Claudio risolto errori

pipeline_template_example.tex

@@ -1,12 +1,12 @@
 \subsection{Example}\label{sec:example}
-\newcommand{\pone}{$\langle service,owner=dataset.owner\rangle$}
-\newcommand{\ptwo}{$\langle service,owner=partner(dataset.owner) \rangle$}
-\newcommand{\pthree}{$\langle service, owner \neq dataset.owner AND owner \neq partner(dataset.owner)$}
+\newcommand{\pone}{$\langle service\_owner=dataset\_owner\rangle$}
+\newcommand{\ptwo}{$\langle service\_owner=partner(dataset\_owner) \rangle$}
+\newcommand{\pthree}{$\langle service\_owner \neq dataset\_owner AND owner \neq partner(dataset\_owner)$}
 
 
 We present an example of pipeline template focusing on policy annotations. The pipeline template consists of five stages, and each stage is annotated with a policy presented in \cref{tab:anonymization}. \hl{Connecticut Prison (CTP) is the service user executing the pipeline. New York Prison and New Hampshire Prison are two partner DOC.}\hl{SPOSTARE NEL SYSTEM MODEL? SI, MA DATA OWNER DIPENDE DAL DATASET, HO MESSO SERVICE USER} We recall that \cref{tab:dataset} shows a sample of our reference dataset.
 
-In the following we will make reference to three different type of anonymization:\hl{E' GIUSTO USARE \tf{i}? SPOSTIAMO PRIMA?}
+In the following we will make reference to three different type of anonymization:\hl{E' GIUSTO USARE}\tf{i}\hl{? SPOSTIAMO PRIMA?}
 \begin{enumerate*}[label=\roman*)]
   \item \emph{level0} (\tf{0}): no anonymization is performed;
   \item \emph{level1} (\tf{1}): the data is partially anonymized, only the first name and last name are anonymized;
@@ -56,9 +56,8 @@ \subsection{Example}\label{sec:example}
 %In summary, this section has delineated a comprehensive pipeline template. This illustrative pipeline serves as a blueprint, highlighting the role of policy implementation in safeguarding data protection across diverse operational stages.
 \begin{table*}[ht!]
   \centering
-  \caption{Anonymization policies}
-  \label{tab:anonymization}
-  \bgroup
+  \caption{Anonymization policies}\label{tab:anonymization}
+%  \bgroup
   \def\arraystretch{1.5}
 
   \begin{tabular}[t]{c|c|l}

system_model.tex

@@ -46,12 +46,11 @@ \subsection{Service Pipeline and Reference Scenario}\label{sec:service_definitio
 The user's preferences align with a predefined pipeline template that orchestrates the following sequence of operations:
 \begin{enumerate*}[label=(\roman*)]
   \item \emph{Data fetching}, including the download of the dataset from other states;
-  \item \emph{Data preparation and protection}, including data merging, cleaning and anonymization;
+  \item \emph{Data preparation and protection}, including data merging, cleaning and anonymization;\hl{QUESTO E' MERGE (M). IO PENSAVO DIVENTASSE UN NODO $v_i$. NEL CASO CAMBIANDO LA DEFINIZIONE 3.1 DOVE NON ESISTONO PIU' I NODI MERGE E JOIN.}
   \item \emph{Data analysis}, including statistical measures like averages, medians, and clustering-based statistics;
   \item \emph{Machine learning task}, including training and inference;
-  \item \emph{Data storage}, including the storage of the results in the corresponding states. Specifically, one copy remains in Connecticut (where sensitive information in the source dataset is not protected),
-        while two additional copies are distributed to New York and New Hampshire (with sensitive information from the source dataset being safeguarded).
-  \item \emph{Data visualization}, including the visualization of the results.
+  \item \emph{Data storage}, including the storage of the results in the corresponding states. Specifically, one copy remains in Connecticut (where sensitive information in the source dataset is not protected), while two additional copies are distributed to New York and New Hampshire (with sensitive information from the source dataset being safeguarded).\hl{SPIEGHIAMO BENE LA PARENTESI}
+  \item \emph{Data visualization}, including the visualization of the results.\hl{STORAGE E VISUALIZATION NON LI FACEVAMO ALTERNATIVE CON UN NODO FINE?}
 \end{enumerate*}