RESUMEN
Linked Science is the practice of inter-connecting scientific assets by publishing, sharing and linking scientific data and processes in end-to-end loosely coupled workflows that allow the sharing and re-use of scientific data. Much of this data does not live in the cloud or on the Web, but rather in multi-institutional data centers that provide tools and add value through quality assurance, validation, curation, dissemination, and analysis of the data. In this paper, we make the case for the use of scientific scenarios in Linked Science. We propose a scenario in river-channel transport that requires biogeochemical experimental data and global climate-simulation model data from many sources. We focus on the use of ontologies-formal machine-readable descriptions of the domain-to facilitate search and discovery of this data. Mercury, developed at Oak Ridge National Laboratory, is a tool for distributed metadata harvesting, search and retrieval. Mercury currently provides uniform access to more than 100,000 metadata records; 30,000 scientists use it each month. We augmented search in Mercury with ontologies, such as the ontologies in the Semantic Web for Earth and Environmental Terminology (SWEET) collection by prototyping a component that provides access to the ontology terms from Mercury. We evaluate the coverage of SWEET for the ORNL Distributed Active Archive Center (ORNL DAAC).
RESUMEN
The Genomic Standards Consortium (GSC) invited a representative of the Long-Term Ecological Research (LTER) to its fifth workshop to present the Ecological Metadata Language (EML) metadata standard and its relationship to the Minimum Information about a Genome/Metagenome Sequence (MIGS/MIMS) and its implementation, the Genomic Contextual Data Markup Language (GCDML). The LTER is one of the top National Science Foundation (NSF) programs in biology since 1980, representing diverse ecosystems and creating long-term, interdisciplinary research, synthesis of information, and theory. The adoption of EML as the LTER network standard has been key to build network synthesis architectures based on high-quality standardized metadata. EML is the NSF-recognized metadata standard for LTER, and EML is a criteria used to review the LTER program progress. At the workshop, a potential crosswalk between the GCDML and EML was explored. Also, collaboration between the LTER and GSC developers was proposed to join efforts toward a common metadata cataloging designer's tool. The community adoption success of a metadata standard depends, among other factors, on the tools and trainings developed to use the standard. LTER's experience in embracing EML may help GSC to achieve similar success. A possible collaboration between LTER and GSC to provide training opportunities for GCDML and the associated tools is being explored. Finally, LTER is investigating EML enhancements to better accommodate genomics data, possibly integrating the GCDML schema into EML. All these action items have been accepted by the LTER contingent, and further collaboration between the GSC and LTER is expected.