Package goals for (the rest of) 2023

[emilliman5]

Here are my thoughts on totential goals/strategy for 2023 (or next 1 year). Any and all input is welcome. This initial list is meant to start the discussion.

1. Consistency and completeness: implement assessment/metrics for as many ref_source types as possible
2. Implementation paradigm for 3rd party packages: see Add security assessment via {oysteR} #272
3. Cohort metrics implementation and rollout, scoring a set of packages in its totality: Dev/cohort assess #248, Define methods for cohort metric class #199 Define a class for a cohort of R packages and its metrics  #198 Strategy for cohort metrics  #174 Package assessment challenge example: labeling -> ggplot2 #160
4. Enable ease of use: wrapper function Consider adding a wrapper function #276 , expand ref_source types (e.g. PositPM, pharmaVerse), reporting/output functionality

Please feel free, to add any priorities you think should be considered, or comment on the ones suggested here.

[AARON-CLARK]

Agree! It's a good list.

1. Consistency and completeness: implement assessment/metrics for as many ref_source types as possible

Created a few issues we discussed that are associated with # 1. Specifically, #300, #299, and #294. #296 is sort of related... it's within the same family.

[AARON-CLARK]

I also love # 4 proposed by @parmsam-pfizer: helping users (especially newbies) get to the risk score faster with a wrapper function. I think implementing #299 will help take away some of the pain points / reservations associated with with a wrapper function since the pkg_ref cache would be populated with the maximum assessment info, presenting a risk score not burdened with the drawbacks of any one pkg_ref source type.