[TRU Research] Web App Data Schema
Jim Walseth
jim.walseth at gmail.com
Tue Aug 27 12:18:32 PDT 2019
I should be able to attend as well. Cheers, -Jim
On Mon, Aug 26, 2019 at 3:32 PM Stephen DeSanto <rachidian at gmail.com> wrote:
> Victrola is fine! 5:30 works for me. Gives me time to get there after work.
>
> On Mon, Aug 26, 2019 at 3:09 PM Katie Wilson <katie at transitriders.org>
> wrote:
>
>> Cool, does Victrola on 15th work again, or is somewhere else better?
>> Having an actual meeting, even if a small one, will help me to sit down and
>> focus on this instead of getting distracted by other things. 5pm good, or
>> 5:30 or 6?
>>
>> On Aug 26, 2019, at 9:38 AM, Stephen DeSanto <rachidian at gmail.com> wrote:
>>
>> I'm also available Tues evening. Otherwise I'll keep making updates from
>> home. :)
>>
>> On Sun, Aug 25, 2019 at 4:43 PM Katie Wilson <katie at transitriders.org>
>> wrote:
>>
>>> This is awesome, thank you Stephen. I put some thoughts in-line in red below,
>>> and attached a hard-to-interpret spreadsheet with info about Business
>>> Choice participants.
>>>
>>> I will try to schedule some time this week to start completing rows for
>>> the businesses I’m sure about based on the info we have. If anyone wants to
>>> get together for a spreadsheet workparty this week let me know, I have time
>>> Tuesday and Friday evenings.
>>>
>>> Katie
>>>
>>> On Aug 25, 2019, at 3:37 PM, Stephen DeSanto <rachidian at gmail.com>
>>> wrote:
>>>
>>> Hi everyone. Made a few updates to the master list of employers
>>> <https://docs.google.com/spreadsheets/d/1HmOcG7hJLD1G0unCMPcsDnXr4RIA_PMKEE5ne-hhQR8/edit?usp=sharing>
>>> for the upcoming website:
>>>
>>> - Added companies and transit benefits raw descriptions from TRU
>>> survey data
>>> - Added "Likely CTR Targets":
>>> https://seattletransitpasses-research.pbworks.com/w/page/133438365/Likely%20Target%20Assessment
>>> - Added "Potential CTR Targets":
>>> https://seattletransitpasses-research.pbworks.com/w/page/133437828/Potential%20CTR%20Targets
>>> - "Likely" / high-profile targets (hotels, banks) are highlighted in
>>> ORANGE
>>> - Added "Potential Poster Children":
>>> https://seattletransitpasses-research.pbworks.com/w/page/133439169/Potential%20Poster%20Children
>>> - Poster children are highlighted in GREEN
>>>
>>> Highlight colors are just to make it easier to find rows that a) someone
>>> said should be included in the list, and b) probably needs benefits data
>>> incorporated
>>>
>>> Things to be done:
>>>
>>> - Normalize locations data For this and the “leaf scores” and the
>>> “polluter” columns, I’d be inclined to do this after we’ve got
>>> enough info to check the “publish” box. I could be wrong, but I feel like
>>> it will be less work that way.
>>> - Assign "leaf scores" to all companies that don't have one
>>> - Assign "polluter" etc badges to companies we want to name&shame
>>> - Add all of the hotels?
>>> https://seattletransitpasses-research.pbworks.com/w/page/133666440/Hotels
>>> Yeah let’s go ahead and add them...
>>> - Add Choice participants? Good question. I did get info back from
>>> Metro on what products the choice participants are buying, I can’t remember
>>> whether I shared that with you all. Anyway, it’s attached. It’s actually a
>>> little hard to interpret (I got a tutorial from a Metro staffer) so I can
>>> try to explain by phone or in person if someone wants to dig throughthat.
>>> Maybe it makes sense to look through that info and add businesses
>>> selectively as we feel like we have a grasp on their programs.
>>> - Add column for Commute Seattle participants?
>>> https://seattletransitpasses-research.pbworks.com/w/page/133438167/Commute%20Seattle%20List%20of%20Passport%20Participants I
>>> don’t think we need to do this, because this info is most likely
>>> duplicative with what we learned from Metro about passport participants.
>>> The Commute Seattle list doesn’t tell us how much of a subsidy they
>>> provide, so it’s not going to add much.
