Masterarbeit
Adaptive user input interfaces based on domain-specific ontologies for research
dataset publishing
Completion
2020/05
Research Area
Intelligent Information Management
Students
Advisers
Description
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.
