health-data-ny-gov/deer-tick-surveillance-nymphs-may-to-sept-kibp-u2ip
Icon for Socrata external plugin

Query the Data Delivery Network

Query the DDN

The easiest way to query any data on Splitgraph is via the "Data Delivery Network" (DDN). The DDN is a single endpoint that speaks the PostgreSQL wire protocol. Any Splitgraph user can connect to it at data.splitgraph.com:5432 and query any version of over 40,000 datasets that are hosted or proxied by Splitgraph.

For example, you can query the deer_tick_surveillance_nymphs_may_to_sept table in this repository, by referencing it like:

"health-data-ny-gov/deer-tick-surveillance-nymphs-may-to-sept-kibp-u2ip:latest"."deer_tick_surveillance_nymphs_may_to_sept"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "county_centroid_state",
    "b_miyamotoi", -- Percentage of nymph deer ticks that tested positive (or proportion infected) for Borrelia miyamotoi, the bacteria that can cause a relapsing-fever like disease with symptoms like those seen in anaplasmosis patients.   Note: When taken in conjunction with tick population density (or population size), this field can give a sense of risk of encountering an infected tick. But tick population density and proportion infected can vary widely at different publicly accessible sites within a county, as well as from year to year. Testing of ticks for B. miyamotoi started in 2015. 
    "b_microti", -- Percentage of nymph deer ticks that tested positive (or proportion infected) for Babesia microti, the parasite that causes babesiosis.   Note: When taken in conjunction with tick population density (or population size), this field can give a sense of risk of encountering an infected tick. But tick population density and proportion infected can vary widely at different publicly accessible sites within a county, as well as from year to year. 
    "a_phagocytophilum", -- Percentage of nymph deer ticks that tested positive for Anaplasma phagocytophilum, the bacteria that causes anaplasmosis [or human granulocytic anaplasmosis (HGA)].   Note: When taken in conjunction with tick population density (or deer tick population size), this field can give a sense of risk of encountering an infected tick. But tick population density and the proportion infected can vary widely at different publicly accessible sites within a county, as well as from year to year. 
    "total_tested", -- Total number of nymph deer ticks that were tested for the listed bacteria or parasites. Ticks are tested individually. 
    "nymphal_density", -- The average number of nymph deer ticks (also known as blacklegged ticks or their scientific name Ixodes scapularis) collected per 1,000 meters sampled in the county. Tick population density is calculated only from the total nymph deer ticks collected (and does not include other species or life stages collected at the time of the site visit).    Note: When taken in conjunction with percentage of nymph deer ticks positive (or proportion infected) with the specified bacteria or parasite, this field can give a sense of risk of encountering an infected tick. But tick population density and proportion infected can vary widely at different publicly accessible sites within a county, as well as from year to year. Statewide tick surveillance and testing began in 2008.  
    "total_ticks_collected", -- The total number of ticks (all species and life stages) collected in the county during visits to publicly accessible sites from May to September. 
    "total_sites_visited", -- The total number of publicly accessible sites visited in the county. For the nymph dataset, this means publicly accessible sites visited from May to September.
    "county", -- The county where ticks (all species and life stages) were collected. Ticks are often collected from multiple publicly accessible sites in each county. 
    "b_burgdorferi", -- Percentage of nymph deer ticks that tested positive (or proportion infected) for Borrelia burgdorferi, the bacteria that causes Lyme disease.   Note: When taken in conjunction with tick population density (or population size), this field can give a sense of risk of encountering an infected tick. But tick population density and proportion infected can vary widely at different publicly accessible sites within a county, as well as from year to year. 
    "county_centroid", -- This is a centroid location within the county. It is used strictly for mapping purposes and does not reflect any specific place of the listed locality or county.
    "county_centroid_city",
    "county_centroid_zip",
    "county_centroid_address",
    ":@computed_region_8ire_itmf",
    ":@computed_region_9yqb_tdyd",
    ":@computed_region_assa_msit",
    ":@computed_region_5edz_4hdv",
    ":@computed_region_43an_4dx5",
    "year" -- Year in which ticks (all species and life stages) were collected.
FROM
    "health-data-ny-gov/deer-tick-surveillance-nymphs-may-to-sept-kibp-u2ip:latest"."deer_tick_surveillance_nymphs_may_to_sept"
LIMIT 100;

Connecting to the DDN is easy. All you need is an existing SQL client that can connect to Postgres. As long as you have a SQL client ready, you'll be able to query health-data-ny-gov/deer-tick-surveillance-nymphs-may-to-sept-kibp-u2ip with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at health.data.ny.gov. When you queryhealth-data-ny-gov/deer-tick-surveillance-nymphs-may-to-sept-kibp-u2ip:latest on the DDN, we "mount" the repository using the socrata mount handler. The mount handler proxies your SQL query to the upstream data source, translating it from SQL to the relevant language (in this case SoQL).

We also cache query responses on the DDN, but we run the DDN on multiple nodes so a CACHE_HIT is only guaranteed for subsequent queries that land on the same node.

Query Your Local Engine

Install Splitgraph Locally
bash -c "$(curl -sL https://github.com/splitgraph/splitgraph/releases/latest/download/install.sh)"
 

Read the installation docs.

Splitgraph Cloud is built around Splitgraph Core (GitHub), which includes a local Splitgraph Engine packaged as a Docker image. Splitgraph Cloud is basically a scaled-up version of that local Engine. When you query the Data Delivery Network or the REST API, we mount the relevant datasets in an Engine on our servers and execute your query on it.

It's possible to run this engine locally. You'll need a Mac, Windows or Linux system to install sgr, and a Docker installation to run the engine. You don't need to know how to actually use Docker; sgrcan manage the image, container and volume for you.

There are a few ways to ingest data into the local engine.

For external repositories (like this repository), the Splitgraph Engine can "mount" upstream data sources by using sgr mount. This feature is built around Postgres Foreign Data Wrappers (FDW). You can write custom "mount handlers" for any upstream data source. For an example, we blogged about making a custom mount handler for HackerNews stories.

For hosted datasets, where the author has pushed Splitgraph Images to the repository, you can "clone" and/or "checkout" the data using sgr cloneand sgr checkout.

Mounting Data

This repository is an external repository. It's not hosted by Splitgraph. It is hosted by health.data.ny.gov, and Splitgraph indexes it. This means it is not an actual Splitgraph image, so you cannot use sgr clone to get the data. Instead, you can use the socrata adapter with the sgr mount command. Then, if you want, you can import the data and turn it into a Splitgraph image that others can clone.

First, install Splitgraph if you haven't already.

Mount the table with sgr mount

sgr mount socrata \
  "health-data-ny-gov/deer-tick-surveillance-nymphs-may-to-sept-kibp-u2ip" \
  --handler-options '{
    "domain": "health.data.ny.gov",
    "tables": {
        "deer_tick_surveillance_nymphs_may_to_sept": "kibp-u2ip"
    }
}'

That's it! Now you can query the data in the mounted table like any other Postgres table.

Query the data with your existing tools

Once you've loaded the data into your local Splitgraph engine, you can query it with any of your existing tools. As far as they're concerned, health-data-ny-gov/deer-tick-surveillance-nymphs-may-to-sept-kibp-u2ip is just another Postgres schema.