Closed snooravi closed 2 years ago
@MalakH21 's ideas
Service request data from MyLA311 for 2015 - 2021 data source: LA open data
explore the data patterns and trends in:
with respect to request # per person/NC
so that we could see if there is anything interesting to make suggestions on e.g a specific request overwhelms in several NC's
(simple ML prediction?)
Background A bit of background/moodling to start:
I'm thinking of scoping base on different "user" types:
I'm thinking about this from the data not the existing web app. I'm starting to look at viability of these ideas in the app.
Use Cases/Storylines
These are some basic ideas. I will look at the reference doc on 311 users from last night to see specifics of alignment. I will put together more details for next monday. Don't want to spend a lot of time if this is too far afield.
Next steps: Chose your favorite topic and explore the datasets within or that would support to review on Wednesday with the team.
@MalakH21 's ideas
- Not sure if graffiti harbors some of the same sentiment as homeless encampments - but it seems like a good storyline to consider since the reporters here cited the usage of 311. Although you can only use the Alpha tool to go back as far in time as cited in the article, the map and data visualization tools lend themselves very well to understanding volume change. There could also be a local understanding of where a mural exists or street art and that could be used in conjunction with the tool to see how requests in that specific spot have changed over time vs. more "non-artistic" graffiti.
- Explore the interactions between [SSL] Single Streetlight and [MSL] Multiple Streetlight requests and particular intersects and traffic collision data and here to see if there is any correlation - it might be difficult to pinpoint because it would involve digging into the why of the accident, which may not be worth doing
relevant to #1 & #2 service request data - https://data.lacity.org/City-Infrastructure-Service-Requests/MyLA311-Service-Request-Data-2020/rq3b-xjk8
data source for #2 https://data.lacity.org/Public-Safety/Traffic-Collision-Data-from-2010-to-Present/d5tf-ez2w has codes for which types of collisions were caused by stop signs/street lights
data sources for #1 more context on grafitti cleaning in LA http://laocb.org/programs/graffiti-abatement/
Notes:
Identify neighborhood council (and neighboring councils)
Final:
Re this post https://github.com/hackforla/access-the-data/issues/89#issuecomment-960305167
The definition of graffiti is unsanctioned painting on a surface
If you paint on a wall with the owner's permission is art if you paint on the wall without the owner's permission, it's graffiti
Not sure if graffiti harbors some of the same sentiment as homeless encampments - but it seems like a good storyline to consider since the reporters here cited the usage of 311. Although you can only use the Alpha tool to go back as far in time as cited in the article, the map and data visualization tools lend themselves very well to understanding volume change. There could also be a local understanding of where a mural exists or street art and that could be used in conjunction with the tool to see how requests in that specific spot have changed over time vs. more "non-artistic" graffiti.
Have you tried the Hack for LA 311 tool https://311-data.org?
Explore the interactions between [SSL] Single Streetlight and [MSL] Multiple Streetlight requests and particular intersects and traffic collision data and here to see if there is any correlation - it might be difficult to pinpoint because it would involve digging into the why of the accident, which may not be worth doing
Have you reviewed the work Henry Kaplan did for Greater Wilshire NC
@snooravi @mcmorgan27 @MalakH21 @ShikaZzz I think Sarah is indicting what I am about explicitly spell out, but I do want to leave the note on this issue for future team members.
After having read all the brainstorming here, I am appreciative of all the talent on this team.
I think this is a great starting point
@mcmorgan27 I'm thinking of scoping base on different "user" types:
- Joe Citizen - local resident
- Suzy Small Biz owner - brings a commercial perspective to the problem/questions
- NC board member/citizen volunteer
- City level "planner" and "service agencies"
I'm thinking about this from the data not the existing web app. I'm starting to look at viability of these ideas in the app.
Data Analysis using the raw data from the portal is too high a level for the initial workshop. Our team will focus on building our workshop, which is how to use the 311-data.org tools and the Alpha Report Tool https://hackforla.github.io/311-report/
Final outcome:
We will focus on grafitti volume in LA over time in various neighborhoods.
Overview
We are looking to anchor on a story that will be interesting to LA citizens leveraging available 311 data. Example storylines we have considered:
Action Items
Each member of the Access the Data Workshop will provide 1-3 different ideas for us to consider in Wednesday's team meeting.
Resources/Instructions
311data.org