Green Books

About

The Negro Motorist Green Books (later, The Negro Travelers' Green Books) are a series of travel guides published from 1936 to 1966 that contain a list of businesses a black traveler could patronize without fear of discrimination. Their contents contain a historical map of safe havens for black travelers across American during the Jim Crow era.

This import is an import of multiple annual volumes of directory of related listings. These listings are of addresses, some with typos, some with incomplete addresses. As such, the geocoding process will be more important than in already geo-associated datasets.

Many of the entries are included in multiple years' editions of the Green Book. As such, thinking about the structure of relations and how to indicate inclusion across multiple versions of the directories will be critical.

What questions will this import help answer?

• Once complete, any sort of data query about location and category-based analysis of the Green Books
• Information about who supplied the entries to Victor Green for inclusion. Did they live in a particular part of town? Were there other black neighborhoods in these towns, either unserved or underserved, by the Green Books?
• This will help serve as a foundation for further expansion into the documentation of the business environments, as well as "velcro" for attaching other related information.
• Point data for where some businesses were located during redlining. See: Mapping Inequality.

Approach

The general strategy here – which is open for discussion and adjustment – is this:

1. Recognize that a complete dataset will be much easier to work with than adding to partially complete datasets
2. Reach out to owners of subsets of this data to see if they'd be willing to share and combine with others
   1. Most complete data: Primary target / most complete dataset: UVA's The Architecture of the Negro Travelers' Green Book. This is the front end for a database covering Green Book entries, links to detailed histories of entries, multiple addresses, different spellings of the same place, images, and stories. Unfortunately, the data is incomplete and does not cover some states.
   2. Additional data: some enriched data is found on state-specific websites, such as the North Carolina African American Heritage Commission's Oasis Spaces website. Their incremental improvements to the data should be merged with the data planned for this import.
3. Experiment with existing Green Book data sets on OHM in preparation for obtaining more complete data:
4. Tagging: Identify a rich set of tags that will expose the information contained in the directories, encourage linking to related information and datasets, as well as the OHM-specific translation of source attributes.
5. Validation: Set up a process for validating the data associated with each entry.

Team Members & Coordination

Requirements

• requirements

Volunteers

To sign up, please just add your name here and start

• Jeff Meyer; OHM User: jeffmeyer
• your name here!
• your friend's name here!

Coordination

• tbd

Validation steps

• Map Roulette?

Mapping Scope

The primary mapping (i.e., assigning geometries to our entities) scope for this project will the geocoding of the addresses included in the directories.

UNDER DISCUSSION: Geocoding process

Need a best practices description for geocoding.

Tagging standards

See also: Create a TagInfo project page & project file (TagInfo project file documentation).

UNDER DISCUSSION: Tagging sources vs. entities

How do we separate metadata about the entity from metadata about the source? The Green Books often only included a partial name, leaving off the descriptive parts of names. "The Saint James Hotel" would be listed as "The Saint James" under the category "Hotels."

Example: Big Buster Cafe

• The listing in the source is just "Big Buster" with the category "Tavern"
• name=Big Buster Cafe" seems appropriate, as that's what the local business directory included
• Should the directory text be preserved? Assuming yes, source:name seems inappropriate for "Big Buster", name:source is sort of confusing, given the whole use of source at multiple locations in the keyspace. gb:name=Big Buster is just one possibility and should be viewed as strictly temporary.

UNDER DISCUSSION: Mapping of Green Book categories to OSM tagging conventions

Here is a proposed initial draft of a mapping of Green Book categories to OHM tags:

