2004
Journal article
Closed Access
Integrating knowledge representation and reasoning in geographical information systems
Mancarella P., Raffaetà A., Renso C., Turini F.
We propose a formalism and a programming environment in which sophisticated spatio-temporal reasoning can be performed, while keeping the capabilities of manipulating and presenting large amounts of geographical data, typical of commercial Geographical Information Systems (GISs). The spatio-temporal knowledge representation language, named MuTACLP$. $, is based on constraint logic programming and it is integrated via a middleware of commands and translation features with a commercial GIS. The paper presents the language, the architecture of the environment and a few examples of its use in the field of event planning.Source: International journal of geographical information science (Print) 18 (2004): 417–447. doi:10.1080/13658810410001672908
DOI: 10.1080/13658810410001672908
Metrics:
Mancarella P., Raffaetà A., Renso C., Turini F.
We propose a formalism and a programming environment in which sophisticated spatio-temporal reasoning can be performed, while keeping the capabilities of manipulating and presenting large amounts of geographical data, typical of commercial Geographical Information Systems (GISs). The spatio-temporal knowledge representation language, named MuTACLP$. $, is based on constraint logic programming and it is integrated via a middleware of commands and translation features with a commercial GIS. The paper presents the language, the architecture of the environment and a few examples of its use in the field of event planning.Source: International journal of geographical information science (Print) 18 (2004): 417–447. doi:10.1080/13658810410001672908
DOI: 10.1080/13658810410001672908
Metrics:
See at:
International Journal of Geographical Information Science 
| CNR ExploRA
2003
Conference article
Closed Access
Qualitative spatial reasoning in a logical framework
Raffaetà A., Renso C., Turini F.
In this paper we present an approach to qualitative spatial reasoning based on the spatio-temporal language STACLP. In particular, we show how the topological 9-intersection model and the direction relations based on projections can be modelled in such a framework. STACLP is a constraint logic programming language where formulae can be annotated with labels (annotations) and where relations between these labels can be expressed by using constraints. Annotations are used to represent both time and space.Source: 8th Congress of the Italian Association for Artificial Intelligence, pp. 78–90, Pisa, Italy, September 2003
DOI: 10.1007/b13658
Metrics:
Raffaetà A., Renso C., Turini F.
In this paper we present an approach to qualitative spatial reasoning based on the spatio-temporal language STACLP. In particular, we show how the topological 9-intersection model and the direction relations based on projections can be modelled in such a framework. STACLP is a constraint logic programming language where formulae can be annotated with labels (annotations) and where relations between these labels can be expressed by using constraints. Annotations are used to represent both time and space.Source: 8th Congress of the Italian Association for Artificial Intelligence, pp. 78–90, Pisa, Italy, September 2003
DOI: 10.1007/b13658
Metrics:
See at:
doi.org | link.springer.com | CNR ExploRA
2008
Conference article
Unknown
The spatial knowledge representation of players movement in mobile outdoor gaming
Wachowicz M., Daniel O., Renso C., Muoz Moraga E., Parada J.
This paper describes an innovative approach for developing a spatial knowledge representation based on the existence of multi tier spaces as a mental construction of human movement. The three "spaces" paradigm has been proposed to support the reasoning process in terms of sensing, symbolic, and social spaces. The spatial knowledge representation was implemented as a computational ontology in Protégé, and it has been applied to provide new insight about the actual behavioural patterns of players within a recreation site, accordingly to checkpoints and similar players´ interactions. This first experiment consisted of an educational game in Amsterdam using mobile phones and GPStechnology for 200 students having the age of 12-14. The results demonstrate that different types of inferences play a different role accordingly to what a recreational planner needs to infer, that is, the location of interactions among players and the environment.Source: The Fourth International Conference on Monitoring and Management of Visitor Flows in Recreational and Protected Areas, Montecatini Terme, Italy, 28/10/2008
Wachowicz M., Daniel O., Renso C., Muoz Moraga E., Parada J.
This paper describes an innovative approach for developing a spatial knowledge representation based on the existence of multi tier spaces as a mental construction of human movement. The three "spaces" paradigm has been proposed to support the reasoning process in terms of sensing, symbolic, and social spaces. The spatial knowledge representation was implemented as a computational ontology in Protégé, and it has been applied to provide new insight about the actual behavioural patterns of players within a recreation site, accordingly to checkpoints and similar players´ interactions. This first experiment consisted of an educational game in Amsterdam using mobile phones and GPStechnology for 200 students having the age of 12-14. The results demonstrate that different types of inferences play a different role accordingly to what a recreational planner needs to infer, that is, the location of interactions among players and the environment.Source: The Fourth International Conference on Monitoring and Management of Visitor Flows in Recreational and Protected Areas, Montecatini Terme, Italy, 28/10/2008
See at: CNR ExploRA
2001
Contribution to conference
Unknown
Spatio-temporal and uncertain reasoning on geographical data
Renso C.
