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conclusion: Reviewed intro

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Manos Katsomallos 2021-11-29 06:08:03 +01:00
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\chapter{Conclusion and future work} \chapter{Conclusion and future work}
\label{ch:con} \label{ch:con}
Continuous publishing of data, also known as time series, has found over the past decades several application domains, including healthcare, smart building, and traffic monitoring. Continuous publishing of data, also known as time series, has found over the past decades several application domains, including healthcare, smart building, and traffic monitoring.
In many cases, time series contain personal details (and are usually geotagged), and thus their processing entails privacy concerns. In many cases, time series contain personal details, which are usually geotagged, and thus their processing entails privacy concerns.
%The processing/publishing of user-generated data in the form of time series, poses privacy risks to the individuals involved.\kat{the deterioration of the quality that we deal with here, is because of the privacy protection of the data, not because of the processing/publishing. I rephrased, together with the next sentence.} %The processing/publishing of user-generated data in the form of time series, poses privacy risks to the individuals involved.\kat{the deterioration of the quality that we deal with here, is because of the privacy protection of the data, not because of the processing/publishing. I rephrased, together with the next sentence.}
Several methods have been proposed in order to protect the privacy of individuals while processing their data, but cannot avoid to deteriorate arbitrarily the quality therein. Out of these methods, we distinguish differential privacy, which quantifies the balance between user protection and data utility by a factor $\epsilon$. Several methods have been proposed in order to protect the privacy of individuals while processing their data, but cannot avoid to deteriorate arbitrarily the quality therein. Out of these methods, we distinguish differential privacy, which quantifies the balance between user protection and data utility by a factor $\varepsilon$.
In this thesis, we have concentrated on continuous user-generated data publishing. In this thesis, we have concentrated on continuous user-generated data publishing.
% \kat{say exactly what case you covered, this is way to general. and connect it to the differential privacy that you previously mentioned, otherwise it seems irrelevant.} % \kat{say exactly what case you covered, this is way to general. and connect it to the differential privacy that you previously mentioned, otherwise it seems irrelevant.}
@ -15,7 +15,7 @@ Next, we summarize this thesis in the individual chapters by describing our cont
% quality and privacy in user-generated Big Data % quality and privacy in user-generated Big Data
% \kat{??? be specific, this is the conclusions chapter. 'The problems surrounding quality and privacy in user-generated Big Data ' means nothing.. } % \kat{??? be specific, this is the conclusions chapter. 'The problems surrounding quality and privacy in user-generated Big Data ' means nothing.. }
quality and privacy in continuous data publishing. quality and privacy in continuous data publishing.
Subsequently, we discuss interesting perspectives and open questions for future investigation. Subsequently, we discuss interesting perspectives and open questions for future research.
\input{conclusion/summary} \input{conclusion/summary}