Merge pull request #171 from chaselgrove/style

More editing

content/about/collaborators.md

@@ -4,9 +4,9 @@ type: docs
 weight: 30
 ---
 
-Our efforts are substantially informed and enhanced through the breadth and depth of scientific expertise of our collaborators in both [Collaborating Projects](#collaborating-projects) and [Service Projects](#service-projects).
+Our efforts are substantially informed and enhanced through the breadth and depth of scientific expertise of our collaborators in both [Collaborative Projects](#collaborative-projects) and [Service Projects](#service-projects).
 
-[Contact us](mailto:[email protected]) if you are interested in becoming a ReproNim Collaborating or Service Project.
+[Contact us](mailto:[email protected]) if you are interested in becoming a ReproNim Collaborative or Service Project.
 
 <link rel="stylesheet" href="/css/logos.css">
 <div class="container logos">
@@ -40,11 +40,11 @@ Our efforts are substantially informed and enhanced through the breadth and dept
     </div>
 </div>
 
-## Collaborating Projects
+## Collaborative Projects
 
 We are collaborating with numerous groups around the country and abroad to synergistically develop ReproNim tools in concert with (and as informed by) rapidly advancing technologies in a variety of areas including image analysis, workflow processing, data sourcing and hosting, and associated API developments.
 
-The P41 Center Collaborative Projects (CPs) serve as technology drivers, users, and testbeds for the cutting-edge technology developed in P41 Technology, Research and Development projects.
+The P41 Center Collaborative Projects (CPs) serve as technology drivers, users, and testbeds for the cutting-edge technology developed in P41 Technology and Research Development projects.
 
 - CP1: [Segmenting Brain Structures for Neurological Disorders](https://reporter.nih.gov/search/kT7X-zyN302C6XNNo4g5xQ/project-details/10295766)
     - [Bruce Fischl](https://www.nmr.mgh.harvard.edu/user/5499) (PI)

content/about/in-practice.md

@@ -23,7 +23,7 @@ references to them (by NUMBER.LETTER) on other pages.
 <!-- 1: Study planning -->
 1. Study planning
     <!-- 1a: Implement good science -->
-    1. Implement good science basics (power analysis, statistical consults, etc).
+    1. Implement good science basics (power analysis, statistical consults, etc.).
     <!-- 1b: Use pre-existing data -->
     2. Use pre-existing data for planning and/or analysis.
     <!-- 1c: Create a DSMP -->

content/participate/_index.md

@@ -9,7 +9,7 @@ We actively seek and support community engagement and feedback in the technical
 - Read the [ReproNim blog](https://reprodev.wordpress.com/category/article/).
 - Sign up for our [mailing list](https://www.nitrc.org/mailman/listinfo/repronim-announcement).
 - Explore, use, and contribute to our [training resources](/resources/training/).
-- Become a [Collaborator or Service Project](/about/collaborators/).
+- Become a [Collaborative or Service Project](/about/collaborators/).
 - Become a [ReproNim/INCF Fellow](/fellowship/).
 - Follow our [webinar series](/about/webinars/).
 - Drop in on our virtual office hours on the first Thursday of each month.  Find details in our [news](/about/news/).

content/resources/_index.md

@@ -3,8 +3,8 @@ title: Resources
 type: docs
 ---
 
-This section is dedicated to **how** to make use of the ReproNim ecosystem, comprising tools, training materials and tutorials on how to use ReproNim resources to improve the reproducibility of your neuroimaging studies.  
+This section is dedicated to how to make use of the ReproNim ecosystem.  It includes tools, training materials, and tutorials on how to use ReproNim resources to improve the reproducibility of your neuroimaging studies.  
 
 If you are new to the concept of ReproNim's mission to increase reproducible practices in neuroimaging, we suggest you familiarize yourself with [why neuroimaging should be reproducible](/about/why/) and [ReproNim's Principles of Reproducible Neuroimaging](/about/in-practice/). 
 
-If you are unfamiliar with ReproNim and its approach, we suggest you visit [Getting started with ReproNim](/resources/getting-started/) for a general orientation to the website, along with a set of user stories that illustrate how ReproNim can address data and software management issues you may encounter in your current neuroimaging workflow.
+If you are unfamiliar with ReproNim and its approach, we suggest you visit [Getting started with ReproNim](/resources/getting-started/) for a general orientation to the website and a set of user stories that illustrate how ReproNim can address data and software management issues you may encounter in your current neuroimaging workflow.

content/resources/training/_index.md

@@ -4,56 +4,45 @@ type: docs
 weight: 5 
 ---
 
-We produce teaching materials and training programs in reproducible research, and aim to reach a broad audience.
-Our materials and programs address the overall issues that affect the reproducibility of neuroimaging research (modules, webinars) and consider their applications in a wide variety of experimental and environmental contexts.
+ReproNim produces teaching materials and training programs in reproducible research and aims to reach a broad audience.  Our materials and programs address the overall issues that affect the reproducibility of neuroimaging research and consider their applications in a wide variety of experimental and environmental contexts.
 
 ## What we offer
 
-A **modular online curriculum** that provides topical training in overarching issues that affect the reproducibility of neuroimaging research (data acquisition and characterization, experimental methods, analyses, record keeping and reporting, reusability, and sharing of data and methods).
+A modular online curriculum that provides topical training in overarching issues that affect the reproducibility of neuroimaging research (data acquisition and characterization, experimental methods, analyses, record keeping and reporting, reusability, and sharing of data and methods).
 
