The universities of Michigan, Indiana, and Illinois propose a DataNet partnership called Sustainable Environment through Actionable Data (SEAD). SEAD will enable new modalities of sustainability science - the study of dynamic interactions between nature and society. Advancing the science of sustainability requires integration of social science, natural science, and environmental data at multiple spatial and temporal scales that is rich in local and location-specific observations; referenced for regional, national, and global comparability and scale; and integrated to enable end users to detect interactions among multiple phenomena. SEAD will respond to the expressed needs of sustainability science researchers for long-term management of heterogeneous data by developing new capabilities for data integration, dissemination, and long-term preservation. SEAD will provide researchers with tools for active curation and use social networking to engage data producers and users in community curation, gradually shifting curatorial and collection development responsibilities from professional curators to the producer and user communities. Our focus is on the "long tail" of social and environmental data: derived data products, data collections from individual PI's and small group investigations, and data sets of local, regional or topical significance that are critical to sustainability science but are of limited value until they can be referenced geo-spatially and temporally, combined with related data and observations, and modeled consistently. SEAD will make data accessible to diverse users, including domain scientists, local, national and international policy makers, manufacturers of sustainable technologies, citizen scientists, and informed consumers. SEAD will take advantage of existing robust digital library and institutional repository (IR) infrastructures at the three universities for access, storage, and preservation to ensure wide accessibility of data, linkages between data and scientific publications, and persistence.
SEAD will serve researchers efficiently and in a financially sustainable way via active curation, make innovative use of social networking, integrate data with existing digital library infrastructures, and provide synthesis services that significantly increase the research and societal value of data. Our work will establish a new active curation paradigm that can be readily integrated into the scientific workflow and that leverages social networking technologies to engage the science community in data curation. Our research program will produce novel solutions to the synthesis of heterogeneous data across different levels of spatio-temporal granularity and scope; management of logical contexts and data models; appropriate sharing of data with privacy and proprietary restrictions; and preservation through emulation and migration-based-technologies and policies for distributed stewardship. Our cyberinfrastructure development work will support a network of repositories that functions on several levels: locally through integration of SEAD data into campus digital library/repository infrastructures, inter-institutionally through a model for distributed data curation and storage, and nationally and internationally by extending our approach to other IRs, other DataNet Partners, sensor and observational networks, and topical data archives. Our financial sustainability plan will identify appropriate incentive mechanisms and business models based on a tight coupling of preservation and access services with research library managed IR infrastructure and ongoing involvement of scientists and users.
SEAD will build national and global capabilities for science-informed sustainability policy and planning in land use, natural resource management, agriculture, energy, economic development, "green" manufacturing, and related areas where critical decisions will be made in the next decade. The project will engage the community that preserves and shares scientific data, thus enhancing the public investment in scientific research and making taxpayer funded data widely available and easier to use which will provide high-value cost-effective curation and preservation capabilities through partnerships with other "small science" domains.
