<div class="csl-bib-body">
<div class="csl-entry">Wetz, P. (2016). <i>Semantic stream processing of environmental data</i> [Dissertation, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2016.39502</div>
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dc.identifier.uri
https://doi.org/10.34726/hss.2016.39502
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/3263
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dc.description
Zusammenfassung in deutscher Sprache
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dc.description.abstract
Whether we cope successfully or fail to deal with the world's environmental challenges will be determined in cities where, since 2008, more than half of the global population resides. Recently, also the application of computer science methods to solve environmental issues is increasingly promising. In this thesis we present an approach to enable citizens to make well-informed real time decisions based on environmental data. To this end, we leverage semantic web technologies as a practical means to overcome the obstacles of (i) environmental data integration, (ii) identifying data stream management engines to process real time environmental data, and (iii) enabling ecient use of environmental data streams for city stakeholders. We develop an ontology-based approach to integrate highly heterogeneous and dynamic environmental data sources. We present a novel vocabulary that combines and extends two de-facto standard vocabularies, that is, the Semantic Sensor Network Ontology and the RDF Data Cube Vocabulary. Further, we create a framework to evaluate suitable RDF Stream Processing (RSP) engines based on the special requirements of the environmental data domain, such as processing of high-frequency data, providing correct results, and scalability. This framework called YABench facilitates the identication of appropriate RSP engines under varying circumstances for scenarios in the environmental domain. After we identify C-SPARQL as a suitable RSP engine, we propose Linked Streaming Widgets. Linked Streaming Widgets represent lightweight semantic modules based on stream data, which can be combined to web applications by end users. By doing so, users can author their own mashups integrating environmental stream data sources, ultimately supporting well-informed decision making. We implement this concept as an extension of a mashup platform. To demonstrate its feasibility, we present and discuss two use cases based on citybike and air quality data, respectively, and perform performance evaluations indicating the practicability of Linked Streaming Widgets.
en
dc.language
English
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dc.language.iso
en
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dc.rights.uri
http://rightsstatements.org/vocab/InC/1.0/
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dc.subject
stream processing
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dc.subject
semantic web
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dc.subject
linked data
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dc.subject
RDF
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dc.subject
OWL
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dc.subject
mashups
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dc.title
Semantic stream processing of environmental data
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dc.type
Thesis
en
dc.type
Hochschulschrift
de
dc.rights.license
In Copyright
en
dc.rights.license
Urheberrechtsschutz
de
dc.identifier.doi
10.34726/hss.2016.39502
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dc.contributor.affiliation
TU Wien, Österreich
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dc.rights.holder
Peter Wetz
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dc.publisher.place
Wien
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tuw.version
vor
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tuw.thesisinformation
Technische Universität Wien
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dc.contributor.assistant
Kiesling, Elmar
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tuw.publication.orgunit
E188 - Institut für Softwaretechnik und Interaktive Systeme
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dc.type.qualificationlevel
Doctoral
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dc.identifier.libraryid
AC13325644
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dc.description.numberOfPages
177
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dc.identifier.urn
urn:nbn:at:at-ubtuw:1-6319
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dc.thesistype
Dissertation
de
dc.thesistype
Dissertation
en
dc.rights.identifier
In Copyright
en
dc.rights.identifier
Urheberrechtsschutz
de
tuw.advisor.staffStatus
staff
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tuw.assistant.staffStatus
exstaff
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tuw.advisor.orcid
0000-0002-8295-9252
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item.openaccessfulltext
Open Access
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item.openairecristype
http://purl.org/coar/resource_type/c_db06
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item.grantfulltext
open
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item.mimetype
application/pdf
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item.languageiso639-1
en
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item.openairetype
doctoral thesis
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item.fulltext
with Fulltext
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item.cerifentitytype
Publications
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crisitem.author.dept
E188 - Institut für Softwaretechnik und Interaktive Systeme