Merge pull request #24 from ReproNim/add-maryann-getting-started

Add maryann getting started

content/resources/getting-started/_index.md

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-## Introduction
+**The ReproNIM philosophy**:  Incorporate reproducible practices into the typical neuroimaging workflow.  These practices ensure more robust, well documented studies at the end for you, your colleagues and your peers.
 
-### The ReproNim philosophy
+ReproNIM offers best practices, tools and training to implement reproducible neuroimaging in your lab.  Here is a brief overview of our website:
 
-Incorporate reproducible practices into the typical neuroimaging workflow.  These practices ensure more robust, well documented studies at the end for you, your colleagues and your peers.
+* **New to reproducible neuroimaging?**
+  * Why reproducible neuroimaging
+    * What is reproducible neuroimaging?
+  * **Wondering what ReproNIM can do for you?**
+    * Meet our exemplary user personas and the issues they face in running neuroimaging studies
+    * View our introduction to the ReproNIM way, step-by-step guides on some steps you can take using ReproNIM tools to improve your ability to perform robust and shareable neuroimaging studies
+  * **Tools and how-to guide:**
+    * Our ReproGuide provides descriptions of our tools and how to use them
+  * **Training:**
+    * [On-line training course](https://www.repronim.org/teach.html) on a range of basic and more advanced topics related to reproducible neuroimaging
+    * ReproNIM Fellows Program:  Become a ReproNIM fellow through our train the trainer program
 