An abstract is not available.Source: Review Progetto ReviGIS, Tolosa, France, 2001
Renso C.
An abstract is not available.Source: Review Progetto ReviGIS, Tolosa, France, 2001
See at: CNR ExploRA
2007
Contribution to book
Unknown
Characterising the Next Generation of Mobile Applications Through a Privacy-Aware Geographic Knowledge Discovery Process
Renso C.
The proliferation of mobile technologies for 'always-on' at 'any-time' and 'anyplace' has facilitated the generation of huge volume of positioning data sets containing information about the location and the movement of entities through the geographic environment. In principle, every time an entity moves through space, it creates a trajectory (i.e. track or path) representing the history of its past and current locations. Examples of interesting trajectories of moving entities may range from hurricane and tornado tracks [19] to individual trajectories of animals [26] and planes [5]. Specially designed sensors can provide the location of a mobile entity as well as information about the geographic environment where this entity is moving. Current research on mobile technologies such as sensor web, wireless communication and portable computers has been crucial for the development of multi-sensor systems. Their use to sense a geographic environment and mobile entities can include photodiodes to detect light level, accelerometers to provide tilt and vibration measurements, passive infrared sensors to detect the proximity of humans, omni-directionalmicrophones to detect sound and other built-in sensors for temperature, pressure, and CO gas [9].Source: Mobility, Data Mining and Privacy: Geographic Knowledge Discovery, pp. 39–70. Berlin: Springer-Verlag, 2007
Renso C.
The proliferation of mobile technologies for 'always-on' at 'any-time' and 'anyplace' has facilitated the generation of huge volume of positioning data sets containing information about the location and the movement of entities through the geographic environment. In principle, every time an entity moves through space, it creates a trajectory (i.e. track or path) representing the history of its past and current locations. Examples of interesting trajectories of moving entities may range from hurricane and tornado tracks [19] to individual trajectories of animals [26] and planes [5]. Specially designed sensors can provide the location of a mobile entity as well as information about the geographic environment where this entity is moving. Current research on mobile technologies such as sensor web, wireless communication and portable computers has been crucial for the development of multi-sensor systems. Their use to sense a geographic environment and mobile entities can include photodiodes to detect light level, accelerometers to provide tilt and vibration measurements, passive infrared sensors to detect the proximity of humans, omni-directionalmicrophones to detect sound and other built-in sensors for temperature, pressure, and CO gas [9].Source: Mobility, Data Mining and Privacy: Geographic Knowledge Discovery, pp. 39–70. Berlin: Springer-Verlag, 2007
See at: CNR ExploRA
2009
Contribution to book
Unknown
The role of a multi-tier ontological framework in reasoning to discover meaningful patterns of sustainable mobility
Wachowicz M., Macedo J., Renso C., Ligtenberg A.
The successful applications of Geographical Knowledge Discovery in Databases (GKDD) are not common, despite the vast literature on knowledge discovery in databases. Although it is relatively straightforward to find patterns in very large spatio-temporal databases, establishing their relevance and explaining their causes are both very complex problems. In practice, spatio- temporal databases are not adequate to handle geographical knowledge in an ad-hoc manner, and as a result, most of the patterns found in a GKDD process may well already be background knowledge, which refers to the common sense reasoning of a geographical knowledge domain. Addressing these issues requires considering a geographical knowledge discovery process as a multi- tier ontological process, in the sense that more complex reasoning modes can be used to help the comprehension of what makes one pattern structurally and meaningfully different from another. Towards this goal, this Chapter proposes a multi-tier ontological framework to support a GKDD process. Three ontological tiers are described to provide the common base for the organisation of different nature and sources of knowledge as well as the reasoning tasks integrated within a spatio-temporal database. They are: Domain, Application and Data Ontology Tiers. The potential of this approach is illustrated on (a) reducing the semantic gap between an ontological tier and a database representation by using mappings between the ontology and conceptual model, and (b) permitting to define spatio-temporal relationships within an ontology, which can be translated to spatio-temporal conceptual queries. The implementation has been carried out as a proof-of-concept and the specific information metaphor of movement-as-trajectory has been used to illustrate the implementation of the Data Ontology Tier. The preliminary results are pointing out that geographical knowledge of sustainable mobility must come from a global and systemic view of patterns within a GKDD process, and the important role of a multi-tier ontological framework on the integration of semantic abstractions (concepts), reasoning tasks, and patterns. They had also drawn attention to the fact that combining ontological representation with database querying mechanisms is fundamental for the use information metaphors in GKDD processes.Source: Geographic Data Mining and Knowledge Discovery, edited by H. Miller, J. Han, pp. 1–30. Berlin: Springer, 2009
Wachowicz M., Macedo J., Renso C., Ligtenberg A.
