\section{Goal \& Research question}
Maintaining the automated crawlers and the infrastructure that provides the
-\textit{Temporum} and its matching aid automization are the parts within the
-dataflow that require the most amount of resources. Both of these parts require
+\textit{Temporum} and its matching aid automation are the parts within the
+data flow that require the most amount of resources. Both of these parts require
a programmer to execute and therefore are costly. In the case of the automated
crawlers it requires a programmer because the crawlers are scripts or programs
created are website-specific. Changing such a script or program requires
adapted to the new structure and will produce good data again. This feedback
loop, shown in Figure~\ref{feedbackloop}, can take days and can be the reason
for gaps and faulty information in the database. The figure shows information
-flow with arrows. The solid and dotted lines form the current feedbackloop.
+flow with arrows. The solid and dotted lines form the current feedback loop.
\begin{figure}[H]
\label{feedbackloop}
\centering
lot of time repairing
crawlers and make the task of adapting, editing and removing
crawlers feasible for someone without programming experience. In practice this
-means shortening the feedbackloop. The shorter feedback loop is also shown in
-Figure~\ref{feedbackloop}. The dashed line shows the shorter feedbackloop that
+means shortening the feedback loop. The shorter feedback loop is also shown in
+Figure~\ref{feedbackloop}. The dashed line shows the shorter feedback loop that
relieves the programmer.
For this project a system has been developed that provides an
node $n2$ and $n3$ are final. Finally $v_0$ describes the initial node, this is
visualized in figures as an incoming arrow. Because of the property of labeled
edges, data can be stored in a DAWG. When traversing a DAWG and saving all the
-edgelabels one can construct words. Using graph minimalization big sets of
-words can be stored using a small amouth of storage because edges can be
+edge labels one can construct words. Using graph minimisation big sets of
+words can be stored using a small amount of storage because edges can be
re-used to specify transitions. For example the graph in
Figure~\ref{exampledawg} can describe the language $L$ where all words $w$ that
are accepted $w\in\{abd, bad, bae\}$. Testing if a word is present in the DAWG