GESIS Knowledge Graph (beta)

Maxine

Maxine is a PhD student in the sociology. She is searching for most recent surveys covering questions on migration and publications analysing these datasets. As a newbie, she is uncertain about which academic search portal to use for finding such inter-connected information. The GESIS KG contains links between social science research data and publications. This data is integrated in the GESIS Search portal. Maxine can use the GESIS Search to find the information she needs.

You can find an example SPARQL query here.

Will

Will is a senior researcher in information science. In his research, he is investigating citation behaviour and usage of data in different scientific disciplines across time. To analyse data citation and usage behaviour in the social science domain, Will can query the necessary data from the GESIS KG via its provided SPARQL endpoint. Alternatively, he can download the KG as a dump file to analyse it offline with other preferred tools. The provided documentation of the underlying schema of the GESIS KG helps him to understand the structure of the data.

You can find an example SPARQL query here.

Nancy

Nancy is a research data engineer and works in a research infrastructure organization. In her current project, she needs to integrate metadata from scientific resources from GESIS and other organizations into another search system. For doing so, she needs to access and harvest metadata from the GESIS KG via an OAI-PMH API. The OAI-PMH API of the GESIS KG will allow Nancy to harvest the metadata from GESIS she needs in a standardized format. The webpage of the API will also provide documentation for Nancy on how to use the API and how to harvest the data.

Resources and entities

The GESIS Knowledge Graph comprises several types of scientific resources, entities and relationships between them. The latest version of the GESIS Knowledge Graph ontology can be found in the Download section.

The figure above illustrates the three main scientific resources which are currently entailed in the GESIS KG. We distinguish between scientific resources and entities. The main resources and entities of the GESIS Knowledge Graph are listed and described below:

Relationships / links between resources

This section describes the relationships between scientific resources in the GESIS Knowledge Graph and how they are represented in the data model.

Since the GESIS KG holds m:n links between scientific resources and specific data about the links between resources, additional classes determining references and link metadata are included into the data model. In order to enable also a direct link between two resources without details about the link, but for easier querying, we will add direct links in the next release of the data model.

The links between resources are either manually curated or automatically generated. The manual links are determined by employees of GESIS or are provided via research data bibliographies that are created and curated for specific research data programs. The research data linked in this way are marked as manual and lead to unique research data sets. For the automatically generated links between publications and research data, an internally developed pipeline for dataset citation detection and disambiguation is used which is a further development of the InfoLink tool. This pipeline is used to identify the mention of research data in full texts and then automatically links them to the mentioned research data. The linked research data are marked as automatic and do not necessarily refer to an unique research data set but to possible research data that that is used to create the publication. It is important to mention that the automatically generated links have not yet been evaluated by domain experts.

Provenance

In the following table, it is described how provenance information is reflected in the GESIS KG. In different properties, it is captured from which data source within GESIS Search a particular resource is originating, from where a mentioned dataset is originating, and from which link detection pipeline or manual effort a link is originating as well as versioning information.

Persistent identifiers

Resources and entities in the GESIS Knowledge Graph hold several identifiers. While this includes persistent identifiers like DOIs assigned by PID authorities, there are also identifiers assigned to resources by the authority of the data source. Thirdly, a dereferenceable URI within the namespace of the GESIS Knowledge Graph has been assigned to every resource and entity which is part of the graph. The table below gives an overview of all identifiers which are present in the GESIS Knowledge Graph.

The GESIS KG uses the same IDs for its resources like the IDs in URLs used by the GESIS Search, i.e. URIs of the GESIS KG can be easily constructed if the URL, resp. the ID of a scientific resource in the GESIS Search is known.

Examples
GESIS Search URL of a resource: https://search.gesis.org/research_data/ZA5280
GESIS KG URI of the same resource: https://data.gesis.org/gesiskg/resource/ZA5280

Dataset statistics

APIs

OAI-PMH API (tba)

We will provide an OAI-PMH API which will allow you to access and harvest metadata provided by the GESIS KG in the oai_datacite and berd format. This API will come with a dedicated website and documentation.

SPARQL endopint (beta)

You can explore the data within the GESIS Knowledge Graph using SPARQL queries at the following SPARQL endpoint: https://data.gesis.org/gesiskg/sparql
Below you can find some example SPARQL queries.

SELECT ?id ?title
WHERE {?id ?p <https://schema.org/ScholarlyArticle>.
       ?id <https://schema.org/name> ?title.
} 
LIMIT 10000

SELECT *
WHERE {<https://data.gesis.org/gesiskg/resource/ZA5282> ?p ?o}

SELECT ?publication ?publication_title ?dataset ?dataset_title
WHERE {?publication <https://schema.org/about> ?topic.  
       ?topic <https://schema.org/name> "Migration"@en.
       ?publication ?p <https://schema.org/ScholarlyArticle>.  
       ?publication <https://data.gesis.org/gesiskg/schema/reference> ?r.  
       ?r ?p1 <https://data.gesis.org/gesiskg/schema/DatasetReference>. 
       ?r <https://data.gesis.org/gesiskg/schema/referenceMetadata> ?m. 
       ?m ?p2 <https://data.gesis.org/gesiskg/schema/LinkMetadata>. 
       ?m <https://schema.org/mainEntity> ?dataset.
       ?dataset ?p3 <https://schema.org/Dataset>.
       ?publication <https://schema.org/name> ?publication_title.
       ?dataset <https://schema.org/name> ?dataset_title.
}

SELECT ?year (COUNT(?publication) AS ?count)
WHERE {?publication ?p <https://schema.org/ScholarlyArticle>.
       ?publication <https://data.gesis.org/gesiskg/schema/reference> ?r.  
       ?r ?p1 <https://data.gesis.org/gesiskg/schema/DatasetReference>. 
       ?r <https://data.gesis.org/gesiskg/schema/referenceMetadata> ?m. 
       ?m ?p2 <https://data.gesis.org/gesiskg/schema/LinkMetadata>. 
       ?m <https://schema.org/mainEntity> ?dataset.
       ?dataset ?p3 <https://schema.org/Dataset>. 
       ?dataset <https://schema.org/about> ?topic.  
       ?topic <https://schema.org/name> "Migration"@en.
       ?publication <https://schema.org/datePublished> ?year .
} 
GROUP BY ?year
ORDER BY ?year

Download

You can download the GESIS Knowledge Graph as a full RDF dump as well as its underlying ontology at Zenodo:
https://doi.org/10.5281/zenodo.14229945

GESIS Search

The GESIS Knowledge Graph is integrated in the GESIS Search. Links between scientific resources are included in the result list and detailed views of search results.

License

The GESIS Knowledge Graph is available for access, download, and reuse under a Creative Commons Attribution 4.0 license since the license of some input sources is CC-BY as well.
If you are using the GESIS Knowledge Graph or parts from it, please cite the GESIS KG as follows:

Biswas, D., & Zapilko, B. (2024). GESIS Knowledge Graph (1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14229945

Versions and changelog