The successful applications of Geographical Knowledge Discovery in Databases (GKDD) are not common, despite the vast literature on knowledge discovery in databases. Although it is relatively straightforward to find patterns in very large spatio-temporal databases, establishing their relevance and explaining their causes are both very complex problems. In practice, spatio- temporal databases are not adequate to handle geographical knowledge in an ad-hoc manner, and as a result, most of the patterns found in a GKDD process may well already be background knowledge, which refers to the common sense reasoning of a geographical knowledge domain. Addressing these issues requires considering a geographical knowledge discovery process as a multi- tier ontological process, in the sense that more complex reasoning modes can be used to help the comprehension of what makes one pattern structurally and meaningfully different from another. Towards this goal, this Chapter proposes a multi-tier ontological framework to support a GKDD process. Three ontological tiers are described to provide the common base for the organisation of different nature and sources of knowledge as well as the reasoning tasks integrated within a spatio-temporal database. They are: Domain, Application and Data Ontology Tiers. The potential of this approach is illustrated on (a) reducing the semantic gap between an ontological tier and a database representation by using mappings between the ontology and conceptual model, and (b) permitting to define spatio-temporal relationships within an ontology, which can be translated to spatio-temporal conceptual queries. The implementation has been carried out as a proof-of-concept and the specific information metaphor of movement-as-trajectory has been used to illustrate the implementation of the Data Ontology Tier. The preliminary results are pointing out that geographical knowledge of sustainable mobility must come from a global and systemic view of patterns within a GKDD process, and the important role of a multi-tier ontological framework on the integration of semantic abstractions (concepts), reasoning tasks, and patterns. They had also drawn attention to the fact that combining ontological representation with database querying mechanisms is fundamental for the use information metaphors in GKDD processes.Source: Geographic Data Mining and Knowledge Discovery, edited by H. Miller, J. Han, pp. 1–30. Berlin: Springer, 2009
See at: CNR ExploRA
2011
Journal article
Open Access
An algorithm to identify avoidance behavior in moving object trajectories
Alvares L. O., Loy A. M., Renso C., Bogorny V.
Research on trajectory behavior has increased significantly in the last few years. The focus has been on the search for patterns considering the movement of the moving object in space and time, essentially looking for similar geometric properties and dense regions. This paper proposes an algorithm to detect a new kind of behavior pattern that identifies when a moving object is avoiding specific spatial regions, such as security cameras. This behavior pattern is called avoidance. The algorithm was evaluated with real trajectory data and achieved very good results.Source: Journal of the Brazilian Computer Society (Impr.) 17 (2011): 193–203. doi:10.1007/s13173-011-0037-3
DOI: 10.1007/s13173-011-0037-3
Metrics:
Alvares L. O., Loy A. M., Renso C., Bogorny V.
Research on trajectory behavior has increased significantly in the last few years. The focus has been on the search for patterns considering the movement of the moving object in space and time, essentially looking for similar geometric properties and dense regions. This paper proposes an algorithm to detect a new kind of behavior pattern that identifies when a moving object is avoiding specific spatial regions, such as security cameras. This behavior pattern is called avoidance. The algorithm was evaluated with real trajectory data and achieved very good results.Source: Journal of the Brazilian Computer Society (Impr.) 17 (2011): 193–203. doi:10.1007/s13173-011-0037-3
DOI: 10.1007/s13173-011-0037-3
Metrics:
See at:
Journal of the Brazilian Computer Society 
| CNR ExploRA
2011
Conference article
Open Access
Trajectory data analysis using complex networks
Brilhante I., De Macedo J., Renso C., Casanova M. A.
A massive amount of data on moving object trajectories is available today. However, it is still a major challenge to process such information in order to explain moving object interactions, which could help in revealing non-trivial behavioral patterns. To that end, we consider a complex networks-based representation of trajectory data. Frequent encounters among moving objects (trajectory encounters) are used to create the network edges whereas nodes represent trajectories. A real trajectory dataset of vehicles moving within the City of Milan allows us to study the structure of vehicle interactions and validate our method. We create seven networks and compute the clustering coefficient, and the average shortest path length comparing them with those of the Erd?s-Rényi model. Our analysis shows that all computed trajectory networks have the small world effect and the scale-free feature similar to the internet and biological networks. Finally, we discuss how these results could be interpreted in the light of the traffic application domain.Source: 15th Symposium on International Database Engineering & Applications, IDEAS, pp. 17–25, Lisbon, Portugal, 21-23 September 2011
DOI: 10.1145/2076623.2076627
Metrics:
Brilhante I., De Macedo J., Renso C., Casanova M. A.
