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Effiziente Datenminimierung im Gebäude- und Quartierssektor

Authors: Rupp, Valentin; Heumüller, Julie; von Grafenstein, Maximilian;

Effiziente Datenminimierung im Gebäude- und Quartierssektor

Abstract

Beim Einsatz digitaler Anwendungen im Gebäude- und Quartierssektor lassen in diesem Rahmen verarbeitete Datensätze zu Raumklima, Energieverbrauch und sonstigen gebäudebezogenen Daten häufig Rückschlüsse auf das Verhalten von Einzelpersonen oder Personengruppen zu. Beziehen sich diese Daten auf eine identifizierte oder identifizierbare Person, findet das nationale bzw. europäische Datenschutzrecht Anwendung und mit ihm die gesamte Bandbreite rechtlicher Verpflichtungen des Verantwortlichen. Ziel des Datenschutzrechts ist es dabei, die Betroffenen vor Risiken zu schützen, die durch die Datenverarbeitung verursacht werden und ihnen damit grundsätzlich die Entscheidung über das Maß und dem Umgang mit diesen Risiken zu gewähren. Da das Datenschutzrecht dies an den sehr unbestimmten Begriff des personenbezogenen Datums knüpft, ist bei vielen Anwendungen dabei nicht von vornherein absehbar, welche tatsächlichen und rechtlichen Folgen im konkreten Fall an eine Verarbeitung der Daten geknüpft sind. Die vorliegende Visualisierung soll daher der Erläuterung dienen, wie anhand einer Berücksichtigung von Risiken für Betroffene der Personenbezug von Daten ermittelt und durch den Einsatz technisch-organisatorischer Maßnahmen möglichst weitgehend minimiert werden kann. Auf diese Weise wird einerseits der rechtlichen Verpflichtung eines effektiven Schutzes von Betroffenen Rechnung getragen. Andererseits können digitale Anwendungen mit einer höheren Rechts- und damit Planungssicherheit betrieben werden.

Keywords

Smart Home, Energiewende, Gebäude, Data Governance, Datenschutz, Energiewendebauen, Quartier, Data Protection, Privacy by Design

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  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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download
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
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149
104
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