Getty Hierarchy

This repository contains both a binary executable and a Python module written in Rust:

• The executable can be used to parse one of the Getty vocabularies NTriples dumps into two hashmaps (read below for info on how these were built):
  1. One holding the vocabulary hierarchy;
  2. One being a term_id: term_label map.
• The Python module is very simple and can be used to reconstruct the hierarchy of a term, given its id.

The purpose of this project is to offer an easy and fast way to reconstruct the hierarchy of any term in Python, which can come in handy when this operation needs to be performed several times, without the need to call the Getty API every time.
NOTICE: both the module and the executable have been tested on Linux only, against the AAT vocabulary only.

Little disclaimer

Notice that we use term or node as synonyms. I am nowhere near an expert of Getty's vocabularies nor an expert of the Linked Open Data format and this project was born as a weekend project, since I needed to reconstruct the hierarchy of labels used in a dataset (calling the web API proved to be quite expensive for a large number of labels).
Furthermore, this project is in no way linked with or supported by the Getty vocabularies project.

The Python module

Installing

This repository offers Python wheels for versions 3.6, 3.7 and 3.8 which were built with Maturin (you can find them in the binaries directory, at the root of this repository). This means you can simply install the module by downloading the right wheel file for your Python version and run:

pip install getty_hierarchy-1.0.0-cp3x-cp3xm-manylinux1_x86_64.whl

At the moment, the repository hosts Linux and MacOS wheels only, but I'm planning to release for Windows as well (see Building from source if you need the package for another platform in the meantime).

Usage

Once installed, usage of the module is pretty straightforward.
First, you need to import the getty_hierarchy module:

import getty_hierarchy

Then, you should construct the only class exposed by the API, that is the Hierarchy class.
You can do this in two ways:
by calling the base constructor

hierarchy = getty_hierarchy.Hierarchy()

This will load into memory both the hierarchy and term-label pickled maps for the AAT vocabulary.
If instead you wish to use your own pickled files, you can do that by calling the Hierarchy.from_custom_pickled static method

hierarchy = getty_hierarchy.Hierarchy.from_custom_pickled(
        "./path_to_pickled_hierarchy.bin", 
        "./path_to_pickled_termmap.bin"
    )

The first argument is the path to the pickled hierarchy map, whereas the second is the path to the pickled term-label map: these can be generated with the binary executable offered in this repository (see Using the executable).
Furthermore, you can pass an empty string as the second argument if you don't need the term-label map.

Once the Hierarchy class is constructed, you can use two methods:
the get_parents method will return the list of a term parents, sorted so that the closest parent comes first:

# eg. node_id = 300053049
hierarchy.get_parents(node_id)

# Output
[300053043, 300229467, 300053003, 300053001, 300264090]

If you feel the need, you can test the parents list correctness by visiting the web API page and using id 300053049 as input.
if a term has more than one parent (or if its parents do), the output will be as follows:

hierarchy.get_parents(300073708)

# Output
[[300055980, 300055126, 300264086], [300389850, 300015646, 300264088]]

The religions term has two parents in the AAT hierarchy, whose ids are 300055980 and 300389850; as you may notice, the resulting list in the Python code is actually a list of lists:
the preferred parent (more info in the How the hierarchy is built section) comes first and the other parents come afterwards (with no specific order). This means that the first list in our example contains the "preferred" hierarchy (eg. what is listed here under Hierarchical position) and the second list holds what is listed here under Additional parents.
This is a recursive behaviour, meaning that if in this example node 300055126 had two parents, then we would have had a list of lists as the third element, instead of the term_id 300264086.

The second method you can use on the Hierarchy class is the get_node_label method, which you can use to retrieve any term preferred label (again, see [How the hierarchy is built](#How the hierarchy is built) for more info).
It works pretty intuitively as follows:

hierarchy.get_node_label(300053049)

# Output 
# dyeing

Notice: this will output an empty string in case you constructed the Hierarchy class with the from_custom_pickled static method and passed an empty string as the second argument.

Building from source

In order to build from source you will need to install the Rust nightly toolchain: see here for how to install Rust and here for how to use the nightly toolchain.
Once you correctly setup everything, build by simply running:

cargo build --release

you will find the executable in target/release/getty_hierarchy_bin.
To build the Python module, I recommend using Maturin:

maturin build --release

you will find the Python wheels in target/wheels/.

Using the executable

Download the getty_hierarchy_bin file you can find in the binaries directory at the root of this repository (or build it). You can list all the options by running:

./getty_hierarchy_bin --help

which should produce the following output:

Getty hierarchy builder 1.0
Alessio Molinari <[email protected]>

This program will parse a getty nt triples file into two maps: one will be a hierarchy map, the other will be a
term_id:label map (optional).
Finally, these maps will be bincoded (or pickled, if you're familiar with Python) into two file .bin which you will find
in your current working directory.
These files can be used in the Python module to quickly build the hierarchy or the term:label map.

USAGE:
    getty_hierarchy_bin [FLAGS] <FILE>

FLAGS:
    -h, --help           Prints help information
    -V, --version        Prints version information
        --no-term-map    If set, the program won't generate the term:label map

ARGS:
    <FILE>    Getty NT triples dump file

Usage example: generate the hierarchy and term:label maps

First, download one of the Getty NTriples zip, eg. the AAT one and extract it. Then you can run:
./getty_hierarchy_bin AATOut_Full.nt
This will probably take a minute or two and will output the two pickled files bincoded_hierarchy.bin and bincoded_termmap.bin.

How the hierarchy is built

The hierarchy map is built by parsing the NTriples dump available on the Getty website. The parents of any term are retrieved using the http://vocab.getty.edu/ontology#broader property.
If any term has more than one parent, the preferred parent (retrieved via the http://vocab.getty.edu/ontology#broaderPreferred property) is listed before the others.
The term:label map is instead built by retrieving the http://vocab.getty.edu/ontology#term and the http://vocab.getty.edu/ontology#prefLabelGVP properties: however, the term id which should be used to retrieve the label is the same used to retrieve a term parents in the hierarchy map (instead of using the http://vocab.getty.edu/aat/term/*id* term id).

More technical details

As a consequence of what we said in the previous section, we need to allocate a temporary HashMap to build the term:label map. This is better explained with an example: when we build the hierarchy map we use the term_id retrieved with the http://vocab.getty.edu/ontology#broader property as a key. For any term, this term_id is not the same we get from the http://vocab.getty.edu/ontology#term property and, as a consequence, if we wanted to retrieve the parent labels of a term, we'd have to use different ids wrt. what we have in the returned list. For instance, the id of the term dyeing is 300053049; however, its label has id 1000053049 (see here). In order to allow us to map the term_id we use in the hierarchy to its label value as a string, we need to first retrieve the (let's call it) term_label_id, map it to its string value and then remap that string value to the above mentioned term_id. As such, building the term:label map has a quite consistent overhead compared to simply building the hierarchy map and that is why it is possible to entirely skip it, both in the executable and in the Python module. If you have any suggestion on how to improve this, feel free to open an issue :)

Credits

This project was inspired and helped by the already existing repository from mdlincoln, available at https://github.com/mdlincoln/getty_vocab (those scripts in ruby were pretty helpful to understand how to approach this in the first place). Also, take a look at his blog post here https://matthewlincoln.net/2014/02/21/hierarchies-of-the-getty.html

Of course, this whole project was made possible by the dumps made available by the Getty project at http://vocab.getty.edu