Vorschau

PDF, Englisch - Hauptdokument Download (359kB) | Lizenz: BIRD: Usind conversantional user interfaces to provide relevant metadata for interdisciplinary research dataset publishing von Langer, André ; Schmolke, Lukas ; Gaedke, Martin steht unter einer Creative Commons Namensnennung 4.0

Abstract

When publishing scientific artifacts, such as recorded files from an experiment, generated files from a software, or developed application components, researchers are encouraged to provide additional structured meta information about certain characteristics of these scientific datasets, as these are normally not self-descriptive. For that purpose, several proposed metadata standards and schemas already exist. Such a meta data description nowadays commonly comprises a title, some information about the author and institution, some other administrative or citational metadata, some simple and maybe ambiguous keywords and an unstructured free-text description of the main content. However, especially for early-career researchers, it is an obstacle to start with research data publishing because they are not aware of relevant existing standards,are bored to fill out extensive, static, text input-orientedsubmission forms in well-established research data repository applications, or see it as a time-consuming activity without support or interaction. Chatbot-like user interfaces are a promising approach that were already successfullyapplied in other knowledge domains to request structured information from a user and guide the userthrough a set of relevant questions in an adaptive fashion. In the particular domain of scientific metadata management, the number of existing approaches is still limited. We investigate opportunities and challenges of such a conversational UI-based approach tobuild the prototype of a dialog system based on the Raza framework and the OpenAIRE guidelines for research dataset publishing which will generate a semantically enriched JSON-LD file result.This export file can then beused as a structured datasource in a consecutive application or tool chain, or simply be published as microdata together with the corresponding dataset on web platforms, in order to improve the controlled description and discoverability of the shared research data according to the FAIR principles.