A massive amount of data on moving object trajectories is available today. However, it is still a major challenge to process such information in order to explain moving object interactions, which could help in revealing non-trivial behavioral patterns. To that end, we consider a complex networks-based representation of trajectory data. Frequent encounters among moving objects (trajectory encounters) are used to create the network edges whereas nodes represent trajectories. A real trajectory dataset of vehicles moving within the City of Milan allows us to study the structure of vehicle interactions and validate our method. We create seven networks and compute the clustering coefficient, and the average shortest path length comparing them with those of the Erd?s-Rényi model. Our analysis shows that all computed trajectory networks have the small world effect and the scale-free feature similar to the internet and biological networks. Finally, we discuss how these results could be interpreted in the light of the traffic application domain.Source: 15th Symposium on International Database Engineering & Applications, IDEAS, pp. 17–25, Lisbon, Portugal, 21-23 September 2011
DOI: 10.1145/2076623.2076627
Metrics:
See at:
www.inf.puc-rio.br | dl.acm.org | doi.org | CNR ExploRA
2011
Contribution to journal
Open Access
Special issue on "Context-Aware Data Mining (CADM)"
Renso C., Bogorny V., Xiong H.
Source: Knowledge and Information Systems 28 (2011): 249–250. doi:10.1007/s10115-011-0436-y
DOI: 10.1007/s10115-011-0436-y
Metrics:
Renso C., Bogorny V., Xiong H.
Source: Knowledge and Information Systems 28 (2011): 249–250. doi:10.1007/s10115-011-0436-y
DOI: 10.1007/s10115-011-0436-y
Metrics:
See at:
Knowledge and Information Systems | Knowledge and Information Systems | www.springerlink.com | CNR ExploRA
2011
Report
Unknown
Complex network study on moving object trajectories
Brilhante Igo Ramalho, De Macedo Jose, Renso Chiara
Although we have a massive amount of data on moving object trajectories, which have been easily collected by geographic positioning devices, it is still a major challenge to process such information in order to generate knowledge about the behavior of these objects. In this paper, we study moving object trajectories from a complex network point of view. First, we consider a network with a node representing one trajectory and an edge representing an encounter between two trajectories in time and space. Real data were gathered from vehicles moving within Milan's city center, in a total of 225,932 trajectories. We have generated 7 networks denoting each day of the week. Our analysis shows that for all computed networks the degree distribution decays exponentially. We determine the exact values of the clustering coefficient, and the average shortest path length and compare them with those of the Erdo ?s-Re ?nyi. The time evolution of these quantities are calculated and the corresponding results discussed.Source: ISTI Technical reports, 2011
Brilhante Igo Ramalho, De Macedo Jose, Renso Chiara
Although we have a massive amount of data on moving object trajectories, which have been easily collected by geographic positioning devices, it is still a major challenge to process such information in order to generate knowledge about the behavior of these objects. In this paper, we study moving object trajectories from a complex network point of view. First, we consider a network with a node representing one trajectory and an edge representing an encounter between two trajectories in time and space. Real data were gathered from vehicles moving within Milan's city center, in a total of 225,932 trajectories. We have generated 7 networks denoting each day of the week. Our analysis shows that for all computed networks the degree distribution decays exponentially. We determine the exact values of the clustering coefficient, and the average shortest path length and compare them with those of the Erdo ?s-Re ?nyi. The time evolution of these quantities are calculated and the corresponding results discussed.Source: ISTI Technical reports, 2011
See at: CNR ExploRA
2013
Journal article
Restricted
Semantic trajectories modeling and analysis
Parent C., Spaccapietra S., Renso C., Andrienko G., Andrienko N., Bogorny V., Damiani M. L., Gkoulalas D. A., Macedo J. A., Pelekis N., Theodoridis Y., Yan Z.
