two stage process. Firstly, the content is compared by classifying the semantic primitives from the candidate web service and user objective on the basis of whether the primitives are common or similar. On the basis of these classifications, the percentage match and semantic relationship (subset, superset, overlaps, disjoint, identical) are determined. Secondly, the order of the semantic primitives is compared and the edit distance determined as a measure of semantic similarity. The method is tested using two examples: a comparison of spatial relations and a comparison of a user objective and three geospatial web services. The results show that the method is able to determine which concepts are broadly semantically similar and which are not.
The Representation of Geographic Object Semantics Using Inclusion Rules
Stock, K.M. (1998). The Representation of Geographic Object Semantics Using Inclusion Rules. Paper presented at GIS/LIS 98 Annual Conference and Exposition held at Fort Worth, Texas, 8-12 November 1998.
A number of attempts have been made to provide standard terms or definitions for real world entities to aid in data
sharing. However, the information communities model of the OpenGIS Consortium recognizes that individual user
groups will have their own set of definitions and language, and that translations between these will be necessary
(OpenGIS Consortium, 1996). In order for translations to be successful, a method for capturing the semantics of
database elements is required. Simple definitions have been shown to be inadequate (Mark, 1993; Kuhn, 1994).
An alternative method for the representation of element semantics uses inclusion rules, and is based on psychological
theory of concept attainment, and particularly on a model proposed by Klausmeier, Ghatala and Frayer (1974). The
method identifies inclusion rules as being the basis for concept attainment, and combines these rules into predicates
to represent element semantics. The method allows cross referencing between predicates that define element
semantics, so reduces reliance on the expression style of individual participants in the data sharing activity.
In addition to providing a method for representation of element semantics, the inclusion rules method allows the
relationships between element semantics to be determined. This determination is necessary in order for semantic
translation to occur.
An example using topographic elements indicates that rules can be defined and predicates formed to represent
element semantics with limited dependence on individual expression. The example then shows that predicates can
be used to translate element semantics to allow data sharing between heterogeneous communities.
Describing Spatial Relations using Informal Semantics
Stock, Kristin (2010) Describing Spatial Relations Using Informal Semantics. Extended abstract, presented at GIS Research UK (GISRUK 2010), 14-16 April, London, UK.
An Approach to the Management of Multiple Aligned Multilingual Ontologies for a Geospatial Earth Observation System
Stock, K. and Cialone, C. (2011). An Approach to the Management of Multiple Aligned Multilingual Ontologies for a Geospatial Earth Observation System. Presented at GeoS 2011: Fourth International Conference on Geospatial Semantics, Brest, France, 12-13 May 2011. Lecture Notes in Computer Science (LNCS) 6631.
Ontologies are widely used, within and outside the geospatial context to support semantic search that is capable of... more Ontologies are widely used, within and outside the geospatial context to support semantic search that is capable of returning suitable resources. Some large, heterogeneous earth observation systems that are currently being developed in a multi-thematic environment require the support of multiple ontologies. Furthermore, some of the systems under current development operate in a multi-lingual environment, and it is desirable that multiple languages be supported by the systems themselves. This paper proposes a solution to this set of requirements using an architecture containing multiple and multilingual ontologies. Such ontologies are required to be related and the architecture described in this work, which adopts a spatial data infrastructure based on open geospatial standards, employs an algorithm for semantic search across the multiple multilingual ontologies aligned using the W3C Simple Knowledge Organization System (SKOS). It also provides an approach that is extendable by the addition of further ontologies if they are required for particular thematic purposes. A number of issues arose during phases of implementation, but the broad approach proved effective for supporting a large, heterogeneous, multilingual earth observation system.
The Semantic Management of Environmental Resources within the Interoperable Context of the EuroGEOSS: Alignment of GEMET and the GEOSS SBAs
Cialone, C. and Stock, K. (2010). The Semantic Management of Environmental Resources within the Interoperable Context of the EuroGEOSS: Alignment of GEMET and the GEOSS SBAs, EGU General Assembly 2010, held 2-7 May, 2010 in Vienna, Austria, p.12133
Heterogeneous Databases-Identifying Semantically Similar Elements in Heterogeneous Spatial Databases Using Predicate Logic Expressions
Stock, K.M. and Pullar, D. (1999). Identifying Semantically Similar Elements in Heterogeneous Spatial Databases using Predicate Logic Expressions. In Andrej Vckovski, Kurt E. Brassel and Hans-Jorg Schek (eds), Interoperating Geographic Information Systems: Second International Conference, INTEROP '99, Zurich, Switzerland, 1999 Proceedings. Lecture Notes in Computer Science 1580, Springer, Berlin.