>>>
>>>
>>> - Citations, descriptions of benefits, etc. for companies that need
>>> it
>>>
>>> There's still a lot we're not 100% sure about for employer benefits, but
>>> we can do the best we have with what we've got, and make changes as we get
>>> new information.
>>>
>>> My thinking was, we can use the "master employer list" to get as much
>>> information about the companies we're interested in. When we're satisfied
>>> that a row is finished and ready for publication, check the checkbox in the
>>> "__publish" column. Then, when we export this data to the website, we can
>>> only get the rows where "__publish" is checked. This hopefully will ensure
>>> that someone manually reviewed and verified all the data for an employer
>>> before it gets published, and that unfinished rows won't be accidentally
>>> exported.
>>>
>>> Is this helpful? Am I just spinning my wheels in the mud?
>>>
>>>
>>>
>>> On Thu, Aug 22, 2019 at 7:06 PM Stephen DeSanto <rachidian at gmail.com>
>>> wrote:
>>>
>>>> FYI, added most of you as editors on the spreadsheet I'm working on, in
>>>> case anyone has time for tedious data tasks (or a quick way to do tedious
>>>> data tasks). I'm currently adding in data from the TRU survey, from
>>>> respondents whose employers offer transit benefits. Eventually, we'll need
>>>> these tagged with industry and fix the neighborhoods data? And add in any
>>>> other company data we have from the other research spreadsheets on the
>>>> wiki? And eventually some subset of this data ends up on the website?
>>>>
>>>> On Tue, Aug 20, 2019 at 3:03 PM Tom Chartrand <tmchartrand at gmail.com>
>>>> wrote:
>>>>
>>>>> Oh you're right, sorry for the confusion everyone! was just fairly
>>>>> hidden in the view i looked at. Column S!
>>>>>
>>>>> On Tue, Aug 20, 2019 at 3:00 PM Katie Wilson <katie at transitriders.org>
>>>>> wrote:
>>>>>
>>>>>> I think the spreadsheet with PII removed still does include the
>>>>>> Employer column, no?
>>>>>>
>>>>>> Sorry I’m being slow to respond to all this good stuff, I am still
>>>>>> digging myself out from being away last week and I’m at an all-day thing
>>>>>> today… but I should have time to pay more attention before the end of the
>>>>>> week!
>>>>>>
>>>>>> On Aug 19, 2019, at 6:26 PM, Stephen DeSanto <rachidian at gmail.com>
>>>>>> wrote:
>>>>>>
>>>>>> I have time to go through the survey data and find the reported
>>>>>> transit benefits per employer, though I'll need the data set that contains
>>>>>> that data. :)
>>>>>>
>>>>>> Otherwise, I am going to be trying to match CTR neighborhoods to the
>>>>>> employers already in our spreadsheet, as well as adding any employers
>>>>>> mentioned in other sources/sheets on our wiki.
>>>>>>
>>>>>> On Mon, Aug 19, 2019 at 6:02 PM Tom Chartrand <tmchartrand at gmail.com>
>>>>>> wrote:
>>>>>>
>>>>>>> This is looking great, Stephen!
>>>>>>> I had put myself down to organize the survey data with respect to
>>>>>>> employers for this, but I just realized that info was removed as PII (of
>>>>>>> course)! So either Mike will need to take that on (I think Mike did the
>>>>>>> original PII removal) or we'll need to figure out an appropriate way of
>>>>>>> sharing that.
>>>>>>> I'm feeling pretty swamped myself lately, so if you (Stephen) were
>>>>>>> down to help him with the task that could be great. I can certainly still
>>>>>>> take on some of it if needed though, once we get this sorted out.
>>>>>>> Katie, maybe you could help coordinate this and make sure Mike sees
>>>>>>> this sooner rather than later?
>>>>>>>
>>>>>>> Also, do let me know if you have any more specific spots in the
>>>>>>> report where some backup from the PSRC dataset could be useful!
>>>>>>>
>>>>>>> On Sun, Aug 18, 2019 at 3:59 PM Stephen DeSanto <rachidian at gmail.com>
>>>>>>> wrote:
>>>>>>>
>>>>>>>> I've added the list of industry categories to the Google Sheet, so
>>>>>>>> that should help validate the data we add there, though it's going to
>>>>>>>> likely be a manual task to fill in industries for all the employers.