Focus on movement data has increased as a consequence of the larger availability of such data due to current GPS, GSM, RFID, and sensors techniques. In parallel, interest in movement has shifted from raw movement data analysis to more application-oriented ways of analyzing segments of movement suitable for the specific purposes of the application. This trend has promoted semantically rich trajectories, rather than raw movement, as the core object of interest in mobility studies. This survey provides the definitions of the basic concepts about mobility data, an analysis of the issues in mobility data management, and a survey of the approaches and techniques for: (i) constructing trajectories from movement tracks, (ii) enriching trajectories with semantic information to enable the desired interpretations of movements, and (iii) using data mining to analyze semantic trajectories and extract knowledge about their characteristics, in particular the behavioral patterns of the moving objects. Last but not least, the article surveys the new privacy issues that arise due to the semantic aspects of trajectories.Source: ACM computing surveys 45 (2013): 42-1–42-32. doi:10.1145/2501654.2501656
DOI: 10.1145/2501654.2501656
Project(s): MODAP
Metrics:
Parent C., Spaccapietra S., Renso C., Andrienko G., Andrienko N., Bogorny V., Damiani M. L., Gkoulalas D. A., Macedo J. A., Pelekis N., Theodoridis Y., Yan Z.
Focus on movement data has increased as a consequence of the larger availability of such data due to current GPS, GSM, RFID, and sensors techniques. In parallel, interest in movement has shifted from raw movement data analysis to more application-oriented ways of analyzing segments of movement suitable for the specific purposes of the application. This trend has promoted semantically rich trajectories, rather than raw movement, as the core object of interest in mobility studies. This survey provides the definitions of the basic concepts about mobility data, an analysis of the issues in mobility data management, and a survey of the approaches and techniques for: (i) constructing trajectories from movement tracks, (ii) enriching trajectories with semantic information to enable the desired interpretations of movements, and (iii) using data mining to analyze semantic trajectories and extract knowledge about their characteristics, in particular the behavioral patterns of the moving objects. Last but not least, the article surveys the new privacy issues that arise due to the semantic aspects of trajectories.Source: ACM computing surveys 45 (2013): 42-1–42-32. doi:10.1145/2501654.2501656
DOI: 10.1145/2501654.2501656
Project(s): MODAP
Metrics:
See at:
dl.acm.org | ACM Computing Surveys | Infoscience - EPFL scientific publications | Fraunhofer-ePrints | CNR ExploRA
2013
Contribution to book
Restricted
Tailoring trajectories and their moving patterns to contexts
Wachowicz M., Ong R., Renso C.
Nowadays heterogeneous mobile data sources are producing an enor- mous amount of contextual information that can improve our interpreta- tion of discovered mobility patterns. Because both an entity and the data sources can be mobile, what context is and how it can be used to inter- pret mobility patters may vary anyplace at anytime. This paper describes an approach for tailoring mobility patterns based on the synergy of trajec- tory and mobility pattern annotation techniques, where contexts are rep- resented as dynamic semantic views. These views are obtained after the classification of context variables that are selected based on the classifica- tion criteria previously proposed for a taxonomy of collective phenom- ena. An experiment is used to illustrate the proposed approach for tailor- ing moving flock patterns to contexts of visitors in a recreational area.Source: Geographic Information Science at the Heart of Europe, edited by Danny Vandenbroucke, Bénédicte Bucher, Joep Crompvoets, pp. 285–303, 2013
DOI: 10.1007/978-3-319-00615-4_16
Project(s): SEEK
Metrics:
Wachowicz M., Ong R., Renso C.
Nowadays heterogeneous mobile data sources are producing an enor- mous amount of contextual information that can improve our interpreta- tion of discovered mobility patterns. Because both an entity and the data sources can be mobile, what context is and how it can be used to inter- pret mobility patters may vary anyplace at anytime. This paper describes an approach for tailoring mobility patterns based on the synergy of trajec- tory and mobility pattern annotation techniques, where contexts are rep- resented as dynamic semantic views. These views are obtained after the classification of context variables that are selected based on the classifica- tion criteria previously proposed for a taxonomy of collective phenom- ena. An experiment is used to illustrate the proposed approach for tailor- ing moving flock patterns to contexts of visitors in a recreational area.Source: Geographic Information Science at the Heart of Europe, edited by Danny Vandenbroucke, Bénédicte Bucher, Joep Crompvoets, pp. 285–303, 2013
DOI: 10.1007/978-3-319-00615-4_16
Project(s): SEEK
Metrics:
See at:
doi.org | link.springer.com | CNR ExploRA
2013
Conference article
Open Access
A proactive application to monitor truck fleets
Da Costa Albuquerque F., Casanova M. A., De Macedo J. A. F., De Carvalho M. T. M., Renso C.
Positioning systems, combined with inexpensive communication technologies, open interesting possibilities to implement real-time applications that monitor vehicles and support decision making. This paper first discusses basic requirements for proactive real-time monitoring applications. Then, it describes how to structure and geo-reference unstructured text information available on the Internet, with a focus on road conditions change and using available geocoding services. Lastly, the paper outlines an application that monitors a fleet of trucks and incorporates proactive features.Source: MDM13 - International Conference on Mobile Data Management, pp. 301, Milano, 3-6 June 2013
DOI: 10.1109/mdm.2013.44
Project(s): SEEK
Metrics:
Da Costa Albuquerque F., Casanova M. A., De Macedo J. A. F., De Carvalho M. T. M., Renso C.
