Merge remote-tracking branch 'origin/gh-pages' into text-fix

* origin/gh-pages:
  Rename 00-Overiew.md to 00-overview for consistency and to simplify review of PR #31

Author: yarikoptic

_episodes/00-overview.md

@@ -7,8 +7,8 @@ questions:
 - "Who is this module for?"
 - "How should I study it?"
 objectives:
-- Think about reproducibility as an inherent part of research activities.
-- Apply lesson materials in your daily work as soon as possible.
+- To think about reproducibility as an inherent part of research activities
+- To use lesson materials as soon as possible
 keypoints:
 - "Efficient practices are the (more) reproducible ones"
 
@@ -18,50 +18,55 @@ keypoints:
 
 The term "reproducibility" conjures a mental image of dedicated systems
 conducting automated and repeatable computations.  However, **you** can
-embrace reproducibility in your day-to-day research activities.
-Neuroimaging is a heavily data- and software-driven field of science.
-As a result, by learning best practices for the tools you already use daily,
-you will discover ways to improve your efficiency and increase the
-reproducibility of your research.
+embrace reproducibility as a principle to apply to your day-to-day
+research activities.  Neuroimaging is a heavily data- and software- driven
+field of science.  As a result, by learning more tricks and techniques
+for the tools that you already use daily, you will discover ways to
+not only improve your efficiency but also to increase the reproducibility of
+your research.
 
-Reproducibility requires us to know the **what**, **when**, and **how**
-for any particular analysis we carry out. The lessons in this module will
-help us answer those questions. Before addressing these specific questions,
-consult the referenced external materials (tutorials, lessons, etc.) to get a
-more generic and thorough treatment of the topics.
+To some degree, reproducibility requires knowledge of **what**,
+**when**, and **how** any particular analysis was carried out.
+Therefore the lessons in this module will focus on helping
+answer those questions.  Before addressing these specific questions,
+referenced external materials (tutorials, lessons, etc) will provide a
+more generic and thorough presentation of the topics.
 
 
 ### Who is this module for?
 
-This module is for any scientist, researcher, or student who is using
-software for data analysis, writing custom code, or editing documents.
+The module is for any scientist, researcher, or a student who is using
+software for data analysis, writing custom code or editing documents.
 
 > ## Prerequisites
 >
 >
 > Depending on your level of competence in any particular topic, you
-> may benefit from the external materials that referenced in each
-> particular lesson.  Even if you feel that you're very proficient in all
-> of the topics, we hope you can still learn some new "tricks" or are
-> willing to recommend or contribute new materials to the lessons.
+> might like to go through additional materials that will be
+> referenced in each particular lesson.  Even if you feel that you are
+> very proficient in all of those topics, we hope that you can still
+> learn some new "tricks" or are willing to recommend or contribute new
+> materials to the lessons.
 {: .prereq}
 
 ### How much time should this take?
 
-This depends on your familiarity with the command line/shell, version
-control systems, managing software environments, etc. All of these
-topics may seem independent but are in fact very much related; it's likely
+That primarily depends on your familiarity and experience with working
+in command line/shell, using version control systems, managing
+software environments, having experience providing constructive
+feedback about defects you found in software you use, etc. All those
+topics seem independent but are also very much related, so it is likely
 that you might have some familiarity with all of them, or that you know
-just one of them well. If you have no experience with any topic,
-this may take you a long time: for instance, 5 to 7 full days. If you're
-already experienced, some of the information may be redundant and it may take
-you only a few hours to go through the material in detail. In each
+just one of them well.  If you have no experience with any topic,
+this may take you a long time: for instance, 5 to 7 full days. If you
+are experienced, some of the information may be redundant and it may take
+you only a few hours to go through this material in detail. In each
 lesson, we provide an estimate for the time it would take to learn
 the lesson, assuming you have a basic understanding of the topic.
 
 ### How should the acquired knowledge be used?
 
-The most important lesson is to **apply** the knowledge you gain to
+It is important to **apply** the knowledge gained from the lessons to
 your day-to-day activities as soon as possible! Start using shell
 and/or do it more efficiently by using shortcuts, scripting, making
 those scripts robust, etc. Use version control systems for anything
@@ -73,24 +78,26 @@ run into and don’t just leave them unresolved.
 
 An efficient approach to learning the materials is to first skim
 through all the materials, noting the key concepts and applying them
-right away. Then, after gaining experience and stumbling on some
-problems, review the relevant topic in greater detail.
+right away. Then, after gaining experience and stumbling upon some
+problems, it will be useful to review the relevant topic in greater
+detail while concentrating on the relevant aspects.
 
 **The least efficient approach would be to spend a week "learning
 it" only to forget all of it by not using any of the learned tools
 or recommended practices.**
 
 ### What are the lessons in this module?
 
-This module introduces three somewhat independent topics at the heart of
-efficient and reproducible scientific computing: command line/shell,
-version control systems (for code and data), distribution package managers,
-and a few additional aspects such as bug reporting and licensing. It's
-unlikely that you've managed to completely avoid those tools so far,
-but it's possible that you've under-utilized their capabilities.
+This module guides through three somewhat independent topics, which
+are at the heart of establishing and efficiently using common generic
+resources: command line shell, version control systems (for code and
+data), distribution package managers, and a few additional aspects such
+as bug reporting and licensing.  It is very unlikely that you have
+managed to completely avoid using those tools in past research activities,
+but it is possible that you have under-utilized their capabilities.
 Gaining additional skills in any of these topics can not only help
 your day-to-day research activities become more efficient, but
-also lay the groundwork for establishing habits that will make your work
-more reproducible. Moreover, these topics are the foundation of future
+also lay the foundation for establishing habits that will make your work
+more reproducible.  Moreover, these topics are the foundation of future
 modules in the ReproNim curriculum.