Caption text

Green Book category	Primary Tag	Additional tags	Notes
Automobiles	shop=car
Automotives	shop=car shop=car_parts shop=car_repair shop=tyres		This category contains multitudes... of options.
Barber Shops	shop=hairdresser	hairdresser=barber
Beauty Parlors	shop=hairdresser		not sure if this needs an additional
Beauty Shops	shop=beauty
Chinese Restaurants	amenity=restaurant	cuisine=chinese
Cleaners	amenity=cleaners		needs review
Country Clubs			need something? leisure=country_club
Dance Halls	leisure-dance		leisure isn't usually used on a node
Drug Stores	amenity=pharmacy
Druggist	amenity=pharmacy
Garages	shop=auto_repair
Haberdasher	shop=clothes
Hotels	tourism=hotel
Liquor Stores	shop=alcohol
Millinery	shop=clothes
Movers			need something? amenity=movers?
Night Clubs	amenity=nightclub
Nights Clubs	amenity=nightclub
Pharmacy	amenity=pharmacy
Points of Interest in New York City			should tag as appropriate for the POI
Pool Halls	leisure=pool_hall		leisure isn't usually used on a node; Overture has a pool_hall place
Radio Service			need something? shop=radio_repair?
Recreation Parks	leisure=park		leisure isn't usually used on a node
Resorts	leisure=resorts		leisure isn't usually used on a node
Restaurants	amenity=restaurant	cuisine=*	add cuisine, if known; find menu & link to that!
Road Houses	amenity=restaurant or amenity=pub or tourism=hotel		can vary; should we propose a new addition? roadhouses are usually bar+restaurant+hotel. Maybe tourism=hotel
Sanitariums	amenity=sanatorium
School Of Beauty Culture	amenity=school
Service Stations	amenity=fuel
Tailors	shop=tailor
Taverns	amenity=pub
Taxicabs	amenity=taxi
Tourist Homes	tourism=guest_house
Trailer Parks & Camps			need something? leisure=trailer_camp? leisure=trailer_park; campsite?
Trailers Park			need something? leisure=trailer_park?
Wine & Liquor Stores	shop=alcohol
Wines & Liquor Stores	shop=alcohol		alcohol

UNDER DISCUSSION: should you link to every directory as a source

Each entry might have 8 or more source tags. How many is enough?

How do we identify every map or every source where an entity might be depicted? Do we?

UNDER DISCUSSION: linking to source directory entries

Similar to the prior discussion, do we link to an image of every page containing that entry? This seems like it would be helpful for validation, but how do we help the validator quickly find the right year/image?

See Big Buster Cafe for an example of this entry-to-page image linking.

Tagging dates: EDTF is your friend

Please be sure to use EDTF date keys, such as `start_date:edtf` and `end_date:edtf`

Because the directories are merely listings at a specific point in time, and do not definitively indicate a start or end date, we should assume that an entry that is only in 1 directory would be listed something like this:

start_date=1946
start_date:edtf=[..1946]
end_date=1947
end_date:edtf=[1946..]

But! Because entries may be listed in more than 1 year, each entry might reasonably be tagged as:

start_date=<first directory year for that entry>
start_date:edtf=[..<first directory year for that entry>]
end_date={last directory year for that entry>+1
end_date:edtf=[<last directory year for that entry>..]

NOTE: The offset of "+1" for the end_date tagging is purely a rendering convention.

UNDER DISCUSSION: Project-specific tagging

Querying for this tag should yield all of the OHM entities involved with the project.

project=ussblackhistory

Source tagging

• Looking for CC0 datasets
• Adding appropriate license tags where necessary & where

`license=CC0-1.0` uses the SPDX abbreviation for the Creative Commons CC0 "No Rights Reserved" license.

Wikimedia tagging

Linking objects in OHM to related entities in Wikidata and Wikipedia will enhance the richness of the data in both places and make OHM's data part of a wider fabric of Linked Open Data across the internet.

Wherever possible, please tag all objects with appropriate wikimedia tags:

wikipedia=en:Austrian Circle
wikidata=Q306390

Project Examples in OHM

• 1941 Green Book: The Smithsonian Institution has published a transcription of the 1941 Green Book that was produced by their volunteers. User:jeffmeyer has translated and shared the contents of this file into a https://docs.google.com/spreadsheets/d/17dzlaavKUz3RHvxq5ZL_csdvoFknctt65YPWLAb3Rcw/edit#gid=540995247 spreadsheet].
• 1947 Green Book: NYPL labs created a geojson file containing a subset of entries from this volume. This data file has some known pervasive errors and needs to be updated.

Next steps once complete

• Enrich place points with additional information, such as images, business directory listings, newspaper articles, etc.
• Add local neighborhood context for the surrounding spaces, such as those found on Sanborn Maps
• Add city-level context for the entries by adding information like redlining from Mapping Inequality

Resources

• Wikipedia
• UVA Green Book Resource Listing
• Green Book scans: NYPL has scanned versions of many (but not all) Green Books. These scans will enable an updated text extraction pipeline, as well as enabling direct links from pages to entries for validation.