Positioning systems, combined with inexpensive communication technologies, open interesting possibilities to implement real-time applications that monitor vehicles and support decision making. This paper first discusses basic requirements for proactive real-time monitoring applications. Then, it describes how to structure and geo-reference unstructured text information available on the Internet, with a focus on road conditions change and using available geocoding services. Lastly, the paper outlines an application that monitors a fleet of trucks and incorporates proactive features.Source: MDM13 - International Conference on Mobile Data Management, pp. 301, Milano, 3-6 June 2013
DOI: 10.1109/mdm.2013.44
Project(s): SEEK
Metrics:
See at:
www.inf.puc-rio.br | doi.org | CNR ExploRA
2013
Conference article
Restricted
Average speed estimation for road networks based on GPS raw trajectories
Barbosa I., Casanova M. A., Renso C., Macedo J.
For applications involving displacements around cities, planners cannot count on moving at the legal speed limits. Indeed, the amount of circulating vehicles decreases the average speed and consequently increases the estimated time for daily trips. On the other hand, the number of available trajectories generated by GPS devices is growing. This paper presents a methodology to compute statistics about a road network based on GPS-tracked points, generated by vehicles moving around a city. The proposed methodology allows selecting the most representative data to describe how speeds are distributed along the days of week as well as along the time of the day. The results obtained may be used as an alternative to the shortest-path routing criterion for route planning.Source: ICEIS13 - 15th International Conference on Enterprise Information systems, pp. 490–497, Eseo, Angers Loira Valley, France, 04-07 July 2013
Project(s): SEEK
Barbosa I., Casanova M. A., Renso C., Macedo J.
For applications involving displacements around cities, planners cannot count on moving at the legal speed limits. Indeed, the amount of circulating vehicles decreases the average speed and consequently increases the estimated time for daily trips. On the other hand, the number of available trajectories generated by GPS devices is growing. This paper presents a methodology to compute statistics about a road network based on GPS-tracked points, generated by vehicles moving around a city. The proposed methodology allows selecting the most representative data to describe how speeds are distributed along the days of week as well as along the time of the day. The results obtained may be used as an alternative to the shortest-path routing criterion for route planning.Source: ICEIS13 - 15th International Conference on Enterprise Information systems, pp. 490–497, Eseo, Angers Loira Valley, France, 04-07 July 2013
Project(s): SEEK
See at:
www.scitepress.org | CNR ExploRA
2013
Conference article
Restricted
Baquara: a holistic ontological framework for movement analysis using linked data
Fileto R., Kruger M., Pelekis N., Theodoridis Y., Renso C.
Movement understanding frequently requires further information and knowledge than what can be obtained from bare spatio-temporal traces. Despite recent progress in trajectory data management, there is still a gap between the spatio-temporal aspects and the semantics involved. This gap hinders trajectory analysis benefiting from growing collections of linked data, with well-defined and widely agreed semantics, already available on the Web. This article intro- duces Baquara, an ontology with rich constructs, associated with a system ar- chitecture and an approach to narrow this gap. The Baquara ontology functions as a conceptual framework for semantic enrichment of movement data with an- notations based on linked data. The proposed architecture and approach reveal new possibilities for trajectory analysis, using database management systems and triple stores extended with spatial data and operators. The viability of the proposal and the expressiveness of the Baquara ontology and enabled queries are investigated in a case study using real sets of trajectories and linked data.Source: ER 2013 - Conceptual Modeling. 32th International Conference, pp. 342–355, Hong Kong, China, 11-14 November 2013
DOI: 10.1007/978-3-642-41924-9_28
Project(s): SEEK
Metrics:
Fileto R., Kruger M., Pelekis N., Theodoridis Y., Renso C.
Movement understanding frequently requires further information and knowledge than what can be obtained from bare spatio-temporal traces. Despite recent progress in trajectory data management, there is still a gap between the spatio-temporal aspects and the semantics involved. This gap hinders trajectory analysis benefiting from growing collections of linked data, with well-defined and widely agreed semantics, already available on the Web. This article intro- duces Baquara, an ontology with rich constructs, associated with a system ar- chitecture and an approach to narrow this gap. The Baquara ontology functions as a conceptual framework for semantic enrichment of movement data with an- notations based on linked data. The proposed architecture and approach reveal new possibilities for trajectory analysis, using database management systems and triple stores extended with spatial data and operators. The viability of the proposal and the expressiveness of the Baquara ontology and enabled queries are investigated in a case study using real sets of trajectories and linked data.Source: ER 2013 - Conceptual Modeling. 32th International Conference, pp. 342–355, Hong Kong, China, 11-14 November 2013
DOI: 10.1007/978-3-642-41924-9_28
Project(s): SEEK
Metrics:
See at:
doi.org | link.springer.com | CNR ExploRA
2017
Conference article
Open Access
Searching linked data with a twist of serendipity
Eichler J. S. A., Casanova M. A., Furtado A. L., Ruback L., Leme L. A. P. P., Lopes G. R., Pereira Nunes B., Raffaetà A., Renso C.
