Scientific dataspaces aim at providing associated mechanisms for managing semantically rich relationships among scientific data sources (primary data) and its corresponding findings (derived data). The latter result from a set of activities defining concrete preprocessing and analysis methods (background data) that were applied to a source dataset. To keep track of scientific experiments that are being conducted by members of a scientific community these experiments should be linked with user information i.e. institutional affiliation, email address, working field, etc. of the scientist who conducted the experiment. This paper deals with the development of a scientific dataspace for the breath gas analysis community. Breath gas analysis is an emerging new scientific field with a growing international scientific community addressing many different breath gas studies in terms of investigating and screening for hundreds of compounds in exhaled breath gas. The purpose of breath gas analysis scientific dataspaces is to enable collaborating scientists and institutions several important activities, which include: (a) access to distributed breath gas data and analytical resources collected and developed at different research institutions around the world and (b) to easily contribute to and leverage the resources of an international- and national-scale, multi-institutional environment. This paper describes the conception and prototypical implementation of the scientific dataspace paradigm for breath gas analysis. The scientific dataspace is evaluated on top of applications from breath gas analysis. We discuss the scientific dataspace paradigm in the context of applications from breath gas analysis, however the concepts introduced can also be deployed in other research domains.

Top