The spatio-temporal uncertainty is an inherent feature of moving objects. One scenario where uncertainty exists is the movement of moving objects in the future, which results from lacking the knowledge of the prediction method. To solve this problem is useful, for example, to predict the locations of a hurricane and its relationships with points of interest on the land. The solution calls for a sound model to describe and handle the uncertainty properly. This paper introduces such a model which represents the spatio-temporal uncertainty in the near future. We introduce an uncertainty model called the balloon model specifically for future movements. We discuss how to implement the balloon model in the moving object database and define some important operations on querying the uncertainty.
{"title":"Balloon: representing and querying the near future movement of predictive moving objects","authors":"Hechen Liu, Markus Schneider","doi":"10.1145/2068976.2068978","DOIUrl":"https://doi.org/10.1145/2068976.2068978","url":null,"abstract":"The spatio-temporal uncertainty is an inherent feature of moving objects. One scenario where uncertainty exists is the movement of moving objects in the future, which results from lacking the knowledge of the prediction method. To solve this problem is useful, for example, to predict the locations of a hurricane and its relationships with points of interest on the land. The solution calls for a sound model to describe and handle the uncertainty properly. This paper introduces such a model which represents the spatio-temporal uncertainty in the near future. We introduce an uncertainty model called the balloon model specifically for future movements. We discuss how to implement the balloon model in the moving object database and define some important operations on querying the uncertainty.","PeriodicalId":302720,"journal":{"name":"SSO '11","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130971225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Semantic similarity measurement has been an active research area in GIScience and the Semantic Web for many years. However, implementations of these measures were largely missing, not publicly available, or tailored to specific application needs. To foster the application of similarity reasoning in information retrieval, ontology engineering, and spatial decision support, we implemented the SIM-DL semantic similarity server as well as a plug-in for the popular Protégé ontology editor. While SIM-DL has been successfully applied to several application areas, the implemented similarity theory was largely structural, could not handle concept and instance similarity within the same framework, and was based on a Protégé version and DIG interface that have been re-engineered over the last years. This paper introduces a new version, called SIM-DLA, engineered from scratch to addresses these shortcomings. It is based on our new similarity theory, can handle inter-instance and inter-concept similarity using the same functions and alignments, and is available for the new Protégé version 4.1.
{"title":"Introducing the new SIM-DLA semantic similarity measurement plug-in for the Protégé ontology editor","authors":"Christoph Mülligann, Johannes Trame, K. Janowicz","doi":"10.1145/2068976.2068979","DOIUrl":"https://doi.org/10.1145/2068976.2068979","url":null,"abstract":"Semantic similarity measurement has been an active research area in GIScience and the Semantic Web for many years. However, implementations of these measures were largely missing, not publicly available, or tailored to specific application needs. To foster the application of similarity reasoning in information retrieval, ontology engineering, and spatial decision support, we implemented the SIM-DL semantic similarity server as well as a plug-in for the popular Protégé ontology editor. While SIM-DL has been successfully applied to several application areas, the implemented similarity theory was largely structural, could not handle concept and instance similarity within the same framework, and was based on a Protégé version and DIG interface that have been re-engineered over the last years. This paper introduces a new version, called SIM-DLA, engineered from scratch to addresses these shortcomings. It is based on our new similarity theory, can handle inter-instance and inter-concept similarity using the same functions and alignments, and is available for the new Protégé version 4.1.","PeriodicalId":302720,"journal":{"name":"SSO '11","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121978930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pedro A. Szekely, Craig A. Knoblock, Shubham Gupta, M. Taheriyan, Bo Wu
Using today's GIS tools, users without programming expertise are unable to fully exploit the growing amount of geospatial data becoming available because today's tools limit them to displaying data as layers for a region on a map. Fusing the data in more complex ways requires the ability to invoke processing algorithms and to combine the data these algorithms produce in sophisticated ways. Our approach, implemented in a tool called Karma, encapsulates these algorithms as Web services described using semantic models that not only specify the data types for the inputs and outputs, but also specify the relationships between them. Karma semi-automatically builds these models from sample data and then uses these models to provide an easy to use interface that lets users seamlessly implement workflows that combine and process the data in sophisticated ways.