Serendipity is defined as the discovery of a thing when one is not searching for it. In other words, serendipity means the discovery of information that provides valuable insights by unveiling previously unknown knowledge. This paper focuses on the problem of Linked Data serendipitous search. It first discusses how to capture a set of serendipity patterns in the context of Linked Data. Then, the paper introduces a Linked Data serendipitous search application, called the Serendipity Over Linked Data Search tool - SOL-Tool. Finally, the paper describes experiments with the tool to illustrate the serendipity effect using DBpedia. The experimental results present a prom-issory score of 90% of unexpectedness for real-world scenarios of the mu-sic domainSource: CAiSE 2017 - Advanced Information Systems Engineering 29th International Conference, pp. 495–510, Essen, Germany, 12-16 June 2017
DOI: 10.1007/978-3-319-59536-8_31
Metrics:
Eichler J. S. A., Casanova M. A., Furtado A. L., Ruback L., Leme L. A. P. P., Lopes G. R., Pereira Nunes B., Raffaetà A., Renso C.
Serendipity is defined as the discovery of a thing when one is not searching for it. In other words, serendipity means the discovery of information that provides valuable insights by unveiling previously unknown knowledge. This paper focuses on the problem of Linked Data serendipitous search. It first discusses how to capture a set of serendipity patterns in the context of Linked Data. Then, the paper introduces a Linked Data serendipitous search application, called the Serendipity Over Linked Data Search tool - SOL-Tool. Finally, the paper describes experiments with the tool to illustrate the serendipity effect using DBpedia. The experimental results present a prom-issory score of 90% of unexpectedness for real-world scenarios of the mu-sic domainSource: CAiSE 2017 - Advanced Information Systems Engineering 29th International Conference, pp. 495–510, Essen, Germany, 12-16 June 2017
DOI: 10.1007/978-3-319-59536-8_31
Metrics:
See at:
Archivio istituzionale della ricerca - Università degli Studi di Venezia Ca' Foscari | doi.org | link.springer.com | CNR ExploRA
2014
Journal article
Restricted
CONSTAnT - A conceptual data model for semantic trajectories of moving objects
Bogorny V., Renso C., Ribeiro De Aquino A., De Lucca S. F., Alvares L. O.
Several works have been proposed in the last few years for raw trajectory data analysis, and some attempts have been made to define trajectories from a more semantic point of view. Semantic trajectory data analysis has received significant attention recently, but the formal definition of semantic trajectory, the set of aspects that should be considered to semantically enrich trajectories and a conceptual data model integrating these aspects from a broad sense is still missing. This article presents a semantic trajectory conceptual data model named CONSTAnT, which defines the most important aspects of semantic trajectories. We believe that this model will be the foundation for the design of semantic trajectory databases, where several aspects that make a trajectory "semantic" are taken into account. The proposed model includes the concepts of semantic subtrajectory, semantic points, geographical places, events, goals, environment and behavior, to create a general concept of semantic trajectory. The proposed model is the result of several years of work by the authors in an effort to add more semantics to raw trajectory data for real applications. Two application examples and different queries show the flexibility of the model for different domains.Source: Transactions in GIS (Online) 18 (2014): 66–88. doi:10.1111/tgis.12011
DOI: 10.1111/tgis.12011
Project(s): SEEK
Metrics:
Bogorny V., Renso C., Ribeiro De Aquino A., De Lucca S. F., Alvares L. O.
Several works have been proposed in the last few years for raw trajectory data analysis, and some attempts have been made to define trajectories from a more semantic point of view. Semantic trajectory data analysis has received significant attention recently, but the formal definition of semantic trajectory, the set of aspects that should be considered to semantically enrich trajectories and a conceptual data model integrating these aspects from a broad sense is still missing. This article presents a semantic trajectory conceptual data model named CONSTAnT, which defines the most important aspects of semantic trajectories. We believe that this model will be the foundation for the design of semantic trajectory databases, where several aspects that make a trajectory "semantic" are taken into account. The proposed model includes the concepts of semantic subtrajectory, semantic points, geographical places, events, goals, environment and behavior, to create a general concept of semantic trajectory. The proposed model is the result of several years of work by the authors in an effort to add more semantics to raw trajectory data for real applications. Two application examples and different queries show the flexibility of the model for different domains.Source: Transactions in GIS (Online) 18 (2014): 66–88. doi:10.1111/tgis.12011
DOI: 10.1111/tgis.12011
Project(s): SEEK
Metrics:
See at:
Transactions in GIS | onlinelibrary.wiley.com | CNR ExploRA
2013
Journal article
Restricted
Assessing the attractiveness of places with movement data
Andre Salvaro F., Fileto R., Renso C.
