Michela Bertolotto

Virtual reality for collaborative e-learning

In the past, the term e-learning referred to any method of learning that used electronic delivery methods. With the advent of the Internet however, e-learning has evolved and the term is now most commonly used to refer to online courses. A multitude of systems are now available to manage and deliver learning content online. While these have proved popular, they are often single-user learning environments which provide little in the way of interaction or stimulation for the student. As the concept of lifelong learning now becomes a reality and thus more and more people are partaking in online courses, researchers are constantly exploring innovative techniques to motivate online students and enhance the e-learning experience. This article presents our research in this area and the resulting development of CLEV-R, a Collaborative Learning Environment with Virtual Reality. This web-based system uses Virtual Reality (VR) and multimedia and provides communication tools to support collaboration among students. In this article, we describe the features of CLEV-R, its adaptation for mobile devices and present the findings from an initial evaluation.

Progressive Transmission of Vector Map Data over the World Wide Web

Within distributed computing environments, access to very large geospatial datasets often suffers from slow or unreliable network connections. To allow users to start working with a partially delivered dataset, progressive transmission methods are a viable solution. While incremental and progressive methods have been applied successfully to the transmission of raster images over the World Wide Web, and, in the form of prototypes, of triangular meshes, the transmission of vector map datasets has lacked a similar attention. This paper introduces a solution to the progressive transmission of vector map data that allows users to apply analytical GIS methods to partially transmitted data sets. The architecture follows a client-server model with multiple map representations at the server side, and a thin client that compiles transmitted increments into a topologically consistent format. This paper describes the concepts, develops an architecture, and discusses implementation concerns.

Exploratory spatio-temporal data mining and visualization

Spatio-temporal data sets are often very large and difficult to analyze and display. Since they are fundamental for decision support in many application contexts, recently a lot of interest has arisen toward data-mining techniques to filter out relevant subsets of very large data repositories as well as visualization tools to effectively display the results. In this paper we propose a data-mining system to deal with very large spatio-temporal data sets. Within this system, new techniques have been developed to efficiently support the data-mining process, address the spatial and temporal dimensions of the data set, and visualize and interpret results. In particular, two complementary 3D visualization environments have been implemented. One exploits Google Earth to display the mining outcomes combined with a map and other geographical layers, while the other is a Java3D-based tool for providing advanced interactions with the data set in a non-geo-referenced space, such as displaying association rules and variable distributions.

Geographic knowledge extraction and semantic similarity in OpenStreetMap

In recent years, a web phenomenon known as Volunteered Geographic Information (VGI) has produced large crowdsourced geographic data sets. OpenStreetMap (OSM), the leading VGI project, aims at building an open-content world map through user contributions. OSM semantics consists of a set of properties (called ‘tags’) describing geographic classes, whose usage is defined by project contributors on a dedicated Wiki website. Because of its simple and open semantic structure, the OSM approach often results in noisy and ambiguous data, limiting its usability for analysis in information retrieval, recommender systems and data mining. Devising a mechanism for computing the semantic similarity of the OSM geographic classes can help alleviate this semantic gap. The contribution of this paper is twofold. It consists of (1) the development of the OSM Semantic Network by means of a web crawler tailored to the OSM Wiki website; this semantic network can be used to compute semantic similarity through co-citation measures, providing a novel semantic tool for OSM and GIS communities; (2) a study of the cognitive plausibility (i.e. the ability to replicate human judgement) of co-citation algorithms when applied to the computation of semantic similarity of geographic concepts. Empirical evidence supports the usage of co-citation algorithms—SimRank showing the highest plausibility—to compute concept similarity in a crowdsourced semantic network.

Progressive vector transmission

Progressive transmission of raster images over the WorldWide Web has been successfully applied to provide the user with coarser versions of the data before downloading a complete image. On the other hand, in the vector domain progressive transmission is challenging. Increasing the level of detail of a vector dataset does not simply imply adding pixels to it. In this paper, we discuss issues related to the progressive transmission of vector maps. We also describe a model for multiple representations of maps that can be transmitted progressively.

