A Semantic Web-based Methodology For Describing Scientific Research Efforts

Scientists produce research resources that are useful to future research and innovative efforts. In a typical scientific scenario, the results created by a collaborative team often include numerous artifacts, observations and relationships relevant to research findings, such as programs that generate data, parameters that impact outputs, workflows that describe processes, and publications, posters and presentations that explain results and findings. Scientists have options in what results to share and how to share them, however, there is no systematic approach to documenting scientific research and sharing it on the Web. The goal of this research is to define a systematic approach for describing the resources associated with a scientific research effort such that results and related resources become more accessible and understandable to machines over the Semantic Web. This research defines a methodology, called Collect-Annotate-Refine-Publish (CARP) Methodology, that uniformly structures and links heterogeneous information that is distributed over the Web as scientific collections. Scientific collections are structured descriptions about scientific research that make scientific results accessible based on context and queryable by machines. Initial findings confirm that documenting scientific research on the Web is not a common practice and that tools that implement CARP can guide the process and facilitate documenting scientific research on the Linked Data dataspace. As a result, machines can help understand resources and their relationships in scientific collections, therefore, CARP facilitates reuse of scientific results