Attractiveness of places has been studied by several sciences, giving rise to distinct ways for assessing it. However, the attractiveness evaluation methods currently available lack versatility to analyze diverse attractiveness phenomena in different kinds of places and spatial scales. This article describes a novel method, called M-Attract, to assess the attractiveness of interesting places, based on movement data. M-Attract examines trajectory episodes (e.g., stop, pass) that happen in places and their encompassing regions to compute their attractiveness. It is more flexible than state-of-the-art methods, with respect to land parcels, parameters, and measures used for attractiveness assessment. The proposed method has been extensively evaluated in experiments with real data, which demonstrate its contributions to analyze attractiveness of places and identify relevant phenomena in the geographic space.Source: Journal of Information and Data Management (2013): 124–133.
Project(s): SEEK
Andre Salvaro F., Fileto R., Renso C.
Attractiveness of places has been studied by several sciences, giving rise to distinct ways for assessing it. However, the attractiveness evaluation methods currently available lack versatility to analyze diverse attractiveness phenomena in different kinds of places and spatial scales. This article describes a novel method, called M-Attract, to assess the attractiveness of interesting places, based on movement data. M-Attract examines trajectory episodes (e.g., stop, pass) that happen in places and their encompassing regions to compute their attractiveness. It is more flexible than state-of-the-art methods, with respect to land parcels, parameters, and measures used for attractiveness assessment. The proposed method has been extensively evaluated in experiments with real data, which demonstrate its contributions to analyze attractiveness of places and identify relevant phenomena in the geographic space.Source: Journal of Information and Data Management (2013): 124–133.
Project(s): SEEK
See at:
seer.lcc.ufmg.br | CNR ExploRA
2013
Contribution to book
Unknown
Mobility Data: Modeling, Management, and Understanding
Renso C., Spaccapietra S., Zimànyi E.
Mobility of people and goods is essential in the global economy. The ability to track the routes and patterns associated with this mobility offers unprecedented opportunities for developing new, smarter applications in different domains. Much of the current research is devoted to developing concepts, models, and tools to comprehend mobility data and make them manageable for these applications. This book surveys the myriad facets of mobility data, from spatio-temporal data modeling, to data aggregation and warehousing, to data analysis, with a specific focus on monitoring people in motion (drivers, airplane passengers, crowds, and even animals in the wild). Written by a renowned group of worldwide experts, it presents a consistent framework that facilitates understanding of all these different facets, from basic definitions to state-of-the-art concepts and techniques, offering both researchers and professionals a thorough understanding of the applications and opportunities made possible by the development of mobility data.
Renso C., Spaccapietra S., Zimànyi E.
Mobility of people and goods is essential in the global economy. The ability to track the routes and patterns associated with this mobility offers unprecedented opportunities for developing new, smarter applications in different domains. Much of the current research is devoted to developing concepts, models, and tools to comprehend mobility data and make them manageable for these applications. This book surveys the myriad facets of mobility data, from spatio-temporal data modeling, to data aggregation and warehousing, to data analysis, with a specific focus on monitoring people in motion (drivers, airplane passengers, crowds, and even animals in the wild). Written by a renowned group of worldwide experts, it presents a consistent framework that facilitates understanding of all these different facets, from basic definitions to state-of-the-art concepts and techniques, offering both researchers and professionals a thorough understanding of the applications and opportunities made possible by the development of mobility data.
See at: CNR ExploRA
2013
Conference article
Unknown
Discovering trajectory outliers between regions of interest
Cunha Fontes V., Andre De Alencar L., Bogorny V., Renso C.
Source: GEOINFO 2013 - XIV Brazilian Symposium on Geoinformatics, pp. 49–60, Sao Paulo, Brazil, 24-27 November 2013
Project(s): SEEK
Cunha Fontes V., Andre De Alencar L., Bogorny V., Renso C.
Source: GEOINFO 2013 - XIV Brazilian Symposium on Geoinformatics, pp. 49–60, Sao Paulo, Brazil, 24-27 November 2013
Project(s): SEEK
See at: CNR ExploRA