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An ever-increasing number of real-life applications produce spatio-temporal data that record the position of moving objects (persons, cars, vessels, aircrafts, etc.). In order to provide integrated views with other relevant data sources (e.g., weather, vessel databases, etc.), this data is represented in RDF and stored in knowledge bases with the following notable features: (a) the data is dynamic, since new spatio-temporal data objects are recorded every second, and (b) the size of the data is vast and can easily lead to scalability issues. As a result, this raises the need for efficient management of large-scale, dynamic, spatio-temporal RDF data. In this paper, we propose boosting the performance of spatio-temporal RDF queries by compressing the spatio-temporal information of each RDF entity into a unique integer value. We exploit this encoding in a filter-and-refine framework for processing of spatio-temporal RDF data efficiently. By means of an extensive evaluation on real-life data sets, we demonstrate the merits of our framework.
", "funding": [ { "award": { "acronym": "datACRON", "id": "00k4n6c32::687591", "identifiers": [ { "identifier": "https://cordis.europa.eu/projects/687591", "scheme": "url" } ], "number": "687591", "program": "H2020", "title": { "en": "Big Data Analytics for Time Critical Mobility Forecasting" } }, "funder": { "id": "00k4n6c32", "name": "European Commission" } } ], "publication_date": "2019-04-08", "publisher": "Zenodo", "resource_type": { "id": "publication-conferencepaper", "title": { "de": "Konferenzbeitrag", "en": "Conference paper" } }, "subjects": [ { "subject": "Spatio-temporal RDF, query processing, encoding" } ], "title": "Efficient Spatio-temporal RDF Query Processing in Large Dynamic Knowledge Bases" }, "parent": { "access": { "owned_by": { "user": 31009 } }, "communities": { "entries": [ { "access": { "member_policy": "open", "members_visibility": "restricted", "record_policy": "open", "review_policy": "closed", "visibility": "public" }, "children": { "allow": true }, "created": "2022-11-23T15:53:29.436323+00:00", "custom_fields": {}, "deletion_status": { "is_deleted": false, "status": "P" }, "id": "f0a8b890-f97a-4eb2-9eac-8b8a712d3a6c", "links": {}, "metadata": { "curation_policy": "The EU Open Research Repository serves as a repository for research outputs (data, software, posters, presentations, publications, etc) which have been funded under an EU research funding programme such as Horizon Europe, Euratom or earlier Framework Programmes.
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", "description": "Open repository for EU-funded research outputs from Horizon Europe, Euratom and earlier Framework Programmes.", "organizations": [ { "id": "00k4n6c32" } ], "page": "The EU Open Research Repository is a Zenodo-community dedicated to fostering open science and enhancing the visibility and accessibility of research outputs funded by the European Union. The community is managed by CERN on behalf of the European Commission.
\nThe mission of the repository is to support the implementation of the EU's open science policy, providing a trusted and comprehensive space for researchers to share their research outputs such as data, software, reports, presentations, posters and more. The EU Open Research Repository simplifies the process of complying with open science requirements, ensuring that research outputs from Horizon Europe, Euratom, and earlier Framework Programmes are freely accessible, thereby accelerating scientific discovery and innovation.
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