Jean Paul Calbimonte Perez

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RDF and SPARQL are established standards for data interchange and querying on the Web. While they have been shown to be useful and applicable in many scenarios, they are not sufficiently adequate for dealing with streams of data and their intrinsic continu ...

Sensor networks are increasingly being deployed in the environment for many different purposes. The observations that they produce are made available with heterogeneous schemas, vocabularies and data formats, making it difficult to share and reuse this dat ...

Diabetes Type 1 is a metabolic disease which results in a lack of insulin production, causing high glucose levels in the blood. It is crucial for diabetic patients to balance this glucose level, and they depend on external substances to do so. In order to ...

Despite the proliferation of Internet-of-Things (IoT) platforms for building and deploying IoT applications in the cloud, there is still no easy way to integrate heterogeneous geographically and administratively dispersed sensors and IoT services in a sema ...

Ontologies provide conceptual abstractions over data, in domains such as the Internet of Things, in a way that sensor data can be harvested and interpreted by people and applications. The Semantic Sensor Network (SSN) ontology is the de-facto standard for ...

Air pollution is one of the key indicators for quality of life in urban environments, and is also the subject of global health concern, given the number of mortal diseases associated to exposure to pollutants. Assessing and monitoring air quality is an imp ...

The availability of massive volumes of data and recent advances in data collection and processing platforms have motivated the development of distributed machine learning algorithms. In numerous real-world applications large datasets are inevitably noisy a ...

Events on the Web are increasingly being produced in the form of data streams, and are present in many different scenarios and applications such as health monitoring, environmental sensing or social networks. The heterogeneity of event streams has raised t ...

Sensor network deployments are a primary source of massive amounts of data about the real world that surrounds us, measuring a wide range of physical properties in real time. However, in large-scale deployments it becomes hard to eectively exploit the data ...

The dramatic rise of time-series data produced in a variety of contexts, such as stock markets, mobile sensing, sensor networks, data centre monitoring, etc., has fuelled the development of large-scale distributed real-time computation systems (e.g., Apach ...

The Semantic Web brings a powerful set of concepts, standards and ideas that are already changing the shape of the Web. However, in order to put these notions into practice we need to translate them into code. That is why the broad notion of programming th ...

Diabetic patients are dependent on external substances to balance their blood glucose level. In order to control this level, they historically needed to sample a drop a blood from their hand and have it analyzed. Recently, other directions emerged to offer ...

Processing data streams is increasingly gaining momentum, given the need to process these flows of information in real-time and at Web scale. In this context, RDF Stream Processing (RSP) and Stream Reasoning (SR) have emerged as solutions to combine semant ...

Jean Paul Calbimonte Perez

Chattez avec Graph Search

RSP-QL Semantics: a Unifying Query Model to Explain Heterogeneity of RDF Stream Processing Systems

Enabling Query Technologies for the Semantic Sensor Web

Semantic representation and processing of hypoglycemic events derived from wearable sensor data

OpenIoT: Open Source Internet-of-Things in the Cloud

The Schema Editor of OpenIoT for Semantic Sensor Networks

Semantic Data Layers in Air Quality Monitoring for Smarter Cities

Efficient Distributed Decision Trees for Robust Regression

Reactive Processing of RDF Streams of Events

Semantic Sensor Data Search in a Large-Scale Federated Sensor Network

Deriving Semantic Sensor Metadata from Raw Measurements

SigCO: Mining Significant Correlations via a Distributed Real-time Computation Engine

Scalable and Reactive Programming for Semantic Web Developers

Detection of hypoglycemic events through wearable sensors

Semantic and Sensitivity Aware Location-Privacy Protection for the Internet of Things

TripleWave: Spreading RDF Streams on the Web

Toward Self-monitoring Smart Cities: the OpenSense2 Approach

XGSN: An Open-source Semantic Sensing Middleware for the Web of Things