For data to be successfully integrated, semantically similar database elements must be
identified as candidates... more
For data to be successfully integrated, semantically similar database elements must be
identified as candidates for merging. However, there may be significant differences
between the concepts that participants in the integration exercise hold for the same real
world entity. A possible method for identifying semantically similar elements prior to
integration is based on cognitive science theory of concept attainment. The theory identifies
inclusion rules as being the basis for the highest level of concept attainment, once concepts
have been attained at lower, perceptive levels. Predicates can be used to combine inclusion
rules as a basis for semantic representation of elements. The predicates for different
database elements can then be compared to determine the similarities and differences
between the elements. This information can be used to develop a set of semantically similar
elements, and then to resolve representational conflicts between the elements prior to
integration.
Determining Semantic Equivalence between User Objectives and Implemented Web Services
Stock, Kristin (2007). Determining Semantic Equivalence between User Objectives and Implemented Web Services. Extended abstract. Presented at the Workshop on Semantic Similarity Measurement and Geospatial Applications, Conference on Spatial Information Theory, Melbourne, 19-23 September, 2007.
Ontology-Based Geospatial Approaches for Semantic Awareness in Earth Observation Systems
Stock, K., Hobona, G., Granell, C. and Jackson, M. (2011). Ontology-Based Geospatial Approaches for Semantic Awareness in Earth Observation Systems. In Geospatial Semantics and the Semantic Web: Foundations, Algorithms and Applications, Naveen Ashish and Amit P. Sheth (eds). Semantic Web and Beyond, Volume 12, Springer.
Current work towards making earth observation systems semantically aware attempts to improve user experience by... more Current work towards making earth observation systems semantically aware attempts to improve user experience by allowing more flexibility in the way that users interact with earth observation systems. Such improvements may occur directly by making data discovery more semantically-flexible, and indirectly in providing intelligent functionality that removes some of the load from users in interpretation of data and processes. Semantic awareness in earth observation systems may be addressed from four different angles: semantics and information modelling; semantic data management; semantic data discovery and semantic data processing. Each of these areas is the subject of ongoing and developing research in the broader geospatial community, has been applied in a number of different situations and systems, and presents particular challenges for earth observation systems. The Global Earth Observation System of Systems (GEOSS) is a large, global, heterogeneous earth observation system and provides a case study of the use of different methods for achieving semantic awareness in each of these four areas. Furthermore, an example architecture for an earth observation system that involves multiple aligned ontologies illustrates the challenges posed by real world, heterogeneous systems. In combination, the review of related work, applications and challenges in each of the four areas, together with the GEOSS case study and example architecture provide an indication of the state of the art in semantic research as it applies to earth observation system. Furthermore, this summary provides a hint towards the future for semantics in earth observation systems and the need for additional work in this area.
To Ontologise or Not To Ontologise: An Information Model for a Geospatial Knowledge Infrastructure
Stock, K., Reitsma, F., Ou, Y., Bishr, M., Ortmann, J., Stojanovic, T. and Robertson, A. (forthcoming). To Ontologise or Not to Ontologise: Foundations for an Ontology-Registry for a Geospatial Knowledge Infrastructure. Computers and Geosciences.
A geospatial knowledge infrastructure consists of a set of interoperable components,
including software,... more
A geospatial knowledge infrastructure consists of a set of interoperable components,
including software, information, hardware, procedures and standards, that work together
to support advanced discovery and access to geoscientific resources, including
publications, data sets and web services. Such advanced discovery is intended to support
scientists in finding resources that meet their needs, and focuses on representing the
semantic details of the scientific resources, including the detailed aspects of the science
that led to the resource being created.
