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The Data on the Web Best Practices Working Group, as part of W3C Data Activity, is standardizing the Data Quality Vocabulary (DQV) for expressing data quality of datasets published on the Web. By exploiting such DQV-based quality metadata associated to the datasets in a data portal, data consumers can achieve data quality-based filtering and ranking of datasets on the portal's conventional search...
The proliferation of soft information sources has led to an explosion of data while creating fertile grounds to obtain actionable insights. In such an unstructured data environment, the fundamental challenge is to discover topics and latent relationships, indicating significant events, in an unsupervised manner from multiple sources. The extracted topics and relationships then provide evidence for...
In the context of large engineering projects the effective and efficient exchange and versioning of information from different engineering disciplines is essential. Semantic data integration approaches provide the necessary means to overcome the gap between heterogeneous local engineering tool concepts and common project-level concepts which enable the mapping of engineering data coming from different...
The biggest challenges in the area of AAL service development is heterogeneity. Possible solution to accommodate dynamic behavior of AAL system needs and diversity of system requirements is to use higher level of system abstraction by using ontology. We describe a development methodology, structure, format selection and evaluation of a proposed AAL ontology building on top of well established ontologies...
Semantic Web technologies are being applied more and more in business context applications. The domain of Business Process Management (BPM) is no exception. Additionally, Linked Data principles become interesting to apply in this context as well to enrich processes with information from more diverse sources. We aim to apply Semantic Web technologies and Linked Data principles to enhance Business Process...
In order to easily query and blend structured data on the web a query formulation language is presented. The core novelty of this is that it permits people with restricted IT skills to explore and query one (or multiple) data sources without prior knowledge about the schema, structure, terminology, or any technological details of these sources. Data source considered may be either an offline or inline...
The Internet of Things (IoT) has given rise to new types of data, emerging for instance from the collection of sensor data and the control of actuators. The explosion of devices that have automated and perhaps improved the lives of all of us has generated a huge mass of information that will continue to grow exponentially. For this reason the need to store, manage, and treat the ever increasing amounts...
Nowadays, more and more people rely on freely available user-generated spatial content, known as Volunteered Geographic Information (VGI). Therefore, spatial data creation is no more exclusively in the hands of professionals and Linked Open Data (LOD) techniques have a role in promoting such online and freely accessible spatial information. However, the volume of VGI data is constantly growing so...
Within the enterprise, domain-specific knowledge is often recorded by IT processes or employees in the form of noisy, unstructured data. The question then arises on how to gain actionable insight from the volumes of un-structured data in order to improve the bottom line in an effective and timely manner. In this paper we propose a method on how to approach the issue within the realm of software license...
The increasing popularity of the Web of Data is motivating the need to integrate semantic-web ontologies. Data exchange is one integration approach that aims to populate a target ontology using data that come from one or more source ontologies. Currently, there exist a variety of systems that are suitable to perform data exchange among these ontologies; unfortunately, they have uneven performance,...
Nowadays personalised service provisioning becomes more feasible due to the increasing availability of smart devices, such as smart phones, tablet computers, Personal Digital Assistants and Play stations. These smart devices can dynamically detect the context data and upload them to support other interesting software applications, such as Facebook and Google maps. Context can become richer and more...
Recently, the number and size of RDF data collections has increased rapidly making the issue of scalable processing techniques crucial. The MapReduce model has become a de facto standard for large scale data processing using a cluster of machines in the cloud. Generally, RDF query processing creates join-intensive workloads, resulting in lengthy MapReduce workflows with expensive I/O, data transfer,...
Data as a Service (DaaS) builds on service-oriented technologies to enable fast access to data resources on the Web. However, this paradigm raises several new concerns that traditional privacy models for Web services do not handle. First, the distinction between the roles of service providers and data providers is unclear, leaving the latter helpless for specifying and verifying the enforcement of...
In this paper we present a general framework to describe a trace-based learner modelling process. This framework includes three knowledge models: the first model is an explicit representation of observations about learner's interactions with a TEL-system, the second model describes the structure and elements describing the Learner Model and the last model describes the main knowledge elements types...
Context data-driven approach refers to the process of collecting and storing context data from a wide range of context sources as sensors and Web services. This approach differs from existing context-aware applications, where context models and applications are closely related and ignore how the context is derived from sources and interpreted. In this paper, we propose a context data model based on...
The specification of clinical items is a fundamental problem in the planning of a clinical trial. In this paper we present an approach that uses an RDF model in combination with a suite of OWL ontologies to formally describe the structural and conceptual composition of items. We argue that a semantic Web data model is more flexible than traditional relational models and therefore more appropriate...
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