Omar Boucelma

A new Spatial OLAP approach for the analysis of Volunteered Geographic Information

Abstract Volunteered Geographic Information (VGI) has great potential for enhancing analysts’ capabilities, assuming that VGI data quality issues, such as credibility and precision, are properly addressed. In this paper, we study the integration of VGI in Spatial OLAP (SOLAP) systems, which allow the integration and analysis of large volumes of good quality data. Using a real-world scenario, we highlight some similarities and differences among these two types of systems. We define a conceptual quality-oriented framework for warehousing and OLAPing VGI data. In particular, to address precision and credibility problems related to VGI data, we propose two new ETL operators: aggregation based on the VGI credibility and a filter based on the historical precision. We also define a new spatio-multidimensional model that provides decision makers with a global description of the quality of the aggregated data. To validate our proposal, we extend the classical relational SOLAP architecture using a standard VGI system.

Learning Content Adaptation for m-Learning Systems: A Multimodality Approach

The ubiquitous availability of mobile communication devices which are connected to the Internet makes it possible to dedicate small amounts of spare time for mobile learning. The limited screen size and resolution makes current mobile devices quite hard to visualize multifaceted Web pages, so this kind of content could be adjusted to meet the device needs. Adjustment in e-Learning means the contextualization of learning contents for m-Learning usage. In this paper, we present a design and implementation of a Web service-based system for adapting, displaying and manipulating learning objects on small handheld devices. A speech solution allows learners to turn any written text into natural speech files, in using standard voices. Our approach allows generation of text and audio based learning material dynamically for m-Learning and ubiquitous access. The deployment of audio data to the Web user via progressive download is also presented.

From Volunteered Geographic Information to Volunteered Geographic OLAP: A VGI Data Quality-Based Approach

Volunteered Geographic Information (VGI) represents a valuable source of information. At the same time this data presents new data quality issues such as credibility. In this paper, we investigate the integration of VGI in Spatial OLAP (SOLAP) systems, which allow analyzing huge volume of geographic datasets. By means of a real case study, we highlight the similarities and differences of these two kinds of systems. We propose a methodology to handle VGI data quality issues during the warehousing and OLAPing phases. In particular, we define a new aggregation ETL operator based on the VGI credibility. We also present a spatio-multidimensional model that provides decision-makers with a general description of the correctness of the SOLAP aggregations.

Multimodality and Context Adaptation for Mobile Learning

The new e-Learning 2.0 approach combines the use of social software, complementary tools, and mobile Web services to support the creation of ad hoc learning communities. The ubiquitous availability of mobile communication devices which are connected to the Internet makes it possible to use small amounts of spare time for mobile learning. The limited screen size and resolution makes current mobile devices quite hard to visualize multifaceted Web pages, so this kind of content could be adjusted to meet the device needs. This means the contextualization of learning contents for m-Learning usage. A Web services-based framework is presented for adapting, displaying, and manipulating learning objects on small handheld devices. A speech solution allows learners to turn any written text into natural speech files, using standard voices.

Flexible Matchmaking for RESTful Web Services

This paper describes a flexible matchmaking approach that relies on an extensible set of schema/ontology matching techniques and primitives that may be combined in various ways, accordingly with the specification of a service request. The approach has been implemented and tested against a collection of RESTFul web services described in hRESTS microformat.

Trusting the Cloud: A PROV + RBAC Approach

This paper describes a provenance-based access control system for the cloud. The system relies on provenance (PROV-DM, PROV-O) and access-control models (RBAC) together with a distributed rule-based mechanism. The system allows rule propagation (in the cloud) and uses a central execution engine for enforcing security and trustworthiness. This paper provides a comparison between PROV-DM and PROV-O in terms of efficiency and expressiveness regarding Provenance graphs.

Provenance Monitoring in the Cloud

The provenance of workflow is an important supportive component of workflows that concerns the knowledge sharing, product reusability, and process verification. Cloud computing brings new application opportunities and, along with them, associated research challenges, such as integrity, privacy, security, and related legal problems. In this talk, we describe an approach and a system for monitoring data/workflow provenance, with the goal of ensuring/assessing cloud security. The approach relies on (1) OPM, the Open Provenance Model for the specification of provenance, (2) Colored Petri Net (CPN) for diagnosis purposes, and (3) Web Service Security policies (WS-S) which are integrated as part of workflow tasks in order to simulate security checkpoints.

Web Services Discovery and Composition: A Schema Matching Approach

Automated matching of service descriptions is the key to service discovery and composition. In this paper, we propose an approach for web services discovery and composition. The approach relies on (1) SAWSDL, a simple and generic annotation language, (2) an XML representation of a web service that carries both syntactic (e.g., WSDL) and semantic (e.g., SAWSDL) information, and (3) the reuse of available schema matchers. The approach departs from exiting ones because it does not advocate a specific matchmaking algorithm, and it promotes the combination of different schema matchers, allowing multiple discovery and composition strategies.

A Multigraph Approach for Web Services Recommendation

In this paper, we describe a Web services recommendation approach where the services’ ecosystem is represented as a heterogeneous multigraph, and edges may have different semantics. The recommendation process relies on clustering techniques to suggest services “of interest” to a user. Our approach has been implemented as a tool called WesReG (Web services Recommendation with Graphs) on top of Neo4j and its cypher query language. We present the system implementation details and present the results of experiments on a collection of real Web services.

Modeling and Retrieving Linked RESTful APIs: A Graph Database Approach

This paper describes an approach that combines Linked Data and Graph Database concepts for modeling and retrieving RESTFul Linked APIs Web APIs. We propose a multi-levels graph structure where the Web APIs vertices are connected by means of different types of links: The graph is stored in a graph database to allow graph exploration, e.g., to achieve an API discovery task for instance. The exploration/retrieval process is performed by means of graph queries: on the user client side, a keyword search interface is provided while, on the server side graph database, a graph query is issued. The approach has been implemented on top of Neo4j and its cypher query language, and an experimentation has been conducted with real datasets.