Data Management Efforts

1. Bureau of Land Management (BLM) Christine Hawkinson, Bureau Data Administrator Data Management Efforts

2. BLM Data roles • Bureau Data Administrator • Responsible for data management policy and guidance • Data Management (Division of Resource Services) Operations • Development of national data standards • Development and implementation of national geospatial datasets • Division of Information Resource Management -Operations • Database (application) development • Implementation of applications • Geospatial Program • Geospatial Infrastructure and Issues • Data Stewards – national, state and local • State and Field Offices • Data Collection

3. Data life cycle

4. Data Development – High Level

5. Data standard & standardized dataset • Data Standard • identify logical / business data requirements • document what information is needed to meet those business requirements to provide for high-quality data. • Defined before data is collected. • Not specific to geospatial data • Standardized Dataset • Anational schema with a shared set of attributes and domain values, capable of being seamlessly compiled to a National dataset. The implementation of a data standard also results in a standardized dataset. • Database / Geodatabase • A defined, automated, shared and centrally managed collection of data. A data base is a collection of interrelated data stored in a structured manner.

6. Data Advisory Committee (DAC) DAWG: Data Advisory Working Group

7. Propose data development project • Deliverables: • Data Development Proposal (template) • Development Schedule – through Defined Dataset • Purpose: • Defines initial scope • Communicates intent of work • Locate Subject Matter Expertsfor Development

8. Enterprise data framework

9. Data Standard Development • Deliverables (templates): • Data Standard Report • Domain Document • Quality Plan • Metadata Description • Implementation Guidelines (opt) • Purpose: • Describes business data, rules and domains for bureau • Provides common schema • Provides information on how quality will be assessed (insures will meet minimum quality requirements)

10. standardized dataset development • Deliverables (templates): • Standardized Dataset Report • Domain Document • Quality Plan and Checklist • Metadata Description • Purpose: • Provides common schema and domain values for national compilation of diverse local datasets • Provides plan for insuring quality and completeness of dataset

11. Implemention plan • Dataset Deliverables: • Implementation Plan • Quality Checklist • Metadata Description (final) • Data Certification • National Certified Dataset • Database Deliverables: • Database design • Data Management Plan (including quality) • Data Migration Plan (optional)

12. Change management • Deliverables: • Updates to existing standard (optional) • Updates to schema • Retired standard

13. National Dataset implementation • States provide state-level datasets • Quality checked for minimum required criteria • Quality reports • Specific domains, attributes, topology • Trusted Data Aggregation: States responsible for error correction • Metadata reviewed for completeness • Meets required minimum • Replicated into national dataset • No data updates at aggregated national level • Timing of updates from states depends on data steward requirements • Dataset is certified by data steward • Can be published once certified (internal/external)

14. Completed Datasets Processes for aggregation vary Examples: • Basic National datasets • Administrative Boundaries • Land Use Planning Areas • Allotments and Pastures • Summarized National datasets • Land Health Reporting • Visual Resource Inventory

15. Example: Land treatments • Several redundant systems • Crosses programs • Same types of treatments/data which are completed for various reasons • Looking at developing a treatment module that can be called by different systems • Same data standard; same data elements • Store once, use and update many times

16. DATA Management functions DAMA DMBOK,2009

17. Questions?