Adaptive user input interfaces based on domain-specific ontologies for research dataset publishing
In the context of OpenScience, researchers are encouraged to publish their research datasets in common data repositories so that others can find and reuse it. To increase the findability of such a research dataset, metadata has to be provided to describe all characteristics of the contained data. However, data repositories are primarily focusing on administrative, citation, technical and some basic descriptive metadata so far. Information on particular dataset characteristics are either provided not at all, in an unstructured way as floating text or only in domain-specific data repositories. This makes it difficult to simply the discoverability of relevant data sets for researchers from different knowledge disciplines.
A semantic technology-based approach is a means to improve the interdisciplinary publishing and discovery process. A variety of domain-specific ontologies already exists, which define relevant properties in a structured way. Traditional approaches of using static input forms do not take these domain-specific metadata models into account. It could be a benefit if an adaptive user input interface is instead presented to the user which takes the research context of the generated research data into consideration and allows the structured input of knowledge-domain specific descriptive metadata. The objective of the Master's thesis project is to define a concept that addresses this domain-specific demands by dynamically generating such a user input interface based on existing ontologies and their relevance for particular research datasets.
To achieve this, a requirement analysis has be performed first. Then, a state-of-the-art analysis concerning existing systems for the classification of research domains and approaches for the generation of user input interfaces must be conducted. A concept has to be designed and described, in which a researcher can provide basic meta data as well as domain-specific meta data that is particularly relevant for the research dataset that shall be published. An implementation and evaluation has to show the feasibility and acceptance.