This paper describes an information model for a geospatial knowledge infrastructure that
uses ontologies to represent these semantic details, including knowledge about domain
concepts, the scientific elements of the resource (analysis methods, theories, scientific
processes) and web services. This semantic information can be used to enable more
intelligent search over scientific resources, and to support new ways to infer and visualise scientific knowledge.
The work describes the requirements for semantic support of a knowledge infrastructure,
and analyses the different options for information storage based on the twin goals of
semantic richness and syntactic interoperability to allow communication between
different infrastructures. Such interoperability is achieved by the use of open standards,
and the architecture of the knowledge infrastructure adopts such standards, particularly
from the geospatial community. The paper then describes an information model that
uses a range of different types of ontologies, explaining those ontologies and their
content. The information model was successfully implemented in a working geospatial
knowledge infrastructure, but the evaluation identified some issues in creating the
ontologies.
Semantically-Aware Automated Spatial Analysis for Natural, Humanitarian and Epidemiological Crises
Stock, Kristin (2007). Semantically-Aware Spatio-Temporal Data Analysis for Humanitarian and Natural Crisis Management. Presentation at the eScience Institute, 31 May 2007, Edinburgh, UK.
To Ontologise or Not To Ontologise: An Information Model for a Geospatial Knowledge Infrastructure
Stock, K., Reitsma, F., Ou, Y., Bishr, M., Ortmann, J., Stojanovic, T. and Robertson, A. (forthcoming). To Ontologise or Not to Ontologise: Foundations for an Ontology-Registry for a Geospatial Knowledge Infrastructure. Computers and Geosciences.
A geospatial knowledge infrastructure consists of a set of interoperable components,
including software,... more
A geospatial knowledge infrastructure consists of a set of interoperable components,
including software, information, hardware, procedures and standards, that work together
to support advanced discovery and access to geoscientific resources, including
publications, data sets and web services. Such advanced discovery is intended to support
scientists in finding resources that meet their needs, and focuses on representing the
semantic details of the scientific resources, including the detailed aspects of the science
that led to the resource being created.
This paper describes an information model for a geospatial knowledge infrastructure that
uses ontologies to represent these semantic details, including knowledge about domain
concepts, the scientific elements of the resource (analysis methods, theories, scientific
processes) and web services. This semantic information can be used to enable more
intelligent search over scientific resources, and to support new ways to infer and visualise scientific knowledge.
The work describes the requirements for semantic support of a knowledge infrastructure,
and analyses the different options for information storage based on the twin goals of
semantic richness and syntactic interoperability to allow communication between
different infrastructures. Such interoperability is achieved by the use of open standards,
and the architecture of the knowledge infrastructure adopts such standards, particularly
from the geospatial community. The paper then describes an information model that
uses a range of different types of ontologies, explaining those ontologies and their
content. The information model was successfully implemented in a working geospatial
knowledge infrastructure, but the evaluation identified some issues in creating the
ontologies.
Representing OGC Geospatial Web Services in OWL-S Web Service Ontologies
Stock, K., Robertson, A., and Small, M. (forthcoming). Representing OGC Geospatial Web Services in OWL-S Web Service Ontologies. Submitted.
OWL-S is an ontology for describing web services in a way that includes the
semantics (meaning) of the web... more
OWL-S is an ontology for describing web services in a way that includes the
semantics (meaning) of the web service, including the semantics of its behaviour
and the semantics of the static information objects with which it interacts. OWLS
has not been widely used to describe geospatial web services, most of which
conform to specifications of the Open Geospatial Consortium (OGC).
This paper describes an approach to the description of OGC web services using
OWL-S that takes advantage of the generic OGC specifications to reduce the
amount of work involved in creating web service ontologies for OGC web
services, and that uses the GetCapabilities document that is provided for all OGC
web services.
The approach defines an OWL-S OGC web service ontology that describes the
OGC web service specifications (specifically in this case Web Map Service and
Web Feature Service), and then shows how a web service ontology may be
created by creating instances of the OWL-S OGC ontology and the contents of
the GetCapabilities document, thereby reducing the effort involved in creating
web service ontologies for OGC web services.
Developing Feature Types and Related Catalogues for the Marine Community – Lessons from the MOTIIVE Project.
