GEOSS Testbed Report-Out: Data Prioritization and Processing 2/6/2013

Outline Overview Process Outcomes – Datasets – Prioritization – Workflow Applications Next Steps

Overview Testbed Charter GLOS becomes GEO- Participating Organization GLOS GeoNetwork Developed, Registered with GEOSS NOW: Need to grow the GLOS Catalog Great Lakes Testbed Project Plan What datasets should be registered?  Where there are resources to support?  Where there are no resources, but dataset exposure is valuable?  Other?

Process Subcommittee Charge: Develop a systematic process for identifying, prioritizing, and registering datasets relevant in the GEOSS Testbed metadata catalog. Contributors: EC (Wendy Leger), GLOS (Jen Read, Kelli Paige), LimnoTech (Kathy Koch, Tad Slawecki), USGS (Jessica Lucido, Jordan Read, Jessica Thompson)

Outcome: Datasets Built list of candidate datasets from convenient sources – GEOSS Testbed – CGLG/GLOS Foundational Hydrologic Datasets – GLOS Enterprise Architecture Report – Potential IJC Indicators

Outcome: Datasets Consider five: GEOSS + 1 – Beach health – Ice – Groundwater – Water levels – Nutrients

Outcome: Prioritization Strategy/Identification Supports : GL Compact, GL WQA IJC Indicators, Adaptive Management/Water Levels National Ocean Policy/ROP, GLRI GLOS EA (GEOSS ties & GLOS sustainability) Meets a requirement/mandate, serves multiple needs, etc. Is there an existing group of users to work with to identify/confirm? Costs Cost estimate – Metadata Execution time – Metadata Cost estimate – Data Execution Time - Data Effort Complexity/Completeness Execution Lead Data Accessibility Coordination

Outcome: Workflow “Metadata” Add Datasets to Metadata Repository Currently available and prioritized Determine Additional Datasets Process for submittal or data discovery of new datasets Ongoing prioritization Establish Procedures for Quality Review Process for updating existing resource information Process for archiving or removing outdated resources Process for Evaluation Are end-user requirements being met? What can be modified to improve either processes or metadata quality?

As datasets are identified/prioritized a form will be used to gather metadata Identified metadata complies with ISO / Dublin Core standards Ultimate goal will be to have this automated and tie in directly with the metadata repository When available, existing metadata will be harvested automatically, not requiring manual effort

Metadata Standards ISO / Dublin Core / GeoNetwork

Application: Groundwater OGC Groundwater Interoperability Experiment – GWIE: Delivery of features and data adequate for schematic interoperability with “best practices”. – GWIE2: Develop and test improved description of features. Ongoing, well-structured activity will harmonize schema – how data are described. – Harmonization of observations not yet an explicit part of effort

Application: Water Levels CGLG/GLOS ROP and GLRI DMAC Expansion projects look to improve access to Coordinated Lake Levels and ancillary data. – Use cases include hydrology dashboard, Cumulative Impact Assessment Centralized access (NOAA-GLERL), one feed (GLOS) – Compare to GWIE: multiple sources, aggregated feed, common formats

Application: Nutrients GLWQA, SOLEC, … call for understanding of nutrient dynamics – WLEB example: Concerns include eutrophication, algal blooms, hypoxia Discoverable, transparent and interoperable nutrient observations are desirable … but there are many sources to consider.

Sources Used ~ Lake Erie Nutrient Map

Next Steps Nutrients – Continue to work through (selected) sources to prioritize Water Level data Formalization of efforts