1 research outputs found
Creating a Discipline-specific Commons for Infectious Disease Epidemiology
Objective: To create a commons for infectious disease (ID) epidemiology in
which epidemiologists, public health officers, data producers, and software
developers can not only share data and software, but receive assistance in
improving their interoperability. Materials and Methods: We represented 586
datasets, 54 software, and 24 data formats in OWL 2 and then used logical
queries to infer potentially interoperable combinations of software and
datasets, as well as statistics about the FAIRness of the collection. We
represented the objects in DATS 2.2 and a software metadata schema of our own
design. We used these representations as the basis for the Content, Search,
FAIR-o-meter, and Workflow pages that constitute the MIDAS Digital Commons.
Results: Interoperability was limited by lack of standardization of input and
output formats of software. When formats existed, they were human-readable
specifications (22/24; 92%); only 3 formats (13%) had machine-readable
specifications. Nevertheless, logical search of a triple store based on named
data formats was able to identify scores of potentially interoperable
combinations of software and datasets. Discussion: We improved the findability
and availability of a sample of software and datasets and developed metrics for
assessing interoperability. The barriers to interoperability included poor
documentation of software input/output formats and little attention to
standardization of most types of data in this field. Conclusion: Centralizing
and formalizing the representation of digital objects within a commons promotes
FAIRness, enables its measurement over time and the identification of
potentially interoperable combinations of data and software.Comment: 12 pages, 6 figure