Chapter 12 Computing resources
Because our work is quantitative, research computing skills are an important part of your toolset. Most of our team uses the open source software
R for a lot of their workflow, though you probably want to also learn an additional tool during your time in the lab (for many, the natural choice here is
ADMB, as these
C++ template languages are the basis for many statistical population dynamics models in fisheries stock assessment).
Fortunuately, there are heaps of resources (including your labmates!) to help you with your learning.
12.1 Overview of Computing at UMassD
[intro to CITS / how to update your computer, links to site license software]
12.2 SMAST computing facilities
[SMAST server/computing access forms]
12.3 Administrator Privileges
As your computer is your main piece of lab research equipment, it is important to be able to use it effectively. Please ensure you are familiar with procedures for and have the ability to make changes on your computer as an administrator.
12.4 Remote meetings via Zoom
UMassD uses Zoom as its conference call software solution. Everyone should activate their Zoom Pro account which is part of the university license.
[Links to university Zoom stuff]
12.5 Collaborative software
For writing, we collaborate using GoogleDocs. For code and analyses we encourage the use of version control (see Wilson et al. paper for what this could look like), stepping toward the use of git and github for sharing code and analyses. We believe there are many advantages of using these tools to help simplify workflows and shift cognitive load to the science being done rather than on organization and bookkeeping (which computers are good at). Recognizing that these tools represent a learning curve, we provide training in their use, and also encourage alternatives for sharing and documenting work. For example, code and analyses may also be shared among collaborators using a GoogleDrive folder.
12.6 Backups and set up to Lab storage server
The average life expectancy of a hard drive is less than the duration of most graduate programs. Thus it is critical to ensure your data and work are backed up regularly. You may have personal baackup solutions (e.g. through Dropbox, Google Drive, etc.) but the lab has dedicated storage space on a university server that is backed up in multiple locations. Your data should be backed up on here. Information for logging on and accessing this See information provided on a GitHub issue
12.7 Introductory R learning resources
R! There are so many learning resources out there it can feel a little overwhelming in terms of what to choose! Right now, we REALLY like this short intro course by
@allisonhorst. They teach a lot of the workflow and tools around using R right from the get go, which we think is more helpful than knowing how to do all the things. The (excellent) materials are thoughtfully put together, link to a ton of other great resources, and just like the online #rstats community in general, are super supportive of new learners.
If you want a book to work from/through, R for Data Science is highly recommended. (book is free online)
A plug for the online R community. Follow the hashtag #rstats, & also check out accounts
@R4dsCommunity. The weekly #TidyTuesday social coding project is also a great way to practice your growing R skills. Have fun!
12.8 TMB and ADMB