-### Personas
-![](/images/user1.jpg)
-![](/images/user2.jpg)
-![](/images/user3.jpg)
-![](/images/user4.jpg)
+## Meet our users personas
+
+To introduce you to ReproNIM, we have created a set of exemplary user personas that represent some typical users and given them a face (through the magic of AI), a set of skills and interests. We then produced a set of basic use cases that showcased how adopting the principles of neuroimaging and ReproNIM tools can help them in their goals.
+
+Who would you like to hear from?
+
+<div style="display: flex; align-items: flex-start; margin-bottom: 20px; gap: 10px;">
+    <a href="#sarah-the-early-to-mid-career-researcher">
+        <img src="/images/sarah.jpg" alt="Sarah" style="width: 150px; height: auto; object-fit: cover;">
+    </a>
+    <p>
+        Hi, I’m Sarah.  I’m an early to mid-career researcher.  I’m  interested in applying best practices to my day-to-day research workflow.
+    </p>
+</div>
+
+<div style="display: flex; align-items: flex-start; margin-bottom: 20px; gap: 10px;">
+    <a href="#richard-the-software-engineer">
+        <img src="/images/richard.jpg" alt="Richard" style="width: 150px; height: auto; object-fit: cover;">
+    </a>
+    <p>
+        Hi, I’m Richard.  I’m a research software engineer.  I want to incorporate more standards into the technical operations of my lab and also learn more about how to effectively share workflows with his clients.
+    </p>
+</div>
+
+<div style="display: flex; align-items: flex-start; margin-bottom: 20px; gap: 10px;">
+    <a href="#john-the-computational-neuroscientist-and-teacher">
+        <img src="/images/john.jpg" alt="John" style="width: 150px; height: auto; object-fit: cover;">
+    </a>
+    <p>
+        Hi, I’m John.  I am a university-based computational neuroscientist and teacher.  I would like to see what resources ReproNim can offer for my teaching about rigor and reproducibility.
+    </p>
+</div>
+
+<div style="display: flex; align-items: flex-start; margin-bottom: 20px; gap: 10px;">
+    <a href="#evelyn-the-director-of-a-multi-center-project">
+        <img src="/images/evelyn.jpg" alt="Evelyn" style="width: 150px; height: auto; object-fit: cover;">
+    </a>
+    <p>
+      Hi, I’m Evelyn.  I am the director of a multi-center distributed project.  My interest is in harmonizing the research being performed at several sites.
+    </p>
+</div>
+
+## Sarah the early-to-mid career researcher
+
+<img src="/images/sarah.jpg" alt="Sarah" style="width: 250px; height: auto;">
+
+Sarah is fluent in modern technologies and comfortable both at the bench and behind a computer. She spends her days engaged in the hands-on aspects of studies. As she builds her career, she is concerned with keeping up-to-date with the latest trends and tools, but she doesn't dwell on technology for its own sake. Efficiency is important to her, but not if it sacrifices rigor.
+
+**Sarah’s interests**: I would like support for making my workflow development more efficient: How do I go from my 'garden path' trial workflow development, lock into a 'final' workflow, and then efficiently apply this workflow to my complete dataset. My workflow might change, so I'd like to efficiently update and re-apply the new workflow. I've heard 'versioning' will be important for this, but I'm not handy with these technologies.vPublishing my data would be nice, for some additional impact and complying with the NIH data sharing mandate support.
+
+**How can ReproNIM help?**
+
+ReproNIM can help Sarah learn more about data and software management and other best practices for reproducible neuroimaging,  and introduce her to tools and practices for versioning workflows. When data and software are managed throughout the neuroimaging workflow, publishing data, and the pipelines that produced it,  effectively and efficiently is much easier to do.
+
+**Tutorials that might be interesting to Sarah**:
+
+* Creating a neuroimaging data management and sharing plan
+  * Principle \= planning
+* Implementing data management basics:  Using ReproNIM tools to convert data to the BIDS standard and create a data dictionary
+  * Principle:  Data and metadata management
+  * Foundations:  Standards, Annotation
+* Implementing software management basics:  Using Git to manage workflow/pipeline versions
+  * Principle:  Software management
+  * Foundations:  Versioning
+* Publishing your work as a “Re-executable paper”( \= text, data, code):  Standards-based data sharing through Open Neuro
+  * Principle:  Publishing re-executable paper
+  * Foundations: Standards, Annotation
+
+## Richard the software engineer
+
+<img src="/images/richard.jpg" alt="Richard" style="width: 250px; height: auto;">
+
+Richard is responsible for developing the software in support of his lab’s research. High-level requirements are given to him, but he then has freedom in deciding how to implement solutions. He does not code exclusively but researches and plans his work: he must determine how to balance software engineering best practices with the limited resources available for research software engineering.
+
+**Richard’s interests**: Richard would like to generate software products that participate in community standards for data ingestion and export. He is aware of BIDS for standard input data representation, he needs to learn about 'output standards' such as BIDS derivatives and standardized output description (e.g. NIDM). He can be convinced that containerizing his software products can make them easier to deliver to his local clients (and for them to share with others who want to reproduce their work) and easier to support, compared to a bare metal software solution.
+
+**How can ReproNIM Help?**
+
+ReproNIM can help Richard learn how standards such as BIDs and NIDM can help with better data management.  ReproNIM can provide Richard with demos and use cases to show why containerization is worth the effort.
+
+**Tutorials that might be interesting to Richard**:
+
+* Advanced data management: Putting your derived data into BIDS derivatives and creating a semantically-enriched  data dictionary using NIDM, a standard for annotating neuroimaging data
+  * Principles:  Data management
+  * Foundations:  Standards, annotation
+* Working with containers:  Using NeuroDocker to containerize computational
+  * Principles:  Re-executability
+* Advanced data and software management: Datalad containers/run \+, YODA principles
+* More use cases are available through our ReproGuide
+
+## John the computational neuroscientist and teacher
+
+<img src="/images/john.jpg" alt="John" style="width: 250px; height: auto;">
+
+John is a university-based computational neuroscientist and teacher both a research lab and teaching responsibilities. He would like his lab members to understand and utilize principles of re-executable annotated workflows, and is wondering whether whether the Fellowship program might be appropriate for someone in his lab (perhaps a way to train others in the lab thereafter). As a teacher, he is interested in broadly educating his students on reproducibility, including exposure to key concepts, tools and educational materials.
+
+**John** is interested in whether ReproNim provides up to date teaching materials that he might use in his own teaching, and also interested in resources that might help his students and/or lab.
+
+**How can ReproNim Help?**
+
+**Educational resources that might be interesting to John and his students**:
+
+* John should point his students to Why Reproducible Neuroimaging and What is Reproducible Neuroimaging sections of our website for a high level overview of these topics.
+* For more in-depth training, ReproNim has created a modular on-line course that covers basic and advanced topics in reproducible neuroimaging.  Each module contains tutorials and hands on exercises.
+* ReproNIM also offers a Fellows Program, a one year train-the-trainer program in reproducible neuroimaging
+
+ReproNIM has also organized our tools and a set of step-by-step use cases in our ReproGuide.
+
+→ For hands on experience, his students can follow tutorials recommended for Sarah, Richard and Evelyn
+
+## Evelyn the director of a multi-center project
+
+<img src="/images/evelyn.jpg" alt="Evelyn" style="width: 250px; height: auto;">
+
+Evelyn is a researcher, and directs a multi-center distributed project. Her responsibilities include oversight for integrated data sharing and cross-site analyses within the project, as well as making all data ultimately publicly accessible and reusable. She is interested in options for facilitating and streamlining data acquisition, use and reuse for varied purposes, both within and beyond the bounds of the project itself. She has the authority and responsibility to make recommendations for infrastructure that would serve a multidisciplinary multi-site project well.
+
+**Evelyn** thinks ReproNIM might address many of her priorities, but she would really like an end-to-end platform for data acquisition, data management and dissemination. She needs to distribute common analyses to her sites. She’d like it to be easy for the sites to give her results from this analysis that are easy to aggregate and harmonize. As her sites are also collecting their own subjects, she needs common demographic, clinical and behavioral data to be collected/shared in a way that is also easy to aggregate/harmonize.
+
+**How can ReproNIM help?**
+
+ReproNIM is not an end to end platform, but has several tools that can take her current data workflow and make it easy to share FAIR data and analyses across multiple sites.
+
+**Use cases that might be of interest to Evelyn:**
+
+* Planning and data management:  Learn how a data collection and annotation framework for behavioral data to be collected can be set up using ReproSchema and shared across multiple sites.
+  * Principles:  planning, data management
+  * Foundations:  standards, annotations
+* Basic software management for distributed data: Curating and processing a single study to generate standardized, analysis-ready data to participate in distributed projects using Nipoppy
+  * Principles:  Software management
+  * Standards:  Standards, annotation
+* Advanced data management:  Adding standards and semantics to data dictionaries to promote data harmonization and findability using Neurobagel
+  * Principles:  data management, FAIR
+  * Foundations:  Standards, Annotation
+* Advanced metadata management: Searching and sharing metadata through ReproPond and ReproLake
+  * Principles:  Metadata management
+  * Foundations:  Standards, Annotation