Open ExperimentsInHonesty opened 1 year ago
My understanding related to BOP project specific details:
My understanding related to knowledgebase project from technical perspective:
this gets added equal to gdocs
Image from Knowledgebase
28th Oct 23
In regards to Summary of Oct 27 Meeting on Knowledgebase and BoP
Since we will store metadata about content, could we use NoSQL for instance, MongoDB? We chose relational databases because the BOP will be synchronized with the Knowledge and PeopleDepot?
For the APIs, we just need to set up create and retrieve (to summarize the asset data) endpoints and do the deletions and updates from the Django admin portal tentatively speaking?
We will be using Postgres hosted on AWS.
@ethan asked
In regards to Summary of Oct 27 Meeting on Knowledgebase and BoP
Toe for Ethan: Since we will store metadata about content, could we use NoSQL for instance, MongoDB? We chose relational databases because the BOP will be synchronized with the Knowledge and PeopleDepot? Ethan: If attributes of metadata are known I read an article that convinced me relation is better. I will try to dig up the article. PostGres also lets you have JSON fields and you can refer to the JSON attributes.
Toe for Ethan: For the APIs, we just need to set up create and retrieve (to summarize the asset data) endpoints and do the deletions and updates from the Django admin portal tentatively speaking? Ethan: Creation, deletions and updates can be done from Django admin with no API. An API will be needed to retrieve all information about an asset so other applications can use it. Depending on the UI and functional requirements, Django admin may also be able to provide the screen for viewing the summary data - probably not long term, maybe for MVP.
I have questions regarding the survey data and how it was collected. Who is the best person to connect with on this topic please?
My questions are related to understanding whether the survey data is representative of all US brigades, and also the base used for % calculations in cols K, M, Q, S:
Find the report by Jon K for quant
@bonniewolfe @ag2463 shared the Jon K quant report with me. The link is here: (https://rpubs.com/jkropko/775977)
Descriptions for:
Move up the development of the entity table people need to be able to have multiple entities if they are a member of another brigade, they will be prompted to add hack for la if they are also a member there.
These are the fields we anticipate for the kb Refined Requirements: Google ID - Internal Title - Display Description - Display Slug - Internal Active (T/F) - Internal Practice Area - Display Status - Display Published (T/F) - Internal Contributor(s) - Display Tool - Display Internal Source - Display if value provided External Source - Display if value provided Topic Area - Display Usability Rating - Display Review - Display
The following terms will be replaced with source-external and source-internal in the database, but will display as source on webpages. The source-internal will come from the orgs in People Depot.
I have questions regarding the survey data and how it was collected. Who is the best person to connect with on this topic please?
My questions are related to understanding whether the survey data is representative of all US brigades, and also the base used for % calculations in cols K, M, Q, S:
- What is the total number of brigades in the USA?
- How does this number break down across large and small MSAs?
- How are large and small MSAs defined?
- In the GSheet "BOP: Overview of topic areas" on the "Tallies" tab, I see in cells A1:2 that there was an adjusted total # of brigades surved of 84 (28 large MSA + 56 small MSA) but then column B shows only 72 responses. What is the reason for this difference between 84 and 72?
- What was the breakdown of the 72 responses across large and small MSAs?
- If brigades surveyed were a sample of the total, how were survey participants selected?
- Did some brigades contribute multiple responses or was only one response allowed per brigade?, i.e., are the 72 responses coming from 72 different brigades or from fewer than 72 brigades
@ejennywhiley123 In the Quantitative report we did not collect information regarding Active members and that would have enabled us to see if a Brigade was really a Large or Small Brigade. Jon collected meetup numbers and used that to determine Small or Large, and we believe those numbers to be misleading, which he alludes to in his report. After this report was delivered it was determined that we would used Metropolitan Statistical Area (MSA) size as the metric to determine Large and Small Brigades.
@ejennywhiley123 @kit-katrina20 Sorry for the delay, here are proper numbers. Sourced from the origin spreadsheet: BOP Interview Responses and Tracking
It looks like there is other relevant data in that spreadsheet, but it has some serious problems with it. We will contact the original developer of it, and get back to you, hopefully, with the actual number of large MSA and small MSA brigades surveyed and some other data about length of leadership and other numbers.
Brigades and Interview number | Number | Notes |
---|---|---|
Interviews Completed: | 72 | Some interviews, were conducted where two people from the same brigade has seperate interviews |
People interviewed: | 78 | This is number of interviews completed (72) where in some interviews, multiple people from the same brigade attended |
Participating Brigades: | 65 | This is number of interviews completed (78) with the only the first representative from that Brigades interview being counted |
Overview
We need to track the questions that developers ask in the beginning of their tenure, so that we can create a faq in the wiki
Action Items
Resources/Instructions