Ricgraph scripts can be found in various places:
- Directory harvest_to_ricgraph_examples: scripts for harvesting sources and inserting the results in Ricgraph. Documentation for these scripts (this file).
- Directory export_ricgraph_examples: scripts to export items from Ricgraph. Documentation for these scripts.
- Directory find_enrich_ricgraph_examples: scripts for finding and enriching items from Ricgraph. Documentation for these scripts.
- The module code ricgraph.py can be found in directory ricgraph.
- The code for Ricgraph Explorer can be found in directory ricgraph_explorer. Documentation for Ricgraph Explorer.
- Documentation for writing your own scripts.
All code is documented and hints to use it can be found in the source files.
Return to main README.md file.
One of the most useful features of Ricgraph is that it is possible to harvest sources that are important to a user or organization. By doing this, one is able to create a system that perfectly suits a certain information need of that person or organization. In creating harvest scripts, it is possible to harvest only that information that is relevant for a certain purpose. For example, one of the example harvest scripts harvests the Utrecht University staff pages. These pages cannot be harvested by other organizations due to the privileges required. Also, it is possible to harvest a source that is internal to an organization. Ricgraph can be installed on any internal or external accessible system according to your needs, so the data in Ricgraph is only accessible for persons of a certain organization, or for anyone.
There are five examples of harvest scripts provided, for
- harvest of OpenAlex;
- harvest of Pure;
- harvest of Utrecht University data sets;
- harvest of Utrecht University staff pages;
- harvest of software from the Research Software Directory.
There is also a script for batch harvesting, batch_harvest.py. You can use this script to run a number of harvest scripts after each other. It can be adapted to your needs, see the Python code in the script.
It is best to run harvest scripts in a specific order.
Return to main README.md file.
Ricgraph uses the term organization abbreviation. This is a string of a few letters that can be passed to some harvest scripts to determine for which organization such a script will harvest data. Examples are UU or UMCU.
You will see this in keys in the Ricgraph initialization file. Examples are organization_name_UU or organization_name_UMCU. The general format is key_XXXX, with XXXX the organization abbreviation.
If your organization abbreviation is not in the Ricgraph initialization file, feel free to add one. You can use any (short) string and pass it to a harvest script. You only need to insert keys (and values) for the organization(s) you are planning to harvest.
To harvest OpenAlex, use the script harvest_openalex_to_ricgraph.py.
Usage
harvest_openalex_to_ricgraph.py [options]
Options:
--empty_ricgraph <yes|no>
'yes': Ricgraph will be emptied before harvesting.
'no': Ricgraph will not be emptied before harvesting.
If this option is not present, the script will prompt the user
what to do.
--organization <organization abbreviation>
Harvest data from organization <organization abbreviation>.
The organization abbreviations are specified in the Ricgraph ini
file.
If this option is not present, the script will prompt the user
what to do.
This script harvests OpenAlex Works, and by harvesting these Works, it also harvests OpenAlex Authors. This script needs the parameters organization_name_XXXX, organization_ror_XXXX and openalex_polite_pool_email to be set in the Ricgraph initialization file. XXXX is your organization abbreviation.
There is a lot of data in OpenAlex, so your harvest may take a long time. You may reduce this by adjusting parameters at the start of the script. Look in the section "Parameters for harvesting persons and research outputs from OpenAlex": OPENALEX_RESOUT_YEARS and OPENALEX_MAX_RECS_TO_HARVEST.
To harvest Pure, use the script harvest_pure_to_ricgraph.py.
Usage
harvest_pure_to_ricgraph.py [options]
Options:
--empty_ricgraph <yes|no>
'yes': Ricgraph will be emptied before harvesting.
'no': Ricgraph will not be emptied before harvesting.
If this option is not present, the script will prompt the user
what to do.
--organization <organization abbreviation>
Harvest data from organization <organization abbreviation>.
The organization abbreviations are specified in the Ricgraph ini
file.
If this option is not present, the script will prompt the user
what to do.
--harvest_projects <yes|no>
'yes': projects will be harvested.
'no' (or any other answer): projects will not be harvested.
If this option is not present, projects will not be harvested,
the script will not prompt the user.
With this script, you can harvest persons, organizations and research outputs. This script needs two parameters in the Ricgraph initialization file: the url to Pure in pure_url_XXXX, and the Pure API key in pure_api_key_XXXX. XXXX is your organization abbreviation.
There is a lot of data in Pure, so your harvest may take a long time. You may reduce this by adjusting parameters at the start of the script. Look in the sections "Parameters for harvesting persons/organizations/research outputs from Pure". E.g., for research outputs you can adjust the years to harvest with the parameter PURE_RESOUT_YEARS and the maximum number of records to harvest with PURE_RESOUT_MAX_RECS_TO_HARVEST.
