Comments (3)
I have some detailed notes on my effort to stand this up in a containerized local environment ... Kubernetes. Please reach out: [email protected].
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- ID input requirements for geocoder testing
○ Jim's analyst is running these tests, modified DeGauss, all testing in a jupyter notebook
○ Benchmarking project: Where do these geocoders perform well, where they are off, where they totally fail
- Test dataset for geocoding:
○ 104K public service locations, ~30K rural, ~3K Rural-Tribal and 26K non-tribal Rural
○ Next step: parsing of address strings for "junk" addresses… will keep them in as negative control.
○ How do we have an address standardization software
§ Address standardization: formatting, and tests is this a real address
§ Tim: no one address standardizer will work for all four of those geocoders
□ The PostGIS geocoder has a standardizer in it
□ Wrote one for Nominatim
□ TODO (where do we start this"grid"/catalog of standardizers) :Andrew suggests a catalog of standardizers to suit everyone's needs, at least start collecting them, understanding their performance, but not fully described on our end.
§ This is a pre-geocoder workflow step… standardized and then fed in to the geocoder.
§ The three geocoders do not have an ingrained standardizer
§ ArcGIS streetmap was recommended… not OSS, not free, requires license.
○ Cybersecurity vulnerability assessment of the geocoders:
§ Each are deployed on docker, which is fine
§ However, the docker dependencies are >5years old and have some vulnerability elements
§ Will reach out to Cole Brokamp (DeGauss), who to reach out to for Nominatim?
§ Jimmy thinks they will maintain docker image locally and then pass over to Palantir
§ Have decided on the upgraded version of the linux for the image, then will pass it back to Palantir
§ CLAD project goal is the get the best geocode across any location, using multiple geocoders… the more geocoders the harder to maintain
§ Tim suggests: If youre ready to pay for ArcGIS, go there. If not use OSM.
Tims approach is to do whatever is possible with OSM and then fall back on ArcGIS
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@kzollove, @jphuong, @AEW0330: it looks like from Jim's presentation and Kyle's write up that longitude and latitude will have a provenance. Where are you thinking we might capture this provenance? It could be both a workflow and its execution environment(s). Given Andrew's suggestion that we might use RO-Crate (which describes provenance and workflows on top of schema.org and JSON-LD), where might these knowledge graphs go? And will we be able to author them with the same authoring tool we are exploring at #324?
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Related Issues (20)
- Identify Datasets for testing SDoH and Exposome vocabularies HOT 4
- [Use Case]: Evaluating fitness of WorldFAIR for OHDSI/GIS HOT 10
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