Privacy-Preserving Reengineering of Model-View-Controller Application Architectures Using Linked Data

When a legacy system’s software architecture cannot be redesigned, implementing additional privacy requirements is often complex, unreliable and costly to maintain. This paper presents a privacy-by-design approach to reengineer web applications as linked data-enabled and implement access control and privacy preservation properties. The method is based on the knowledge of the application architecture, which for the Web of data is commonly designed on the basis of a model-view-controller pattern. Whereas wrapping techniques commonly used to link data of web applications duplicate the security source code, the new approach allows for the controlled disclosure of an application’s data, while preserving non-functional properties such as privacy preservation. The solution has been implemented and compared with existing linked data frameworks in terms of reliability, maintainability and complexity

A Web GIS-based Integration of 3D Digital Models with Linked Open Data for Cultural Heritage Exploration

This PhD project explores how geospatial semantic web concepts, 3D web-based visualisation, digital interactive map, and cloud computing concepts could be integrated to enhance digital cultural heritage exploration; to offer long-term archiving and dissemination of 3D digital cultural heritage models; to better interlink heterogeneous and sparse cultural heritage data. The research findings were disseminated via four peer-reviewed journal articles and a conference article presented at GISTAM 2020 conference (which received the ‘Best Student Paper Award’)

Semantic data mining and linked data for a recommender system in the AEC industry

Even though it can provide design teams with valuable performance insights and enhance decision-making, monitored building data is rarely reused in an effective feedback loop from operation to design. Data mining allows users to obtain such insights from the large datasets generated throughout the building life cycle. Furthermore, semantic web technologies allow to formally represent the built environment and retrieve knowledge in response to domain-specific requirements. Both approaches have independently established themselves as powerful aids in decision-making. Combining them can enrich data mining processes with domain knowledge and facilitate knowledge discovery, representation and reuse. In this article, we look into the available data mining techniques and investigate to what extent they can be fused with semantic web technologies to provide recommendations to the end user in performance-oriented design. We demonstrate an initial implementation of a linked data-based system for generation of recommendations

A holistic approach for semantic-based game generation

The Web contains vast sources of content that could be reused to reduce the development time and effort to create games. However, most Web content is unstructured and lacks meaning for machines to be able to process and infer new knowledge. The Web of Data is a term used to describe a trend for publishing and interlinking previously disconnected datasets on the Web in order to make them more valuable and useful as a whole. In this paper, we describe an innovative approach that exploits Semantic Web technologies to automatically generate games by reusing Web content. Existing work on automatic game content generation through algorithmic means focuses primarily on a set of parameters within constrained game design spaces such as terrains or game levels, but does not harness the potential of already existing content on the Web for game generation. We instead propose a holistic and more generally-applicable game generation solution that would identify suitable Web information sources and enrich game content with semantic meta-structures.The research work disclosed in this publication is partially funded by the REACH HIGH Scholars Programme — Post- Doctoral Grants. The grant is part-financed by the European Union, Operational Programme II — Cohesion Policy 2014- 2020 Investing in human capital to create more opportunities and promote the wellbeing of society — European Social Fund.peer-reviewe

Linked Open Data - Creating Knowledge Out of Interlinked Data: Results of the LOD2 Project

Database Management; Artificial Intelligence (incl. Robotics); Information Systems and Communication Servic

A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web

Over the past decade, rapid advances in web technologies, coupled with innovative models of spatial data collection and consumption, have generated a robust growth in geo-referenced information, resulting in spatial information overload. Increasing 'geographic intelligence' in traditional text-based information retrieval has become a prominent approach to respond to this issue and to fulfill users' spatial information needs. Numerous efforts in the Semantic Geospatial Web, Volunteered Geographic Information (VGI), and the Linking Open Data initiative have converged in a constellation of open knowledge bases, freely available online. In this article, we survey these open knowledge bases, focusing on their geospatial dimension. Particular attention is devoted to the crucial issue of the quality of geo-knowledge bases, as well as of crowdsourced data. A new knowledge base, the OpenStreetMap Semantic Network, is outlined as our contribution to this area. Research directions in information integration and Geographic Information Retrieval (GIR) are then reviewed, with a critical discussion of their current limitations and future prospects

Linked Data based Health Information Representation, Visualization and Retrieval System on the Semantic Web

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.To better facilitate health information dissemination, using flexible ways to represent, query and visualize health data becomes increasingly important. Semantic Web technologies, which provide a common framework by allowing data to be shared and reused between applications, can be applied to the management of health data. Linked open data - a new semantic web standard to publish and link heterogonous data- allows not only human, but also machine to brows data in unlimited way. Through a use case of world health organization HIV data of sub Saharan Africa - which is severely affected by HIV epidemic, this thesis built a linked data based health information representation, querying and visualization system. All the data was represented with RDF, by interlinking it with other related datasets, which are already on the cloud. Over all, the system have more than 21,000 triples with a SPARQL endpoint; where users can download and use the data and – a SPARQL query interface where users can put different type of query and retrieve the result. Additionally, It has also a visualization interface where users can visualize the SPARQL result with a tool of their preference. For users who are not familiar with SPARQL queries, they can use the linked data search engine interface to search and browse the data. From this system we can depict that current linked open data technologies have a big potential to represent heterogonous health data in a flexible and reusable manner and they can serve in intelligent queries, which can support decision-making. However, in order to get the best from these technologies, improvements are needed both at the level of triple stores performance and domain-specific ontological vocabularies

An Adaptive Approach for Interlinking Georeferenced Data

International audienceThe resources published on the Web of data are often described by spatial references such as coordinates. The common data linking approaches are mainly based on the hypothesis that spatially close resources are more likely to represent the same thing. However, this assumption is valid only when the spatial references that are compared have been produced with the same positional accuracy, and when they actually represent the same spatial characteristic of the resources captured in an unambiguous way. Otherwise, spatial distance-based matching algorithms may produce erroneous links. In this article, we first suggest to formalize and acquire the knowledge about the spatial references, namely their positional accuracy, their geometric modeling, their level of detail, and the vagueness of the spatial entities they represent. We then propose an interlinking approach that dynamically adapts the way spatial references are compared, based on this knowledge