>>>>>>>>
>>>>>>>> I've also added a "citation" column, which can be the public
>>>>>>>> representation of where we got the data to make our claim. We can fuss with
>>>>>>>> the wording later.
>>>>>>>>
>>>>>>>> I should have time this week to go through our survey data and
>>>>>>>> other wiki tables to add or modify employers in the Google Sheet. Agree
>>>>>>>> that it'll be good to have solid information on our primary targets and
>>>>>>>> champions.
>>>>>>>>
>>>>>>>> On Tue, Aug 13, 2019 at 10:48 PM Harry Maher <
>>>>>>>> harryb.maher at gmail.com> wrote:
>>>>>>>>
>>>>>>>>> Just a quick update with regard to qualitative data analysis: I
>>>>>>>>> made a "Commute Survey Qualitative Data Analysis" folder on pbworks and put
>>>>>>>>> a doc with some quotes in it for the report. I tried to pull out the main
>>>>>>>>> relevant themes that I noticed discussed in the two qualitative questions
>>>>>>>>> currently in the file with a couple of quote options for each
>>>>>>>>> theme/category of response to the question.
>>>>>>>>>
>>>>>>>>> -Harry
>>>>>>>>>
>>>>>>>>> On Sun, Aug 11, 2019 at 12:54 PM Tom Chartrand <
>>>>>>>>> tmchartrand at gmail.com> wrote:
>>>>>>>>>
>>>>>>>>>> Regarding where to have this discussion - I'm just gonna continue
>>>>>>>>>> the email chain cause I haven't followed where to put the discussion on the
>>>>>>>>>> wiki, but someone feel free to steer it over there if we want to!
>>>>>>>>>>
>>>>>>>>>> A brief update regarding establishing a larger list of employers
>>>>>>>>>> to include in the dataset: basic contact information for all seattle
>>>>>>>>>> businesses, sorted by the North American Industry Classification System, is
>>>>>>>>>> available at
>>>>>>>>>> https://web6.seattle.gov/fas/slimbizsearch/ResultsPage.aspx?NAICList=Top100,
>>>>>>>>>> but it's a huge list of course, with no info on number of employees or
>>>>>>>>>> revenue to filter out the smaller ones. Still, I did send off an email
>>>>>>>>>> about getting a copy of the database just for purposes of cross-referencing
>>>>>>>>>> names and such.
>>>>>>>>>> On 8/10/19 6:42 PM, Katie Wilson wrote:
>>>>>>>>>>
>>>>>>>>>> For “neighborhood” I think it makes sense to use the “CTR
>>>>>>>>>> Network Areas” as defined here
>>>>>>>>>> <https://www.seattle.gov/transportation/projects-and-programs/programs/transportation-options-program/commute-trip-reduction-program/draft-2019-2023-networks-and-targets>
>>>>>>>>>> .
>>>>>>>>>>
>>>>>>>>>> For “industry” I think it makes sense to use the “Employment
>>>>>>>>>> Sector” categories listed on Page 12 of this CTR strategic plan.
>>>>>>>>>> <https://www.seattle.gov/Documents/Departments/SDOT/TransportationOptionsProgram/CTR_Draft_Strategic_Plan_Jan2019.pdf>
>>>>>>>>>>
>>>>>>>>>> On the ratings, I think it does make sense to lump "piggy bank"
>>>>>>>>>> and "brown tortoise" in the same rating (0), and then add a tortoise badge
>>>>>>>>>> for employers that aren’t even doing the pre-tax thing.
>>>>>>>>>>
>>>>>>>>>> Another simplification option to consider would be to lump
>>>>>>>>>> together 3 and 4 leaves. But let’s leave them separate for now and
>>>>>>>>>> depending on how things shake out we can easily combine them later.
>>>>>>>>>>
>>>>>>>>>> We don’t have any major sources of data on what benefits
>>>>>>>>>> employers provide other than:
>>>>>>>>>> — Metro public disclosure request spreadsheet
>>>>>>>>>> <https://seattletransitpasses-research.pbworks.com/w/page/133438080/First%20Public%20Records%20Request>
>>>>>>>>>> — Our commute survey
>>>>>>>>>> — Info gleaned online from company websites, asking around,
>>>>>>>>>> glassdoor etc (what I’ve found I’ve added to the relevant tables
>>>>>>>>>> in the wiki
>>>>>>>>>> <https://seattletransitpasses-research.pbworks.com/w/page/132177123/Employers>,
>>>>>>>>>> on CTR employers and “potential poster children” and “likely target
>>>>>>>>>> assessment” and “hotels”)
>>>>>>>>>>
>>>>>>>>>> Maybe it makes sense to have another string indicating sufficient
>>>>>>>>>> certainty — when we have two sources, or one very reliable source, we enter
>>>>>>>>>> an X or whatever, and that gives us the green light to display that data.