Pure has two APIs, a READ and a CRUD API. The Pure READ API ("old" API) is only for reading data from Pure. The Pure CRUD API ("new" API) can be used to create, read, update and delete data in Pure (hence the name: CRUD). You do not need to specify which API you want to use, the script will be able to determine it for you (just include the API key in the initialization file). The author recommends to use the READ API. You can use both of them to harvest data from Pure, but each of them has its own advantages and disadvantages:
- The Pure READ API has a number of filters, which allow to reduce data requested from Pure on the Pure server, thereby preventing this data to be sent to the computer which is running the Pure harvest script, and for the harvest script, to process all this data. E.g., the READ API has a filter for persons, so only active persons in Pure will be sent to the harvesting computer, thereby reducing the number of persons to process in the harvest script from all persons in Pure to only active persons in Pure. Another filter is the start and end publication year for research outputs. This makes it possible for the Pure harvest script to only process research outputs from a certain year, instead of all research outputs in Pure. This prevents potential memory problems.
- The Pure CRUD API allows the Pure administrator to specify which Pure fields are allowed to be sent from the Pure server to the computer that is running the Pure harvest script. This allows for only sending data that is requested. However, since this API is in development, a lot of the filters present in the READ API do not exist (yet), especially the filters mentioned in the previous bullet. That means, if you run the Pure harvest script, you might encounter memory problems while harvesting research outputs due to the number of research outputs in Pure, unless you set PURE_RESOUT_MAX_RECS_TO_HARVEST in the Pure harvest script to some suitable value.
You can also harvest projects from Pure, if your organization uses them. You will need to use the Pure READ API, harvesting projects with the PURE CRUD API has not been implemented yet.
Projects will be connected to related persons, related organizations (the chair/department/faculty the person is from), related research outputs, and related projects (if any).
Note that it can happen that you may find a project that is connected to a person-root which only has a PURE_UUID_PERS and nothing else, or that you may find a project that is connected to a research output which only has a PURE_UUID_RESOUT and nothing else. This is probably caused by the Pure harvest script that (in its standard configuration) only harvests active persons, those are persons who are working at your organization at the time of harvest (so you will not have any information about persons that have worked on the project, e.g. PhDs or postdocs, since they may already have left your organization), and only harvests research outputs from 2020 onward, and your project may have research outputs from before 2020.
To harvest Utrecht University data sets from the data repository Yoda, use the script harvest_yoda_datacite_to_ricgraph.py.
Usage
harvest_yoda_datacite_to_ricgraph.py [options]
Options:
--empty_ricgraph <yes|no>
'yes': Ricgraph will be emptied before harvesting.
'no': Ricgraph will not be emptied before harvesting.
If this option is not present, the script will prompt the user
what to do.
This script can be used out of the box since it doesn't need an API key.
To harvest the Utrecht University staff pages, use the script harvest_uustaffpages_to_ricgraph.py.
Usage
harvest_uustaffpages_to_ricgraph.py [options]
Options:
--empty_ricgraph <yes|no>
'yes': Ricgraph will be emptied before harvesting.
'no': Ricgraph will not be emptied before harvesting.
If this option is not present, the script will prompt the user
what to do.
This script needs the parameter uustaff_url to be set in the Ricgraph initialization file.
To harvest software packages from the Research Software Directory, use the script harvest_rsd_to_ricgraph.py.
Usage
harvest_rsd_to_ricgraph.py [options]
Options:
--empty_ricgraph <yes|no>
'yes': Ricgraph will be emptied before harvesting.
'no': Ricgraph will not be emptied before harvesting.
If this option is not present, the script will prompt the user
what to do.
--organization <organization abbreviation>
Harvest data from organization <organization abbreviation>.
The organization abbreviations are specified in the Ricgraph ini
file.
If this option is not present, the script will prompt the user
what to do.
This script needs one parameter in the Ricgraph initialization file: rsd_organization_XXXX. XXXX is your organization abbreviation. It can be used out of the box since it doesn't need an API key.
The order of running the harvesting scripts does matter. The author harvests only records for Utrecht University and uses this order:
- harvest_pure_to_ricgraph.py (since it has a lot of data which is mostly correct);
- harvest_yoda_datacite_to_ricgraph.py (not too much data, so harvest is fast, but it contains several data entry errors);
- harvest_rsd_to_ricgraph.py (not too much data);
- harvest_openalex_to_ricgraph.py (a lot of data from a number of sources);
- harvest_uustaffpages_to_ricgraph.py.
Best practice is to start with that source that has the most data. If you don't have an API key for Pure, one can best start with the harvest script for OpenAlex.
For making your own harvesting scripts, refer to the code used in the harvest scripts described above, and read How to make your own harvesting scripts.