Enhancing FAIR compliance: a controlled vocabulary for mapping Social Sciences survey variables

In Social Sciences surveys, the dynamic relationship among study units and survey instruments like questionnaires, variables, questions, and response formats evolve. For instance, a longitudinal survey may feature different metrics for the same variable at various intervals, known as "waves." When reusing variables, researchers may need to modify variable attributes such as labels or names, question-wording or response scales. Therefore, offering a transparent explanation for these variable relations across different waves and studies is imperative. Although current methodologies use standards like Data Documentation Initiative – Lifecycle (DDI-LC) and DataCite to model these relationships, these frameworks fall short of capturing the complexity of variable relationships in Social Sciences. Existing DDI-controlled vocabularies for Commonality Type [[i]] employ codes—such as 'identical,' 'some,' and 'none'—to outline shifts in item elements like variables; however, this approach is insufficient for disambiguating these relationships since they are do not differentiate the variable attributes subject to change. To address this gap, we present the GESIS Controlled Vocabulary for Variables in Social Sciences Research Data [[ii]], as a first approach, which aims to enhance semantic interoperability across organizations and systems. This first approach is motivated in the context of the consortium KonsortSWD [[iii]] of the German National Research Data Infrastructure (NFDI) [[iv]]. It offers a concise textual identification for each variable relationship, supplemented by a detailed description to clarify the specifics of the relationship. These explicit relations facilitate harmonization across waves and enrich the data reuse by supporting search and browse functionality. The CV is published via the CESSDA vocabulary manager and aims to create a semantically rich, interconnected knowledge graph for Social Science Research, aligning with FAIR data principles.

[i]. DDI Alliance Controlled Vocabulary for Commonality Type. https://vocabularies.cessda.eu/vocabulary/CommonalityType?lang=en

[ii]. GESIS Controlled Vocabulary for Variables relations for Social Sciences research data. https://vocabularies.cessda.eu/vocabulary/Variables-Relations?lang=en

[iii]. KonsortSWD (Consortium for the Social, Behavioural, Educational and Economic Sciences) is funded by the National Research Data Infrastructure (NFDI) https://www.konsortswd.de/

[iv]. German National Research Data Infrastructure (NFDI) Homepage: https://www.nfdi.de/