>>>>>>>>>> Also it may not make sense to put a lot of work into categorizing employers
>>>>>>>>>> into Network Area and Employment Sector until we have reliable data on what
>>>>>>>>>> benefits they’re offering.
>>>>>>>>>>
>>>>>>>>>> Speaking of Seattle Coffee Works, I spoke with their HR person a
>>>>>>>>>> few months ago and actually employees have to pay $20/month (pre-tax $) if
>>>>>>>>>> they want an ORCA card. Still a great deal but not 100% subsidy as reported
>>>>>>>>>> in the Metro data— which, I then learned, is self-reported by the company.
>>>>>>>>>> Metro only knows that all those companies are signed up for the Passport
>>>>>>>>>> program. I noted the real situation on this page
>>>>>>>>>> <https://seattletransitpasses-research.pbworks.com/w/page/133439169/Potential%20Poster%20Children>.
>>>>>>>>>> Anyway, the point is we should probably crosscheck the Metro data as much
>>>>>>>>>> as we can with our survey or other sources of information.
>>>>>>>>>>
>>>>>>>>>> (Also speaking of Seattle Coffee Works they have locations in Capitol
>>>>>>>>>> Hill & Cascade too
>>>>>>>>>> <https://www.seattlecoffeeworks.com/our-cafes.aspx>. From
>>>>>>>>>> talking with the HR person I’m pretty sure all are include in their
>>>>>>>>>> passport program, and the employees swap around a lot from location to
>>>>>>>>>> location. They probably use the Ballard location as home base for transit
>>>>>>>>>> pass purposes since that’s the least expensive zone.)
>>>>>>>>>>
>>>>>>>>>> One project would be to come up with a list of employers that
>>>>>>>>>> have name recognition (or that we are interested in for some other reason)
>>>>>>>>>> and put a little work into attaining sufficient certainty. If we posted the
>>>>>>>>>> list to a page and put a call out on social media and email I bet we’d get
>>>>>>>>>> some answers.
>>>>>>>>>>
>>>>>>>>>> On Aug 8, 2019, at 5:26 PM, Stephen DeSanto <rachidian at gmail.com>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>> Hi everyone,
>>>>>>>>>>
>>>>>>>>>> I've taken a first pass at the data schema for showing employer
>>>>>>>>>> transit benefits in our upcoming web app. In this draft, each employer
>>>>>>>>>> record is represented as follows:
>>>>>>>>>>
>>>>>>>>>> {
>>>>>>>>>> "employer": string,
>>>>>>>>>> "industry": [string],
>>>>>>>>>> "neighborhood": [string],
>>>>>>>>>> "alias": [string],
>>>>>>>>>> "rating": int,
>>>>>>>>>> "description": string
>>>>>>>>>> "badges": [string]
>>>>>>>>>> }
>>>>>>>>>>
>>>>>>>>>> *Employer* is a plain text string.
>>>>>>>>>> *Industry* is a list of strings (or a single string, if we want
>>>>>>>>>> to limit one employer = one industry).
>>>>>>>>>> *Neighborhood* is treated similarly to industry
>>>>>>>>>> *Alias* is a list of other names for the same company. For
>>>>>>>>>> example,
>>>>>>>>>> *Rating* is a numerical scale that represents the "worker's
>>>>>>>>>> monthly cost of an unlimited transit pass". The scale provided during the
>>>>>>>>>> meeting went from "4 leaves" to "brown tortoise"; aligning to the leaves,
>>>>>>>>>> that gives us a scale of [-1, 0, 1, 2, 3, 4]. We could adjust this up to
>>>>>>>>>> 0-5, or lump "piggy bank" and "brown tortoise" in the same rating.
>>>>>>>>>> *Description* is a string that describes the employer's transit
>>>>>>>>>> benefits, i.e. why they got the rating they did.
>>>>>>>>>> *Badges* is a list of strings that represent any additional
>>>>>>>>>> categories we want to assign to a company (e.g. "industry leader",
>>>>>>>>>> "polluter").
