Speaker
Description
The aim of a cooperation between the DDI Alliance and QualidataNet - a network for qualitative data that is being created as part of the NFDI - is to describe qualitative data in a standardized way so that researchers can find it and use it for their own research, regardless of discipline and thematic location.
Since last year, QualidataNet has been involved in the metadata developments of the DDI Alliance, which is working on an international metadata standard for Cross Domain Integration to provide integration-ready data, and which should play an important role in the context of the CDIF Framework of the WorldFAIR Project.
Together, we are focusing on the development of a model for the description of qualitative data across disciplines. We understand qualitative data in a broad sense referring to the type or nature of the data objects, i.e., data that are not presented in a quantitative, coded or structured manner. By qualitative data we do not refer to the methods of their collection, generation or analysis, nor to their sensitivity or the quality of their content, but to the (semi)unstructured nature of the data objects before they are processed or analyzed (i.e. raw), in other words, to the resources that are inputs for analysis - any observation, measurement or fact represented digitally as free text, images, video, sounds, etc. that form the basis for extracting information.
As responsible for qualitative data and in this cross-domain context, QualidataNet is pursuing the goal of enhancing the interoperability of qualitative data beyond our domains. In order to achieve this, we need to find out how non-numerical or qualitative data should be provided in order to make it ready for analysis. To ensure the integration of a broad variety of examples of qualitative data objects, we are searching for further use cases which will give us an overview of the different types of qualitative data and their usage in different research domains. We are interested in how researchers or data curators work with qualitative data objects, how they prepare them for analysis, and how they combine different data types to represent these procedures in the DDI-CDI metadata model. Use cases are examples of studies or datasets in which qualitative data have been collected and have the potential to be reused in other studies and/or disciplines or combined with other (e.g., quantitative) data.
With our poster we want to get in touch with you, talk about the unmet needs in your areas regarding the description of qualitative data such as social media and sensor/tracking data, audiovisual data, visual maps and deep-sea images, etc. and perhaps lay the groundwork for future collaboration to make non-numeric and qualitative data more interoperable.
In addition, please add 3 to 5 keywords.
qualitative data; interoperability; cross-domain integration; metadata model;
| Please assign yourself (presenting author) to one of the following groups. | Data professionals and stewards |
|---|---|
| For whom will your contribution be of most interest? | Data professionals and stewards |