{"title":"Exploiting semantics of web services for geospatial data fusion","authors":"Pedro A. Szekely, Craig A. Knoblock, Shubham Gupta, M. Taheriyan, Bo Wu","doi":"10.1145/2068976.2068981","DOIUrl":"https://doi.org/10.1145/2068976.2068981","url":null,"abstract":"Using today's GIS tools, users without programming expertise are unable to fully exploit the growing amount of geospatial data becoming available because today's tools limit them to displaying data as layers for a region on a map. Fusing the data in more complex ways requires the ability to invoke processing algorithms and to combine the data these algorithms produce in sophisticated ways. Our approach, implemented in a tool called Karma, encapsulates these algorithms as Web services described using semantic models that not only specify the data types for the inputs and outputs, but also specify the relationships between them. Karma semi-automatically builds these models from sample data and then uses these models to provide an easy to use interface that lets users seamlessly implement workflows that combine and process the data in sophisticated ways.","PeriodicalId":302720,"journal":{"name":"SSO '11","volume":"226 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124493626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Savelyev, Sen Xu, K. Janowicz, Christoph Mülligann, Jim Thatcher, Wei Luo
The term Volunteered Geographic Information (VGI) describes various layperson-based, geo-collaboration projects to collect, maintain, and visualize information. VGI has been successfully utilized in scenarios such as emergency response and is also increasingly integrated into commercial products. Based on an analysis of existing projects and research, we propose to extend the idea of VGI by introducing Volunteered Geographic Services (VGS). Instead of contributing information, volunteers can request or offer microservices to their local community. We provide a flexible server framework that handles service requests and offers. We also implement a smartphone application developed using Google's Android platform. The server and mobile client are realized following the Linked Data paradigm and using Semantic Web technologies. In this paper, we discuss the idea behind VGS, motivate it using two scenarios, and explain the technical realization.
{"title":"Volunteered geographic services: developing a linked data driven location-based service","authors":"A. Savelyev, Sen Xu, K. Janowicz, Christoph Mülligann, Jim Thatcher, Wei Luo","doi":"10.1145/2068976.2068980","DOIUrl":"https://doi.org/10.1145/2068976.2068980","url":null,"abstract":"The term Volunteered Geographic Information (VGI) describes various layperson-based, geo-collaboration projects to collect, maintain, and visualize information. VGI has been successfully utilized in scenarios such as emergency response and is also increasingly integrated into commercial products. Based on an analysis of existing projects and research, we propose to extend the idea of VGI by introducing Volunteered Geographic Services (VGS). Instead of contributing information, volunteers can request or offer microservices to their local community. We provide a flexible server framework that handles service requests and offers. We also implement a smartphone application developed using Google's Android platform. The server and mobile client are realized following the Linked Data paradigm and using Semantic Web technologies. In this paper, we discuss the idea behind VGS, motivate it using two scenarios, and explain the technical realization.","PeriodicalId":302720,"journal":{"name":"SSO '11","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131953181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Gahegan, W. Smart, S. Masoud-Ansari, Brandon Whitehead
We describe a semantically-based Web Map Mediation Service (WMMS) that allows researchers to define, capture and reuse semantic relationships between map categories, via a set of Web Services. A map can then be viewed according to different taxonomies or legends, whose categories have been semantically related to those native to the map. Such 'mappings' or 'mediation schema' can be constructed directly between maps, or can utilise an independent 'master schema' such as an application ontology, to which map categories are aligned. This paper explains the workings of the Mediation Service that allows users to: (i) experiment with the design of map classification schemes, (ii) explore how the use of different schemes affects what is apparent on the map and (iii) translate maps---as far as possible---from one classification scheme to another. Semantic equivalences and similarities are supported via underlying ontologies, and it is these that facilitate the merging and re-grouping of classes. Users can create their own map re-classification schemes, which can be serialized for later use. They can also create and share new versions of existing maps that have been reclassified according to the mediations that they specify. Examples are provided of mediations to support the combined use of three different land cover maps used in New Zealand, each with a different set of base categories. The service shows promise in extending the useful life of historical data, by allowing communities to build and share schemas that re-express older map legends.
