IRUS Fulcrum

Documentation for the IRUS Fulcrum telescope

The IRUS Fulcrum telescope collects usage statistics for titles accessed via the Fulcrum Platform. Usage data is accessible through IRUS in much the same way as the IRUS OAPEN telescope. Unlike IRUS OAPEN, IRUS Fulcrum does not record sensitive IP address information. This makes dealing with the data much simpler.

The earliest available data for the Fulcrum platform is April 2022. It follows that all data is of COUNTER 5 standard.

Dataset Name	irus
Table Name	irus_fulcrum
Table Type	Partitioned
Average Runtime	10 min
Average Download Size	1-10 MB
Harvest Type	API
Run Schedule	Monthly on the 4th
Catch-up Missed Runs	✅
Each Run Includes All Data	❌

Airflow connections

The following airflow connections are required:

Name	Description
irus_api	The IRUS requestor_id/api_key - required to access the IRUS platform

Telescope kwargs

Fields passed as keyword arguments to the telescope upon instantiation.

Publishers (publishers)

A list of publisher names. Usage stats from Fulcrum will be filtered on these publisher names. Many institutions have many publisher names associated with them, so it is important that all related names are provided.

Telescope Tasks

Data Download

The download is done via an API call to IRUS:

https://irus.jisc.ac.uk/api/v3/irus/reports/irus_ir/?platform=235&requestor_id={requestor_id}&begin_date={start_date}&end_date={end_date}

Where the requestor ID is the API key for the IRUS API. The telescope will use the same begin and end dates (YYYY-MM) in order to retrieve data on a per-month basis. The requestor ID is the irus_api airflow connection.

A second call to the API is made with the following appended to the above URL:

&attributes_to_show=Country

Which splits the data by country, leaving us with two datasets. These datasets will be referred to as the total and country datasets.

Before making any changes to the data, these datasets are uploaded to a Google storage bucket

Data Transform

The transform step has a few things to achieve:

• Collate the total and country datasets into a single object

• Remove columns that are not of interest to us

• Add the release month to each row as a partitioning column

• Remove rows from the data that do not relate to the publisher of interest

The result of points 1 -> 3 are evident in the schema. The final point requires some communication with the publisher. This is because a single publisher may have published titles under more than one name. For example, University of Michigan has 10 associated publishing names. These names are listed as part of a dictionary in the telescope.

The resulting transformed file is uploaded to a Google Cloud bucket.

BigQuery Load

The transformed data is loaded from the Google Cloud bucket into a partitioned BigQuery table in the irus dataset, which will be created if it does not yet exist. Since the data is partitioned on the release month, there will only be a single table named irus_fulcrum.

Table Schema

name	type	mode	description
proprietary_id	STRING	NULLABLE	Proprietary identifier of the book.
ISBN	STRING	NULLABLE	ISBN of the book.
book_title	STRING	NULLABLE	Title of the book
publisher	STRING	NULLABLE	The publisher
authors	STRING	NULLABLE	The names of the authors
event_month	STRING	NULLABLE	The investigated month.
total_item_investigations	INTEGER	NULLABLE	The total number of item investigations.
total_item_requests	INTEGER	NULLABLE	The total number of item requests.
unique_item_investigations	INTEGER	NULLABLE	The number of unique item investigations.
unique_item_requests	INTEGER	NULLABLE	The number of unique item requests.
country	RECORD	REPEATED	Record to store statistics on the country level.
country.name	STRING	NULLABLE	The country name of the client registered by IRUS.
country.code	STRING	NULLABLE	The country code of the client registered by IRUS.
country.total_item_investigations	INTEGER	NULLABLE	The total number of item investigations.
country.total_item_requests	INTEGER	NULLABLE	The total number of item requests.
country.unique_item_investigations	INTEGER	NULLABLE	The number of unique item investigations.
country.unique_item_requests	INTEGER	NULLABLE	The number of unique item requests.
release_date	DATE	REQUIRED	Last day of the release month. Table is partitioned on this column.