GESIS Knowledge Graph

Data Sources

The GESIS Knowledge Graph contains content from the GESIS Search which comprises information about social science research data, publications on research data and open access publications. Detailed information about the content of the GESIS Search can be found here. GESIS Search aggregates information from different data collections of GESIS. Additionally, the GESIS KG comprises links between scientific resources such as links between research data and publications, publications and instruments, and so on which are also integrated and available in the GESIS Search.

Detailed provenance information about the original data sources and the source of the links is reflected in the GESIS KG and is described in the section Provenance.

Data model

The GESIS Knowledge Graph comprises several types of scientific resources types and the links between them. The complete ontology can be found here.

The figure above illustrates the six main scientific resources types which are currently entailed in the GESIS KG. The main resources types of the GESIS Knowledge Graph are listed and described below:

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.

The figure above depicts links between different resource types with provenance. In the GESIS KG Ontology, we provide both links without provenance and links with provenance — the former for easy querying, and the latter for capturing additional metadata about how the links were created. Since the GESIS KG represents many-to-many (m:n) links between scientific resources and includes specific data about these links, additional classes for references and link metadata are incorporated into the data model.

Links between resources in the GESIS KG are either manually curated or automatically generated. Manual links are created by GESIS staff or are derived from research data bibliographies curated for specific research data programs. These manually linked resources are clearly marked as such and typically point to unique research datasets. The curation of these links is handled by the Manual Link Curation Pipeline. For automatically generated links between publications and research data, GESIS has developed the Dataset Citation Detection Pipeline. This pipeline, originatin from the DFG-funded InFoLiS project, is designed to detect and disambiguate dataset citations. It identifies mentions of research data within full texts and automatically links them to the corresponding datasets. These links are marked as automatic and may not always refer to a single, unique dataset, but rather to potential datasets used in the publication. It is important to note that the automatically generated links have not yet been evaluated by domain experts—this is planned as future work. Another pipeline, the Variable Detection Pipeline, automatically identifies links between publications and variables. This was developed as part of the DFG-funded VADIS project. Additionally, the Publication Citation Detection Pipeline identifies citation links between publications and their referenced works automatically, developed under the DFG-funded Outcite project.

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

We provide an OAI-PMH API, available at https://data.gesis.org/gesiskg/oai/, which allows you to access and harvest metadata provided by the GESIS KG in the DataCite and OpenAIRE format.

SPARQL endopint

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.

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

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

PREFIX schema: <https://schema.org/>
SELECT ?publication ?publication_title 
    ?dataset ?dataset_title
WHERE {
    ?publication schema:about ?topic.  
    ?topic schema:name "Migration"@en.
    ?publication a schema:ScholarlyArticle.
    ?publication schema:citation ?dataset. 
    ?dataset a schema:Dataset.
    ?publication schema:name ?publication_title.
    ?dataset schema:name ?dataset_title.
} LIMIT 1000

PREFIX schema: <https://schema.org/>
SELECT ?year (COUNT(?publication) AS ?count)
WHERE {
    ?publication a schema:ScholarlyArticle.
    ?publication schema:citation ?dataset.
    ?dataset a schema:Dataset. 
    ?dataset schema:about ?topic.  
    ?topic schema:name "Migration"@en.
    ?publication schema:datePublished ?year.
} GROUP BY ?year ORDER BY ?year

PREFIX schema: <https://schema.org/>
PREFIX gesiskg: <https://data.gesis.org/gesiskg/schema/>
PREFIX ddi: <http://rdf-vocabulary.ddialliance.org/lifecycle#>
SELECT *
WHERE {
    ?publication a schema:ScholarlyArticle.
    ?publication schema:name ?publication_title .
    ?variable a ddi:Variable.
    ?publication schema:citation ?variable.
    ?variable schema:name ?variable_title .
    ?variable gesiskg:studyGroup "ALLBUS"@en
}

Download

You can download the current version of the GESIS Knowledge Graph as a full RDF dump (Turtle format) as well as its underlying GESIS KG ontology at: https://doi.org/10.7802/2969

Older version:
v1.0.0: https://doi.org/10.7802/2878
v0.1.0-beta: 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.

Source Code

The source code of the GESIS KG construction pipeline is publicly available on Github. However, full reproducibility of the workflow is not possible, as the input data source, i.e., GESIS Search Elastic Search index, required for the construction process is not publicly accessible.

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., Gupta, E., Yu, R., & Zapilko, B. (2025). GESIS Knowledge Graph (GESIS KG) (Version 2.0.0) [Data set]. GESIS, Cologne. https://doi.org/10.7802/2969.