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diff --git a/docs/TR-20210730212057-IA-WDS-CG/main.pdf b/docs/TR-20210730212057-IA-WDS-CG/main.pdf
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--- a/docs/TR-20210730212057-IA-WDS-CG/main.pdf
+++ b/docs/TR-20210730212057-IA-WDS-CG/main.pdf
diff --git a/docs/TR-20210730212057-IA-WDS-CG/main.tex b/docs/TR-20210730212057-IA-WDS-CG/main.tex
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--- a/docs/TR-20210730212057-IA-WDS-CG/main.tex
+++ b/docs/TR-20210730212057-IA-WDS-CG/main.tex
@@ -246,6 +246,19 @@ time limited. Map and reduce operations are parallelized and certain processing
 steps can process 100K documents per second or even more on commodity hardware
 with spinning disks.
 
+\section{Quality Assurance}
+
+Understanding data quality plays a role, as the data is coming from a myriad of
+sources, each with possible idiosyncratic features or missing values. We employ
+a few QA measures during the process. First, we try to pass each data item
+through only one processing pipeline (e.g. items matched by any identifier
+should not even be considered for fuzzy matching). If duplicate links appear in
+the final dataset nonetheless, we remove them, prefering exact over fuzzy matches.
+
+We employ a couple of data cleaning techniques, e.g. to find and verify
+identifiers like ISBN or to sanitize URLs found in the data. Many of these
+artifacts stem from the fact that large chunks of the raw data come from
+heuristic data extraction from PDF documents.
 
 
 \section{Discussion}