VizierDB/paper-HILDA-2016-Spreadsheets
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Boris Glavic 2016-04-24 19:26:14 -05:00
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4
sections/interface.tex
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@ -20,7 +20,7 @@ Our goal in the design of \langname is to define a form of relational algebra th
We will first sketch the language itself through several examples so that we can better introduce the front-end, before returning to define it more precisely in Section~\ref{sec:language}.
\begin{figure}
\begin{verbatim}
\begin{lstlisting}[morekeywords={LOAD,ROW}]
LOAD 'lineitem.csv'
ADD COLUMN total;
UPDATE total = price * (1 - discount)
@ -29,7 +29,7 @@ INSERT ROW (
name = 'table', price = 10, discount = 0.05,
total = price * (1-discount)
)
\end{verbatim}
\end{lstlisting}
\caption{An example \langname page script}
\label{fig:program}
\end{figure}

29
sections/introduction.tex
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@ -12,7 +12,7 @@ that combines the best of both worlds and augments it with new functionality suc
%
Spreadsheets are a ubiquitous data processing tool. Their simplicity, generality, and adaptability make them ideal for ``playing'' with data through predominantly visual programming metaphors.
%In particular, spreadsheets provide powerful, but entirely visual metaphors for programming both data transformations and visualizations.
Spreadsheets provide several important features that are useful during data curation.
Spreadsheets provide several important features that are useful during data curation:
\begin{itemize}
\item \textbf{Convenient modification of values and computations.} The user can update any cell's value or formula immediately from the user interface. This enables flexile manual curation operations, e.g., to resolve missing value and to easily modify or overwrite any past choices.
@ -49,26 +49,37 @@ While the spreadsheet UI has many advantages, it also has several drawbacks.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\tinysection{Notebook-style UIs}
Systems like iPython expose an interactive, interpreted programming environment through a notebook like interface where the user can mix documentation (text) with code. The output for code blocks is shown directly in the notebook - a feature that is widely used to produce data visualizations.
A notebook UI such as in Jupyther and the visualization provided by workflow systems are much better suited in this regard. However, their disadvantage is that they are not suited well for small modifications to data, exploratory changes, and generalization of operations.
\begin{itemize}
\item
\end{itemize}
\begin{itemize}
\item \textbf{Small modification to data are cumbersome.} Compared to spreadsheets, modifying a few data values of a table requires the user to write code.
\item \textbf{Not }
\end{itemize}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\tinysection{Visualizations}
Both spreadsheets and notebook UIs make it very easy for users to create visualizations from data on the fly and show these visualization inline with the data. Also both paradigms allow these visualization to be tweaked and to be refreshed based on change to their inputs. Spreadsheets in particular make
Both spreadsheets and notebook UIs make it very easy for users to create visualizations from data on the fly and show these visualization inline with the data. Also both paradigms allow these visualization to be tweaked and to be refreshed based on change to their inputs. Spreadsheets in particular provide a very easy to use interface for selecting what data should be visualized.
\begin{itemize}
\item
\end{itemize}
% \begin{itemize}
% \item
% \end{itemize}
\begin{itemize}
\item
\end{itemize}
% \begin{itemize}
% \item
% \end{itemize}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\tinysection{Combining Spreadsheets and Notebooks}
%
Based on these observations we propose a hybrid notebook and spreadsheet interface that combines the best of both worlds. In this paper, we discuss how such an interface facilitates data curation and exploration.
%