U.S. Department of the Interior U.S. Geological Survey Manage and Provide Information: Examples from fish health, contaminants, and water quality data themes Cassandra Ladino USGS Chesapeake Bay Workshop - 05/27/15

Ecosystem Science  Chesapeake Bay science plan for —provide integrated science for effective ecosystem conservation and restoration.  U. S. Geological Survey Chesapeake Science Plan, —Informing Ecosystem Management of America’s Largest Estuary  USGS Science Strategy (2007) —The last decade has witnessed the emergence of a new model for managing Federal lands—ecosystem-based management.  USGS Science Strategy (2007) —The ecosystems strategy is listed first because it has a dual nature. It is itself an essential direction for the USGS to pursue to meet a pressing national and global need, but ecosystem-based approaches are also an underpinning of the other five directions, which all require ecosystem perspectives and tools for their execution.  USGS Science Strategy (2007) —The nature of scientific collaboration also is changing. As the complexity of scientific questions grows, the need for integrated expertise and data from multiple disciplines grows as well.

A Community for Ecosystem Science

Building a Data Infrastructure for Chesapeake Bay Ecosystem Science

A Swiss Army Knife for Applications

BISON Example

BISON Example – The Need  BISON - A national unified resource for discovery, linkage, and reuse of species occurrence data.  "With BISON, the USGS takes a big step toward making biodiversity data held within Federal agencies easier to find and use", added Mary Klein, President & CEO of NatureServe. "I am enthusiastic about future opportunities to work with USGS to increase collaboration among Federal, state and private data holders."

BISON Example – On The Inside  Final Package – original dataset + BISON (enhanced) dataset + metadata record (linked and archived) + ReadMe file (record of BISON data modifications)  Standardized Data – Darwin Core format, Scientific Name mapping to ITIS, FIPS Code location references  Data Updates – ongoing for living datasets  Web and Web Services access – inc. mapping and visualization, and integration with other data layers  Multi-format data download –.csv,. kml,.zip  Machine Access – Via Application Programming Interface (API)

NWIS Example

NWIS Example – On The Inside

Chesapeake Bay Projects  Fish Health  Contaminants  Water Quality Trends

Chesapeake – Fish Health  Similar to the BISON example  Science Goal: Efficiently analyze fish health and water contaminant information collected over approx. the last decade to begin to answer questions about the correlation of the fish lifecycle to contaminant types and level in the water that cause lesions and intersex.

Chesapeake – Fish Health Tech Solutions  Design an integrated database to store annual fish health and contaminants information.  Standardize a data format.  Build Services on top of database to allow data extraction, analysis, and visualization

Chesapeake - Contaminants  Science Goals: Summarize water and sediment samples tested for pesticides, hormones, wastewater, and pharmaceuticals from NWIS so that it can be analyzed along side fish health information to answer lifecycle questions. Rescue historical water and sediment sample data not entered into NWQL/ NWIS. Format passive sampler data to be integrated with fish health, water, and sediment sample data.

Chesapeake – Contaminants Tech Solutions  Design a database  Standardizing a data format  Using database software to format rescued data. Data Set #1 Data Set #2 Data Set #3 Master - Database with Fish Health Information

Chesapeake – Water Quality Trends  Science Goal: Improve access to large amounts of data and efficiency of collaboration between team members.

Chesapeake – Water Quality Trends Tech Solutions

Chesapeake – Land Cover *NEW*  Science Goal: Define a standard process for many intern students to derive many land cover metrics from imagery.  Tech Solution: Develop a data management plan, define a standard format for output data sets, design a database structure for storing the information.

Break Out Session Challenge  For each of the priority datasets that the group identifies: 1. How can team members most efficiently work with the data using new technologies? 2. How do our partners want to access the data? 3. What applications can we build to showcase the science the data supports?

Thanks!  Cassandra Ladino,