Ontologies are being widely used across many scientific fields, most notably in roles related to acquiring, preparing, integrating and managing data resources. Data acquisition and preparation activities are often difficult ...

Data curation for interdisciplinary collaborative science requires a new online web-based approach that integrates domain knowledge from multiple resources and enables in tela (in the web) interactive collaboration between ...

We present Whyis, the first framework for creating custom provenance-driven knowledge graphs. Whyis knowledge graphs are based on nanopublications, which simplifies and standardizes the production of structured, ...

In an ideal world, the evidence presented in a clinical guideline would cover all aspects of patient care and would apply to all types of patients; however, in practice, this rarely is the case. Existing medical decision ...

To investigate the cause and progression of a phenomenon, such as chronic disease, it is essential to collect a wide variety of data that together explains the complex interplay of different factors, e.g., genetic, lifestyle, ...

With the rapid advancements in cancer research, the information that is useful for characterizing disease, staging tumors, and creating treatment and survivorship plans has been changing at a pace that creates challenges ...

Many existing music ontologies have focused on expressing metadata related to performances or recordings, aiding with recommendations of songs or artists, and studying the psychological affects of music. These music ...

Knowledge Graphs have an important role in organizing and making information more broadly available to people and machines. While many knowledge graphs have been developed, the approaches used to build them can differ ...

This editorial introduces the special topic articles on reflections on successful research in artificial intelligence. Consisting of a combination of interviews and full-length articles, the special topic articles examine ...

One primary task of population health analysis is the identification of risk factors that, for some subpopulation, have a significant association with some health condition. Examples include finding lifestyle factors ...