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 \chapter{Conclusion and future work}
 \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.
+In many cases, time series are geotagged data containing sensitive personal details, and thus their processing entails privacy concerns.
+
+The processing/publishing of time series that contain user-generated data, may not only pose privacy risks to the individuals involved but also deteriorate arbitrarily the data utility.
+To this end, differential privacy is the most prominent privacy method that can efficiently balance between user protection and data utility.
+
+In this thesis, we have concentrated on continuous user-generated data publishing.
+We have studied the relevant literature with special emphasis on data correlation.
+Furthermore, we explored ways to provide configurable protection in such settings and developed relevant solutions.
+
+Next, we summarize this thesis in the individual chapters by describing our contribution to the problems surrounding quality and privacy in user-generated Big Data.
+Subsequently, we discuss interesting perspectives and open questions for future investigation.
+
 
 \input{conclusion/summary}
 \input{conclusion/perspectives}