Issues to be addressed
- Formal representations of scientific data; ontologies for scientific information
- What ontologies do we need for representing structural elements in a document?
- How can we capture the semantics of rhetorical structures in scholarly communication, and of hypotheses and scientific evidence?
- Integration of quantitative and qualitative scientific information
- How could RDF(a) and ontologies be used to represent the knowledge encoded in scientific documents and in general-interest media publications?
- Connecting scientific publications with underlying research data sets
- Ontology-based visualization of scientific data
- Provenance, quality, privacy and trust of scientific information
- Linked Data for dissemination and archiving of research results, for collaboration and research networks, and for research assessment
- How could we realize a paper with an API? How could we have a paper as a database, as a knowledge base?
- How is the paper an interface, gateway, to the web of data? How could such and interface be delivered in a contextual manner?
Applications and Use Cases:
- Case studies on linked science, i.e., astronomy, biology, environmental and socio-economic impacts of global warming, statistics, environmental monitoring, cultural heritage, etc.
- Barriers to the acceptance of linked science solutions and strategies to address these
- Legal, ethical and economic aspects of Linked Data in science