-The **ReproNim/INCF Train-the-Trainer Fellowship Program**, to empower researchers to teach reproducible methods to others.
-This program is intentionally customized to support  Fellows to a) identify particular needs and target audiences  (at any level) in their home institutions, and b) then create one or more training events (for example, an academic course, hackathon, or workshop).
+The ReproNim/INCF Fellowship Program empowers researchers to teach reproducible methods to others.
+This program is intentionally customized to support Fellows to identify particular needs and target audiences (at any level) in their home institutions and then create one or more training events (e.g. an academic course, hackathon, or workshop).
 
-We also **partner with groups** to create tailored training programs that address their specific research needs and expand our topical coverage.
-Our Associated training programs include [ReproRehab](https://www.reprorehab.usc.edu/), an NIH-funded training fellowship program (USC) designed to support reproducible research in the physical rehabilitation community, under the founding leadership of ReproNim/INCF Fellowship alumna, Sook-Lei Liew (2020-2021 class).
-We have also partnered with the Adolescent Brain Cognitive Development (ABCD) Study Research Consortium, in collaboration with Angela Laird (FIU), to create [ABCD-ReproNim](https://www.abcd-repronim.org/), a 12 week online course on reproducible data analyses with ABCD data (big data).
+We also partner with groups to create tailored training programs that addresses their specific research needs and expand our topical coverage.
+Our associated training programs include [ReproRehab](https://www.reprorehab.usc.edu/), an NIH-funded training fellowship program (USC) designed to support reproducible research in the physical rehabilitation community under the founding leadership of ReproNim/INCF Fellowship alumna Sook-Lei Liew (USC).
+We have also partnered with the Adolescent Brain Cognitive Development (ABCD) Study Research Consortium in collaboration with Angela Laird (FIU) to create [ABCD-ReproNim](https://www.abcd-repronim.org/), a 12-week online course on reproducible data analyses with ABCD data (big data).
 
-In addition, we and our Fellows have generated a great deal of training materials which are being cataloged in our **ReproInventory**.
+In addition, we and our Fellows have generated a great deal of training materials.  An effort is underway to catalog these in our [ReproInventory](https://github.com/repronim/reproinventory).
 
-Our **ReproNim ‘First Fridays’ monthly Webinar Series** features important efforts in reproducibility, from both ReproNim and others. See our [ReproNim channel](https://www.youtube.com/channel/UCGX2sXmEgDuUGWHDSiT1NdQ/videos) to view our entire collection of webinars to date.
+Our ReproNim "First Fridays" monthly webinar series features important efforts in reproducibility from both ReproNim and other groups. See our [ReproNim YouTube channel](https://www.youtube.com/channel/UCGX2sXmEgDuUGWHDSiT1NdQ/videos) to view our entire collection of webinars to date.
 
-Our **Tutorials** address practical challenges in the execution of reproducible neuroimaging across a number of use case scenarios.
+Our tutorials address practical challenges in the execution of reproducible neuroimaging across a number of use cases.
 
 ## Curriculum
 
-Our **Curriculum** focuses on developing material that address reproducibility in six modular areas.
+Our curriculum focuses on developing material that address reproducibility in five modular areas.
 
-### ReproNim Introduction
+### ReproNim introduction
 
-Why do we care about reproducibility? Can we do anything to improve the reproducibility of our neuroimaging work? Let's get motivated to change the world!
+Why do we care about reproducibility? Can we do anything to improve the reproducibility of our neuroimaging work? Let's get motivated to change the world!  [Go to the module](http://www.repronim.org/module-intro/).
 
-[Go to module](http://www.repronim.org/module-intro/)
+### Reproducibility basics
 
-### Reproducibility Basics
+Shells, version control, package managers, and other tools to embrace "reproducibility by design." [Go to the module](http://www.repronim.org/module-reproducible-basics/).
 
-Shells, version control, package managers, and other tools to embrace "Reproducibility By Design"!
+### FAIR data
 
-[Go to module](http://www.repronim.org/module-reproducible-basics/)
+FAIR is a collection of guiding principles to make data findable, accessible, interoperable, and reusable. We look at ways to ensure that a researcher's data is properly managed and published in support of reproducible research.  [Go to the module](http://www.repronim.org/module-FAIR-data/).
 
-### FAIR Data
+### Data processing
 
-FAIR is a collection of guiding principles to make data Findable, Accessible, Interoperable, and Reusable. We look at ways to ensure that a researcher’s data is properly managed and published in support of reproducible research.
-
-[Go to module](http://www.repronim.org/module-FAIR-data/)
-
-### Data Processing
-
-What do we need to know to conduct reproducible analysis? Learn to: Annotate, harmonize, clean, and version data; and create and maintain reproducible computational environments.
-
-[Go to module](http://www.repronim.org/module-dataprocessing/)
+What do we need to know to conduct reproducible analyses? Learn to annotate, harmonize, clean, and version data and to create and maintain reproducible computational environments.  [Go to the module](http://www.repronim.org/module-dataprocessing/).
 
 ### Statistics
 
-Here we describe some key statistical concepts, and how to use them to make your research more reproducible. Everything you ever wanted to know about power, effect size, P-values, sampling and everything else.
-
-[Go to module](http://www.repronim.org/module-stats/)
+Here we describe some key statistical concepts and how to use them to make your research more reproducible. Everything you ever wanted to know about power, effect size, P-values, sampling, and everything else.  [Go to the module](http://www.repronim.org/module-stats/).