Millard, K., Woolf, A., Stock, K., Longhorn, R., Higgins, C., Small, M., Hulst, S., Hamre, T., Ferreira, M., Lucius, I., Breger, P., Pepper, J., Lowe, D., Harphen, Q. and Wells, S. (2007). Developing Feature Types and Related Catalogues for the Marine Community – Lessons from the MOTIIVE Project. International Journal of Spatial Data Infrastructure Research, 2, 132-162.
MOTIIVE (Marine Overlays on Topography for annex II Valuation and
Exploitation) is a project funded as a Specific... more
MOTIIVE (Marine Overlays on Topography for annex II Valuation and
Exploitation) is a project funded as a Specific Support Action (SSA) under the
European Commission Framework Programme 6 (FP6) Aeronautics and Space
Programme. The project started in September 2005 and finished in October
2007. The objective of MOTIIVE was to examine the methodology and cost
benefit of using non-proprietary data standards for data exchange amongst and
between different communities as defined by the INSPIRE data theme annexes.
Specifically it embraced the harmonisation requirements between the INSPIRE
Annex II data theme ‘elevation’ (terrestrial, bathymetric and coastal) and
INSPIRE Annex III marine thematic data for ‘sea regions’, ‘oceanic spatial
features’ and ‘coastal zone management areas’. This was examined in context
of the requirements for interoperable information systems as required to realise
the objectives of GMES (Global Monitoring for Environmental Security) for ‘global
services’. The work draws particular conclusions on the realisation of Feature
Types (ISO 19109) and Feature Type Catalogues (ISO 19110) in this respect.
More information on MOTIIVE can be found at www.motiive.net
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Seen by: A web-based interview platform with geospatially prompted recalls for GPS household travel survey
by Minhe Ji
Co-authored with Wen Chen
Low data quality and heavy survey burden are standing issues in questionnaire-based household travel surveys (HTS).... more Low data quality and heavy survey burden are standing issues in questionnaire-based household travel surveys (HTS). The proliferation of GPS and Internet-based geospatial technology provides great potential for innovation. This paper presents a web-based, geospatially prompted recall interview platform for GPS-based household travel survey. It made use of geospatial orientation and objects from Google Map as visual and semantic cues to prompt respondents’ recall of travel experiences. The realized system functionality includes end-user self-administrated passive GPS survey data uploading, web server database management for GPS and trip data, automated GPS data noise removal, trip/stop candidate extraction, and GPS trajectory simplification, as well as annotated trip visualization and playback animation. Several essential tools for trip editing and attribute updates are provided in a logical and user-friendly manner. This approach was tested in Shanghai, a metropolitan setting of dense population, heavy inner-city traffic, and cement forests. The preliminary results indicated that the Internet map-based interface offered a great deal of heuristics to improve trip recall accuracy, while the backstage data mining algorithms was able to tolerate greater errors in trip recall and attribution from the user. The combined effects of rich geospatial and semantic hints, short system response time, and friendly user interface may help to significantly reduce the physiological and mental burdens on survey respondents, hence leading to a higher rate of participation.
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Mining Social Media to Create Personalized Recommendations for Tourist Visits
Adrian Popescu, Gregory Grefenstette Mining Social Media to Create Personalized Recommendations for Tourist Visits, COM.Geo 2011, May 23-25, Washington DC, USA.
Photo sharing platforms users often annotate their trip photos with landmark names. These annotations can be... more Photo sharing platforms users often annotate their trip photos with landmark names. These annotations can be aggregated in order to recommend lists of popular visitor attractions similar to those found in classical tourist guides. However, individual tourist preferences can vary significantly so good recommendations should be tailored to individual tastes. Here we pose this visit personalization as a collaborative filtering problem. We mine the record of visited landmarks exposed in online user data to build a user-user similarity matrix. When a user wants to visit a new destination, a list of potentially interesting visitor attractions is produced based on the experience of like-minded users who already visited that destination. We compare our recommender to a baseline which simulates classical tourist guides on a large sample of Flickr users.
Mapping the Flaneur: A Geospatial Translation of Charles Baudelaire's "Les Hiboux"
by Gwilym Eades
Written for a graduate seminar during the early part of my PhD. Presented at the CAG annual meeting, 2009, Ottawa
