SKOPE (Synthesizing Knowledge of Past Environments) is an online resource for paleoenvironmental data and models. It enables scholars to easily discover, explore, visualize, and synthesize knowledge of environments in the recent or remote past. Given a location and temporal interval, SKOPE offers access to diverse sources of long-term, high-resolution environmental data. As a dynamic resource; it will allow users to rerun models with different inputs and it will seamlessly accommodate new datasets and models. SKOPE builds on vast amounts of prior data collection and previous research, transforming those into readily usable environmental knowledge.
Through a 2016 collaborative award to Arizona State University (ASU), the University of Illinois at Urbana -Champaign (UIUC), and Washington State University (WSU), the National Science Foundation is funding the ongoing development of SKOPE (SKOPE NSF proposal page). This development builds on the team’s 18-month design and prototyping effort that was funded by NSF in 2014. The online prototype provides precipitation and temperature data for Arizona, Colorado, New Mexico, and Utah for the last 2000 years at annual temporal resolution and 800m spatial resolution.
An alpha version of the production SKOPE application is now available, with additional datasets and features to follow. Ongoing development of SKOPE is expanding the spatial coverage of precipitation and temperature data provided by the prototype and the beta application. The full implementation of SKOPE will includesa wider array of paleoenvironmental datasets (pollen-based low frequency temperature, vegetation community, crop niche, and maize productivity reconstructions) while retaining a strong emphasis on building cyberinfrastructure to provide easy access to measured and derived datasets, as well as computational procedures, documented with English-language metadata. Retrodicted datasets will include these metadata as well as a goodness-of-fit assessment of the model to a calibration dataset. Technical documentation of the computation procedures, and the datasets produced by procedures we have implemented, will be provided by YesWorkflow.
SKOPE addresses two critical challenges to contemporary science: increasing access to publicly funded research; and ensuring that scientific results are transparent and reproducible. SKOPE will provide robust support for reproducible scientific research requiring paleoenvironmental data. It will not just enable discovery and access to paleoenvironmental data; it will provide researchers with an unprecedented ability to explore the data’s provenance–a detailed, comprehensible record of the origin and computational derivation of the supplied data. Central to SKOPE’s comprehensive support for transparency, reproducibility and provenance management will be the further development of YesWorkflow, a system for revealing the fine-grained provenance of data produced by scripts, programs, and computational pipelines without adapting software to run within a scientific workflow management system and without the overhead of a runtime provenance recorder.
SKOPE is conceived as a tool that can serve diverse professional and academic communities. For example, planners could use its long-term environmental reconstructions to investigate vulnerabilities in existing infrastructure that are outside the experience provided by the historic record. It could be used by archaeologists examining the social consequences of long-term climate changes, or ecologists investigating long-term changes in biodiversity or ancient species distributions. More broadly, it empowers investigations that rely on long-term environmental data.