Projects

essence

ESSENCE

The ESSENCE consortium aims to bring human perspectives into a smart city platform that collects many media types, from personal devices and public displays to augmented reality. The ultimate goal is to create interactive stories embedded in the city environment about civic actions that boost engagement in these projects.

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daiquiri

DAIQUIRI

The DAIQUIRI project will develop AI algorithms that address current challenges associated with data overload, sensor-video matching, dynamic captioning and multi-modal stories. The outcome will be a sensor data platform and dashboard that supports media professionals in their live sports coverage and the audiences' viewing experiences.

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dyversify

DyVerSIFy

The DyVerSIFy project aims to develop software components and methodologies in the domains of dynamic visualization, adaptive anomaly detection and scalability to drive dynamic, adaptive and scalable sensor analytics.

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ecodalo

EcoDaLo

Media companies in Flanders today have fragmented consumer data, with each company maintaining its own data management platform. As a result, data remains largely undervalorized. The EcoDaLo project aims to develop a knowledge platform for publishers allowing the integration of many diverse data sources.

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dissect

DiSSeCt

DiSSeCt aims to design distributed semantic software solutions and algorithms for continuous exchange of huge streams of data between different partners in specific ecosystems. By converting data to knowledge, and exchanging this knowledge in an intelligent, secure and dynamic manner, personalised and context-aware services can be offered to end-users.

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hello jenny

Hello Jenny

Hello Jenny aims to help senior citizens who have no or limited contact with friends or family. It does this by providing a smart speaker to the senior citizen which allows them to schedule a visit with their assigned buddy. An analysis is performed to determine when a senior needs a visit and suggests this to the senior if this is the case.

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mos2s

MOS2S

The MOS2S project focuses on media orchestration platforms and technologies that allow devices, data and media streams to be orchestrated into a rich and coherent media experience on various end-user devices. Applications include crowd journalism and live events (experience and entertainment).

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combust

COMBUST

The opportunities of big data are tremendous. However, it is still a major challenge to combine available data from various heterogeneous sources and put it on offer in a way that is reliable, trustworthy and a good business case for the data owners. The COMBUST project was set up to create solutions and guidelines for this data fusion challenge, in a realistic setting and in view of offering a valuable data service.

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Use cases

covid 19 knowledge graph

COVID 19 Knowledge Graph

This use case generates a knowledge graph from the COVID-19 literature. It uses YARRRML, which is converted to RML, to define how the knowledge graph is generated based on the metadata of the literature. Matey is used to assist in defining the YARRRML rules and the RMLMapper is used to execute the RML rules to generate the knowledge graph.

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ERA

European Union Agency for Railways

The European Union Agency for Railways (ERA) generates a knowledge graph to foster interoperability across their base registry databases which are populated by all EU member states and different actors from the railway domain. This use case uses YARRRML, which is automatically converted to RML, to define how the knowledge graph is generated based on different data sources, such as databases, CSV files, XML files, and so on. The RMLMapper is used to execute the RML rules to generate the knowledge graph, which can be explored and queried online.

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between our worlds

Between Our Worlds

Between Our Worlds is an initiative to provide metadata information about anime as Linked Open Data. It uses YARRRML, which is converted to RML, to define how the knowledge graph is generated based on the metadata downloaded from a Web API. FnO is used to transform certain aspects of the original data. The RMLMapper is used to execute the RML rules to generate the knowledge graph.

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