This simple use cases are taken from a brief factsheet about the geo data portal data integration strategy.
Use Case: Downscaled Climate Projection Portal
A consortium of DOI Climate Science Center (CSC) researchers and other scientists working on an interdisciplinary team need to answer global change adaptive management questions for DOI Landscape Conservation Cooperatives (LCCs). LCC managers need the CSC scientists to run various models to predict the condition of ecosystem function and services according to numerous downscaled climate projections. A group within the CSC consortium has produced downscaled output for a suite of global climate models and made them available as national scale gridded time series. Several other CSC groups have models to predict ecosystem function given the downscaled climate projections and model drivers. The CSC environmental modeling researchers can use a GDP client application in order to transform the three dimensional gridded climate projections into spatial averages or other model required formats. The data volume and processing time to complete this data processing could represent the majority of the time and energy devoted to any environmental modeling project. Using a standards-based generalized tool to automatically derive model ready data, environmental modeling groups within the CSC consortium can realize greatly reduced data manipulation costs and rely on common, easily documented processing methods.
Use Case: National Hydrologic Modeling Portal
A web-based National Hydrologic Model Portal (NHMP) addresses data and model distribution needs of the hydrologic modeling community. The portal streamlines and formalizes the process of retrieving large subsets of geoscience data for hydrologic model parameterization and forcing. A “best available data” catalog contains metadata describing projects, models, data, processes, and how they relate. Through a service oriented technical architecture, the portal facilitates access to sub-sets of data in numerous formats on disparate web servers. Portal processing capabilities include the ability to allocate gridded and point time-series datasets (i.e. high resolution climate variables) or categorical datasets (i.e. land cover) to modeling units regardless of the scale of the source data. Techniques will reduce data processing errors, misinterpretation and (or) misuse, and duplication of effort related to model development. The NHMP workflow encompasses four general categories: a user’s spatiotemporal interests or modeling domain analysis zones (sub-watersheds), a dataset or model output to sample, applicable process options, and data output format specification. The NHMP service will facilitate continental scale studies, such as climate change, ecological impacts, hazard evaluation, and water supply, while also addressing the needs of regional or local scale modeling studies by providing data of consistent coverage and quality.
Use Case: CSO Impact Modeling
A scientist working in collaboration with a regional sewerage district and the EPA to develop a model of combined sewer overflow (CSO) causes, diffusion, transport, and decay. The EPA is interested in informing CSO mitigation decisions taking climate change into account. In order to parameterize and calibrate a model, the scientist needs to access geographic, hydrologic, water quality, meteorological, marine, and other environmental data types. The various data formats and access methods represented require substantial data processing effort which the scientist could undertake but this time could be much better spent applying valuable expertise in coupled hydrodynamic-hydrologic water quality modeling. A data management toolbox is needed to facilitate searching for and obtaining required model parameters, forcings, and calibration targets. With a data interoperability toolbox to facilitate data access across scientific disciplines, the scientist is able to devote her time and expertise to developing a coupled terrestrial-marine water quality model informed by various federal, state, and academic data sources. Improvement in availability and efficiency of data access allows scientists to answer complex multi-disciplinary problems quickly without the sometimes arduous, menial data manipulation often required for such efforts, increasing their capacity to do science that will be critical to informing decision making in our changing world.
Use Case: Beach Health Modeling
A state DNR, USGS water science center, NOAA Environmental Research Lab, and a group of local agencies and citizens want to collaborate to predict near shore water quality to warn swimmers of beach health hazards. Concerned citizens will enter local observations into a database. The USGS scientists will develop a water quality model for the watershed that contributes near the beach. NOAA scientists will develop a hydrodynamic contaminant transport model to track pollutants coming from a local waste water treatment plant, industrial park, and the river being modeled by the USGS. The DNR will use the model predictions as well as numerous environmental monitoring data feeds to calibrate and run a statistical model to predict E-coli concentration at a beach as well as up and down the coastline. The USGS and NOAA modelers can utilize GDP tools to access model parameterization, calibration datasets, and real time model drivers. The DNR can use GDP tools to pull in the numerous environmental data feeds needed as well as access particular summaries of the modeled data products from the USGS and NOAA. A beach health portal using GDP tools to generate model result summaries and visualizations will facilitate citizens' access to the water quality model results from the DNR, NOAA and USGS. An accompanying metadata catalog maintained by the scientists and modelers will transparently present all data sources used and produced by the scientists giving citizens the information they need to make informed decisions about the quality of the beach health predictions.