Suchergebnisse

There exists a huge variety of Open Data portals, some of them providing just a handful, and others tens of thousands of datasets. The datasets they provide are expected to be supplied with metadata describing them. However, this metadata is typically available in one or two languages only, and, if translations exist, they are usually added manually. To build an inclusive data infrastructure, metadata should be available in as many languages as possible. The paper presents an approach for automatic translation of metadata within Open Data portals, based on Semantic Web technologies and using the metadata standard DCAT-AP. Based on this approach, new functionalities are possible, such as enabling users to search for datasets in their native language. The approach was implemented for and tested within a practical application in a production environment.

In this paper, we present our ideas on how to best support researchers in every phase of the research process when dealing with their research data. We propose a Research Data Portal as the central data infrastructure. With the help of this portal, a researcher can easily manage and update his or her research data, share it with collaborators, and reach out to the public. We further propose a Citizen Science Portal, which includes some new and innovative concepts and methods. In this portal, Citizen Science and Auto Science concepts are applied, and support to bring together the best of both worlds is provided. Citizen Science promises to entail the individual (scientists and hobby scientists) to help with research. Auto Science is meant to help analyze research data, e.g., to help publish the data and to help improve its quality, by applying methods from artificial intelligence.