Perspectives in Conceptual Modeling

First International Workshop on Best Practices of UML (BP-UML 2005).- Preface to BP-UML 2005.- Experience Reports and new Applications.- Current Practices in the Use of UML.- An Empirical Study of the Nesting Level of Composite States Within UML Statechart Diagrams.- Utilizing a Multimedia UML Framework for an Image Database Application.- Model Evaluation and Requirements Modeling.- Object Class or Association Class? Testing the User Effect on Cardinality Interpretation.- Organizing and Managing Use Cases.- A Comparative Analysis of Use Case Relationships.- Metamodeling and Model Driven Development.- Applying Transformations to Model Driven Development of Web Applications.- A Precise Approach for the Analysis of the UML Models Consistency.- A UML 2 Profile for Business Process Modelling.- Seventh International Bi-conference Workshop on Agent-Oriented Information Systems (AOIS-2005).- Preface to AOIS 2005.- Invited Talk.- Agent Oriented Data Integration.- Positions in Engineering Agent Oriented Systems.- AOSE and Organic Computing - How Can They Benefit from Each Other? Position Paper.- Modeling Dynamic Engineering Design Processes in PSI.- Agent Oriented Methodologies and Conceptual Modeling.- Preliminary Basis for an Ontology-Based Methodological Approach for Multi-agent Systems.- DDEMAS: A Domain Design Technique for Multi-agent Domain Engineering.- An Agent-Oriented Meta-model for Enterprise Modelling.- Agent Communication and Coordination.- An Approach to Broaden the Semantic Coverage of ACL Speech Acts.- Normative Pragmatics for Agent Communication Languages.- Experimental Comparison of Rational Choice Theory, Norm and Rights Based Multi Agent Systems.- Second International Workshop on Conceptual Modeling for Geographic Information Systems (CoMoGIS 2005).- Preface to CoMoGIS 2005.- Invited Talk.- Map Algebra Extended with Functors for Temporal Data.- Spatial and Spatio-temporal Data Representation.- A Formal Model for Representing Point Trajectories in Two-Dimensional Spaces.- A Logical Approach for Modeling Spatio-temporal Objects and Events.- Conceptual Neighbourhood Diagrams for Representing Moving Objects.- Spatial Relations.- A Refined Line-Line Spatial Relationship Model for Spatial Conflict Detection.- Assessing Topological Consistency for Collapse Operation in Generalization of Spatial Databases.- Spatial Relations for Semantic Similarity Measurement.- Spatial Queries, Analysis and Data Mining.- Approximate Continuous K Nearest Neighbor Queries for Continuous Moving Objects with Pre-defined Paths.- Spatio-temporal Similarity Analysis Between Trajectories on Road Networks.- Using Data Mining for Modeling Personalized Maps.- Data Modeling and Visualisation.- 3D Scene Modeling for Activity Detection.- SAMATS - Edge Highlighting and Intersection Rating Explained.- Applying Semantic Web Technologies for Geodata Integration and Visualization.- Sixth International Workshop on Conceptual Modeling Approaches for e-Business (eCOMO 2005).- Preface to eCOMO 2005.- Bargaining in E-Business Systems.- Conceptual Content Management for Enterprise Web Services.- Verifying Web Services Composition.- Towards Amplifying Business Process Reuse.- First International Workshop on Quality of Information Systems (QoIS 2005).- Preface to QoIS 2005.- Information System Models Quality.- Measuring the Perceived Semantic Quality of Information Models.- Situated Support for Choice of Representation for a Semantic Web Application.- Towards Systematic Model Assessment.- A Fuzzy Based Approach to Measure Completeness of an Entity-Relationship Model.- Quality Driven Processes.- Managing Information Quality in e-Science: A Case Study in Proteomics.- Tool Support and Specification Quality: Experimental Validation of an RE-Tool Evaluation Framework.- Improving Object-Oriented Micro Architectural Design Through Knowledge Systematization.- Tutorials.- Tutorial 1: eduWeaver - The Courseware Modeling Tool.- Tutorial 2: FOOM - Functional and Object Oriented Methodology: An Integrated Approach.- Tutorial 3: Domain Engineering - Using Domain Concepts to Guide Software Design.- Tutorial 4: Reasoning About Web Information Systems.- Tutorial 5: Schema and Data Translation.- Tutorial 6: Modeling and Simulation of Dynamic Engineering Design Processes.- Tutorial 7: Modeling Enterprise Applications.

