Erik Tollerud update with completed intro  about 9 years ago

Commit id: 19e77247f8025fdff116a283979c5218edbc7bef

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\section{Comments}  \label{sec:comments}  We allowed participants to leave comments at the end of the survey to further get a sense of the attitude to this topics. We thank so many of the participants for leaving thoughtful comments. We find that there are three recurring topics in the comments. The first such topic is the switch from IDL to Python.          

\section{Conclusions}  \label{sec:conc}  %http://arxiv.org/abs/1212.1915  %Further, as we push for more researchers to publish their software in order to make research more reproducible and reuse more software, we need realize that one of the most common reasons for not sharing software is shame. Before we force researchers to make code public, we need to provide them with resources to learn how to write good code.          

\section{Data and Methods}  \label{sec:datamethods}  The survey was constructed as a Google questionnaire with seven questions and one comment box. Four of the questions were about software use and most were inspired by the UK survey:  \begin{enumerate}         

\begin{quote}  Software that is used to generate, process or analyze results that you intend to appear in a publication (either in a journal, conference paper, monograph, book or thesis). Research software can be anything from a few lines of code written by yourself, to a professionally developed software package. Software that does not generate, process or analyze results - such as word processing software, or the use of a web search - does not count as ‘research software’ for the purposes of this survey.  \end{quote}  However, this survey was limited to researchers at UK institutions, and more institutions. More  importantly, was not limited to astronomers. Hence, it inspired an effort focused on astronomers, who we suspect  to create a similar data set appropriate for the specific case of astronomy and related have quite different software habits than scientists in other  fields. Motivated by these issues and related discussions during the .Astronomy 6 conference, we created a survey to explore the software habits of astronomers. In this paper we discuss the methodology of the survey in \S \ref{sec:datamethods}, the results from the multiple-choice sections in \S \ref{sec:res}, a discussion of the free-form comments in \S \ref{sec:comments}, in \S \ref{sec:ssicompare} we compare our results to the aforementioned SSI survery, and in \S \ref{sec:conc} we conclude.  Motivated by these issues Additionally, we have made the (anonymized) results as of the time of this writing  andrelated discussions during  the .Astronomy 6 conference, we created a survey code  to explore generate the summary figures available at \url{https://github.com/eteq/software_survey_analysis}. This repository may be updated in  the software habits future if a significant number  of astronomers.   Before moving on to discussing new respondents fill out  the \url{https://github.com/eteq/software_survey_analysis} survey.         

\section{Results}  \label{sec:res}  In this section we analyze the results from the survey and discuss interesting findings and implications.         

\section{Comparison to SSI Survey}  \label{sec:ssicompare}  90\% of astronomers write some of software (93\% of UK astronomers). This is much larger than the SSI survey which finds that 56\% of researchers write some of their software, i.e., astronomy depends much more on software than other sciences.         

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