Exploring data with DP-R|EX

Functionality and use of the data explorer

No registration is required to make full use of the data explorer. The search interface is clearly laid out and allows users to search the indexed research data either via a free text search and/or to generate a hit list in combination with the filter categories provided. The subject-specific description categories are also displayed as tags in each study description, and it is possible to use these tags to further filter the hit list. This also ensures a quick overview of the study content relevant to the research area, so that related or new subject areas can be accessed quickly. Individual hits or a selected hit list can also be temporarily saved or exported. 

The study descriptions include a direct link to the data repositories. As data from research on right-wing extremism and racism is often sensitive and requires special protection, its use may be subject to certain access conditions. In general, the data is available free of charge to users for their own scientific analysis purposes, but prior registration with the data-holding organisation may be necessary. In addition, data access may be subject to authorisation by the data providers and, depending on the data set, use may only be permitted under certain conditions. 

Towards the genesis of topic-related descriptions

R|EX research often involves sensitive research data, access to which should be rule-based and subject to appropriate safeguards and subsequent use from a critical and reflective perspective. The latter also applies to the description standards of such data, which are intended to break down and combat discriminatory narratives. Against this background, we aim to support more detailed and sensitive research on social phenomena and discriminatory and racialised social groups. The challenge here is to use descriptive standards that do justice to the diversity and individuality of the research field and avoid the stigmatisation of vulnerable groups or sensitive research content. 

By adopting an epistemological and, above all, research-oriented perspective, the data landscape was analysed in an interdisciplinary way, also by involving researchers of the research community. This resulted in descriptive categories that cover 

  1. the content-related dimension of different social thought patterns, ideologies or attitudes, 
  2. the group-related dimension from the perspective of the actors and/or those affected, 
  3. and finally the empirical dimension of the respective data types. 

(1) Concept ontology

This category is used to schematise dimensions of discrimination and racialised and migrantised characteristics that are relevant to the research area and can be the subject of a study. These can be both self-attributed characteristics and anticipated external attributions. The characteristics do not necessarily correspond to the units analysed in the data set, but may also be the subject of concepts or theories analysed in the surveys. 

(2) Characteristics of differentiation

This topic-specific concept ontology is used to schematise social phenomena or theoretical constructs relevant to the research area that may be the subject of a study. They have been developed on the basis of an extensive interdisciplinary review of existing literature and empirical studies in the context of R|EX research to ensure a high level of coverage as well as the appropriateness and informative value of the concept ontology. 

(3) Data types

This category includes the types of data relevant to the area of research that may have been generated by a study, taking into account a variety of different survey types. The data types may be subject-, event-, spatial- or time-related and may refer to the individual or aggregate level.