>>>>>>>>>>
>>>>>>>>>> We can make changes to this schema if it makes it easier to work
>>>>>>>>>> with our underlying data visualization platform (e.g. Tableau?
>>>>>>>>>> DataTables?), but hopefully this is a suitable starting place.
>>>>>>>>>>
>>>>>>>>>> As an example, take a hypothetical record for Seattle Coffee
>>>>>>>>>> Works.
>>>>>>>>>>
>>>>>>>>>> {
>>>>>>>>>> "employer": "Seattle Coffee Works",
>>>>>>>>>> "industry": ["restaurant"],
>>>>>>>>>> "neighborhood": ["cbd", "ballard"],
>>>>>>>>>> "alias": ["Ballard Coffee Works"],
>>>>>>>>>> "rating": 4,
>>>>>>>>>> "description": "Provides 100% ORCA Passport subsidy."
>>>>>>>>>> "badges": ["leader"]
>>>>>>>>>> }
>>>>>>>>>>
>>>>>>>>>> *Where Our Data Lives (For Now)*
>>>>>>>>>>
>>>>>>>>>> I've also taken a rough chop at getting started with the data.
>>>>>>>>>> Here, I've just taken the raw list of ORCA Business Passport employers and
>>>>>>>>>> assigned a score based on their subsidy percentage, as an example:
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> https://docs.google.com/spreadsheets/d/1HmOcG7hJLD1G0unCMPcsDnXr4RIA_PMKEE5ne-hhQR8/edit?usp=sharing
>>>>>>>>>>
>>>>>>>>>> The spreadsheet contains columns for each item of the employer
>>>>>>>>>> record, as well as some additional columns to record the raw data we have
>>>>>>>>>> on file for that employer, so we can use that data to automatically or
>>>>>>>>>> manually determine an employer's rating.
>>>>>>>>>>
>>>>>>>>>> If we have data from other sources not listed (e.g. survey data,
>>>>>>>>>> City of Seattle data), the "source_" columns can be renamed or added to
>>>>>>>>>> represent that source's data. For example, if I want to add data from the
>>>>>>>>>> TRU survey, I might rename "__source_b" to "__TRU Survey", then include
>>>>>>>>>> results from that survey in that column for each company. (The columns
>>>>>>>>>> beginning with two underscores are ones I don't expect to be publicly
>>>>>>>>>> available.)
>>>>>>>>>>
>>>>>>>>>> PBworks feels really inadequate for editing large data sets, and
>>>>>>>>>> I don't know where else to put it, so it's living in Google Sheets for now.
>>>>>>>>>> Set to read-only with the link, for now, but please request editing
>>>>>>>>>> permissions so you can add stuff to the sheet.
>>>>>>>>>>
>>>>>>>>>> Currently, my expectation is that the spreadsheet will be
>>>>>>>>>> hand-edited in Google Sheets, and then when we're ready to put live data in
>>>>>>>>>> the web app, we can export the sheet to a flat file, which we can then
>>>>>>>>>> import into a format appropriate for the website (big ol' JSON file,
>>>>>>>>>> database, whatever). Manual process, but probably fine for a project of
>>>>>>>>>> this scale; I'm open to alternatives.
>>>>>>>>>>
>>>>>>>>>> *Things To Do Next*
>>>>>>>>>>
>>>>>>>>>> Aside from the ORCA Passport data and the data we collected
>>>>>>>>>> through TRU survey / legwork (on PBworks), do we have any other data
>>>>>>>>>> sources that would provide context for a score?
>>>>>>>>>>
>>>>>>>>>> For the data sources we have, we'll have to start filling out the
>>>>>>>>>> rest of the spreadsheet, I guess?
>>>>>>>>>>
>>>>>>>>>> Also, we will need to determine:
>>>>>>>>>> a) master list of "industries" we want to support, and
>>>>>>>>>> b) "industry" field(s) for each employer
>>>>>>>>>> c) "neighborhood" field(s) for each employer we don't have one
>>>>>>>>>> for (or being more precise than what I have now)
>>>>>>>>>> d) which companies get tagged with which badges
>>>>>>>>>>
>>>>>>>>>> Hope that helps.
>>>>>>>>>>
>>>>>>>>>> In solidarity,
>>>>>>>>>>
>>>>>>>>>> Stephen
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>
>>>>>>
>>>>>>
>>>
>>
>
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