{"title":"A semantic web map mediation service: interactive redesign and sharing of map legends","authors":"M. Gahegan, W. Smart, S. Masoud-Ansari, Brandon Whitehead","doi":"10.1145/2068976.2068977","DOIUrl":"https://doi.org/10.1145/2068976.2068977","url":null,"abstract":"We describe a semantically-based Web Map Mediation Service (WMMS) that allows researchers to define, capture and reuse semantic relationships between map categories, via a set of Web Services. A map can then be viewed according to different taxonomies or legends, whose categories have been semantically related to those native to the map. Such 'mappings' or 'mediation schema' can be constructed directly between maps, or can utilise an independent 'master schema' such as an application ontology, to which map categories are aligned.\u0000 This paper explains the workings of the Mediation Service that allows users to: (i) experiment with the design of map classification schemes, (ii) explore how the use of different schemes affects what is apparent on the map and (iii) translate maps---as far as possible---from one classification scheme to another. Semantic equivalences and similarities are supported via underlying ontologies, and it is these that facilitate the merging and re-grouping of classes. Users can create their own map re-classification schemes, which can be serialized for later use. They can also create and share new versions of existing maps that have been reclassified according to the mediations that they specify.\u0000 Examples are provided of mediations to support the combined use of three different land cover maps used in New Zealand, each with a different set of base categories. The service shows promise in extending the useful life of historical data, by allowing communities to build and share schemas that re-express older map legends.","PeriodicalId":302720,"journal":{"name":"SSO '11","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127084254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A steadily increasing data tsunami is rolling over us, to a large extent consisting of sensor, image, and statistics data acquired in earth, space, life, and social sciences, to name but a few. Sampled data appear as multi-dimensional raster data - often time series -, but also as point clouds. The Open Geospatial Consortium (OGC) notion of a coverage describes geo raster data and more, such as meshes, trajectories, and surfaces. A current challenge is to use such services in automatically orchestrating mash-ups. The indispensable prerequisite, inter-operability, however, is hindered by the large diversity of data formats and corresponding data models. In this paper we present our ongoing work on a semantic representation of coverage data and service standards. We present a Web Coverage Ontology (WCO) and investigate how to apply WCO to geospatial web coverage services (WCS). By integrating coverages into the semantic landscape we aim at automatic discovery of, composition of, and reasoning about geo coverage services.
{"title":"Applying WCO ontology to geospatial web coverage services","authors":"Xia Wang, P. Baumann","doi":"10.1145/2068976.2068982","DOIUrl":"https://doi.org/10.1145/2068976.2068982","url":null,"abstract":"A steadily increasing data tsunami is rolling over us, to a large extent consisting of sensor, image, and statistics data acquired in earth, space, life, and social sciences, to name but a few. Sampled data appear as multi-dimensional raster data - often time series -, but also as point clouds. The Open Geospatial Consortium (OGC) notion of a coverage describes geo raster data and more, such as meshes, trajectories, and surfaces. A current challenge is to use such services in automatically orchestrating mash-ups. The indispensable prerequisite, inter-operability, however, is hindered by the large diversity of data formats and corresponding data models.\u0000 In this paper we present our ongoing work on a semantic representation of coverage data and service standards. We present a Web Coverage Ontology (WCO) and investigate how to apply WCO to geospatial web coverage services (WCS). By integrating coverages into the semantic landscape we aim at automatic discovery of, composition of, and reasoning about geo coverage services.","PeriodicalId":302720,"journal":{"name":"SSO '11","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134501425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper discusses geospatial barriers modeled as a specialized class of boundaries. This work shows how these concepts contribute to a broader ontology of boundaries. Barriers are modeled as subclasses of the DOLCE class endurant. Other endurants include the objects a barrier protects, i.e., target objects, and the objects that a barrier hinders, i.e., active objects. Two classes related to barriers, active objects, and target objects -- enclose and block - are modeled as perdurants. The distance measurements necessary for determining these endurant and perdurant classes are modeled as qualities. Different combinations of these classes are examined in order to model how barriers can be strengthened, as well as illustrate additional cases involving boundaries as barriers.
{"title":"Modeling geospatial barriers","authors":"E. White, K. Stewart","doi":"10.1145/2068976.2068983","DOIUrl":"https://doi.org/10.1145/2068976.2068983","url":null,"abstract":"This paper discusses geospatial barriers modeled as a specialized class of boundaries. This work shows how these concepts contribute to a broader ontology of boundaries. Barriers are modeled as subclasses of the DOLCE class endurant. Other endurants include the objects a barrier protects, i.e., target objects, and the objects that a barrier hinders, i.e., active objects. Two classes related to barriers, active objects, and target objects -- enclose and block - are modeled as perdurants. The distance measurements necessary for determining these endurant and perdurant classes are modeled as qualities. Different combinations of these classes are examined in order to model how barriers can be strengthened, as well as illustrate additional cases involving boundaries as barriers.","PeriodicalId":302720,"journal":{"name":"SSO '11","volume":"11 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127457930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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