A multigranular spatiotemporal data model

A large percentage of data managed by a variety of different application domains has spatiotemporal characteristics. Unfortunately, traditional geographical information systems do not allow for an easy representation of temporal aspects of spatial data. Moreover, they do not usually support the representation of data at multiple levels of granularity. In this paper we present a multigranular spatiotemporal data model. Our model extends the ODMG model with multiple spatial and temporal granularities. In particular, the model allows for an uniform management of two kinds of spatiotemporal objects: moving entities (e.g. cars, planes, etc.) and temporal maps (i.e., maps representing the change over time of a given geographic area). It also provides a framework for mapping the movement of an entity such as a car onto an underlying geographic area. The model we propose relies on a standard definition of temporal granularity. On the other hand, the representation of spatial entities at multiple granularities is obtained by applying model oriented map generalization principles. In particular, we consider a set of generalization operators that guarantee topological consistency.

A multigranular object‐oriented framework supporting spatio‐temporal granularity conversions

Several application domains require handling spatio‐temporal data. However, traditional Geographic Information Systems (GIS) and database models do not adequately support temporal aspects of spatial data. A crucial issue relates to the choice of the appropriate granularity. Unfortunately, while a formalisation of the concept of temporal granularity has been proposed and widely adopted, no consensus exists on the notion of spatial granularity. In this paper, we address these open problems, by proposing a formal definition of spatial granularity and by designing a spatio‐temporal framework for the management of spatial and temporal information at different granularities. We present a spatio‐temporal extension of the ODMG type system with specific types for defining multigranular spatio‐temporal properties. Granularity conversion functions are introduced to obtain attributes values at different spatial and temporal granularities.

Semantically enriching VGI in support of implicit feedback analysis

In recent years, the proliferation of Volunteered Geographic Information (VGI) has enabled many Internet users to contribute to the construction of rich and increasingly complex spatial datasets. This growth of geo-referenced information and the often loose semantic structure of such data have resulted in spatial information overload. For this reason, a semantic gap has emerged between unstructured geo-spatial datasets and high-level ontological concepts. Filling this semantic gap can help reduce spatial information overload, therefore facilitating both user interactions and the analysis of such interaction. Implicit Feedback analysis is the focus of our work. In this paper we address this problem by proposing a system that executes spatial discovery queries. Our system combines a semantically-rich and spatially-poor ontology (DBpedia) with a spatially-rich and semantically-poor VGI dataset (OpenStreetMap). This technique differs from existing ones, such as the aggregated dataset LinkedGeoData, as it is focused on user interest analysis and takes map scale into account. System architecture, functionality and preliminary results gathered about the system performance are discussed.

Towards a framework for mining and analysing spatio-temporal datasets

High‐resolution spatio‐temporal datasets are being collected every day to record the behaviour of several natural phenomena. However, data‐mining techniques are needed to extract relevant patterns from very large repositories and reveal spatial and temporal patterns in the behaviour of these phenomena. To this aim, we propose a system for mining data with spatial and temporal characteristics, and for visualizing and interpreting the results. Within this system, we have developed two complementary 3D visualization environments, one based on Google Earth and one relying on a Java3D graphical user interface. In this paper, we illustrate the main features of the system we have developed, and report on the main results we have obtained by analysing the Hurricane Isabel dataset.