Zobrazeno 1 - 10
of 199
pro vyhledávání: '"semantic data integration"'
Autor:
Bernd Bayerlein, Markus Schilling, Henk Birkholz, Matthias Jung, Jörg Waitelonis, Lutz Mädler, Harald Sack
Publikováno v:
Materials & Design, Vol 237, Iss , Pp 112603- (2024)
Knowledge representation in the Materials Science and Engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant (consistent) and variant (context-specific) knowledge are
Externí odkaz:
https://doaj.org/article/0996934a9ff040c69b75e43cc12b6778
Akademický článek
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Publikováno v:
Big Data and Cognitive Computing, Vol 7, Iss 1, p 21 (2023)
Semantic data integration provides the ability to interrelate and analyze information from multiple heterogeneous resources. With the growing complexity of medical ontologies and the big data generated from different resources, there is a need for in
Externí odkaz:
https://doaj.org/article/bf9a1f79ae304ec89400bed3d840f84f
Publikováno v:
Biology Direct, Vol 14, Iss 1, Pp 1-17 (2019)
Abstract Background Recently high-throughput technologies have been massively used alongside clinical tests to study various types of cancer. Data generated in such large-scale studies are heterogeneous, of different types and formats. With lack of e
Externí odkaz:
https://doaj.org/article/d4b498a516544aa684d2a3f9fedc5c8c
Akademický článek
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Publikováno v:
ISPRS International Journal of Geo-Information, Vol 11, Iss 2, p 149 (2022)
Semantic technologies have proven their relevance in facilitating the interpretation of Earth Observation (EO) data through formats such as RDF and reusable models, especially for the representation of space and time. While rasters are the usual data
Externí odkaz:
https://doaj.org/article/31e6f55f1a6a46d4a5a3261c0ac4abfa
Autor:
Hansi Zhang, Yi Guo, Qian Li, Thomas J. George, Elizabeth Shenkman, François Modave, Jiang Bian
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 18, Iss S2, Pp 129-147 (2018)
Abstract Background Cancer is the second leading cause of death in the United States, exceeded only by heart disease. Extant cancer survival analyses have primarily focused on individual-level factors due to limited data availability from a single da
Externí odkaz:
https://doaj.org/article/19466a0e94b04b2b90a43aa06457525e
Autor:
Navarro Gallinad, Albert
Citation. Navarro Gallinad, Albert, A Usable Knowledge Graph Framework for Linking Health Events with Environmental Data, Trinity College Dublin, School of Computer Science & Statistics, Computer Science, 2023. http://hdl.handle.net/2262/102971 Abstr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7caaf60a84b423a3c46f3e288886ed49
Autor:
Yannis Tzitzikas, Carlo Allocca, Chryssoula Bekiari, Yannis Marketakis, Pavlos Fafalios, Martin Doerr, Nikos Minadakis, Theodore Patkos, Leonardo Candela
Publikováno v:
Program, 2016, Vol. 50, Issue 1, pp. 16-40.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/PROG-10-2014-0072
Autor:
Jarabo Peñas, Alejandro
This thesis presents the design and prototype implementation of a digital twin based on a knowledge graph for Internet of Things (IoT) platforms. The digital twin is a virtual representation of a physical object or system that must continually integr
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-329198