Data Management Scope and Strategies K.L. Sender and J.L. Pappas Information and Technical Services National Marine Fisheries Service Southwest Fisheries Science Center Honolulu Laboratory

Data Is the Foundation on Which We Build Success. Successful management of data is critical to our mission to make informed decisions.

What Is the Goal of Data Management? The most important goal of Data Management is to ensure access and dissemination of quality data to appropriate end-users in a timely manner.

Quality Data Is the Result of Good Data Management

Why Do We Want to Manage Data? To fulfill the agency’s mission to conserve and manage the nation’s coastal and marine resources to ensure sustainable economic opportunities.

What Is Data Management? It’s Not Just Archiving!

Data Management Includes Data Resource Development.

Data Management Includes Data Collection.

Data Management Includes Data Maintenance.

Data Management Includes Data Dissemination.

Data Management is…

What Are the Costs of Poor Data Management? Misinterpretation of the data Lost data Inaccessible data Indefensible data Wasted time and money Missed deadlines Lost user confidence

What Are the Benefits of Good Data Management? Optimum data quality Improved user confidence Efficient and timely access to data Improved knowledge and understanding of the agency’s data holdings

How Is Good Data Management Achieved? Through the development and implementation of well-conceived data management policy and data administration guidelines.

Data Management Policy Policy for the management and protection of agency data. Set of broad, high-level principles forming a framework in which data management can operate efficiently and effectively.

Data Management Policy Serves To… Ensure availability of stable, reliable and accessible collections of data in electronic form to all appropriate parties; Ensure compliance with all agency-wide mandates and directives. Improve direct access to data by the public and across the agency.

Data Management Policy Allows… Good fisheries science. Good fisheries management Data users to be confident in their interpretations of quality data; The agency to properly defend its data in a court of law.

Data Management Policy What might work…

A Draft Data Management Policy 1.Programs that generate data will adhere to data management policies and guidelines. 2.Data and metadata will be managed and stored in a centralized data resource. 3.The data resource will be safeguarded and protected. and…

A Draft Data Management Policy 4.Data will be shared based on agency policies. 5.Agency data will be cataloged and documented. 6.Information quality will be actively managed throughout the life cycle of the data.

Who Sets Data Management Policy and Guidelines? An information technology/information management steering committee, composed of one or more representatives from the key data management role groups:  Administration  Data generators  Data users  Information technology  Management

Data Management Steering Committee Ensures that data management policies are in line with those of NMFS, NOAA and DOC. Directs development, implementation and maintenance of detailed data policies, standards procedures and guidelines across the agency. Reports progress to the director on the performance achieved against the targets for improvement of data quality and the value gained from effective data management.

Data Management Roles and Responsibilities

Data Ownership The agency is the owner of the data. The organizational unit or group that commissions the collection of a data set assigns a data steward to that data set.

Data Administration Guidelines Required for all data management task areas Data resource development Data collection Data maintenance Data dissemination

References Brohan, M., 2001, The Need for a Formal Data Management Policy, DM Review, v. May. Data Administration Forum, 1999, Data Management Roles and Responsibilities Guidelines, Ver. 1.3, Advisory Council for Information Management, British Columbia. Fisheries Information Technology for the 21 st Century (FITS21). Flanagan, T., et al, 1998, A Practical Guide to Achieving Enterprise Data Quality. Imhoff, C., 1998, Ensuring Data Quality Through Data Stewardship, DM Review, v. Apr.

References (cont.) Imhoff, C., 1997, Data Stewardship: Finally a Process for Achieving Data Integrity, The Data Administration Newsletter. Information Resources Management Staff, Information Systems Office, Office of Finance and Administration, 2000, National Oceanic and Atmospheric Administration Strategic Information Technology Plan, FY 2001 – FY Intra-governmental Group on Geographic Information, 2000, The Principles of Good Data Management. Sargent, J., Bistodeau, R. and Seem, D., 2000, NOAA Fisheries Information Technology (FIT) Architecture White Paper, Systems Development Methodologies. U.S. Fish and Wildlife Service, 2000, Data Standards. University of Michigan, 1994, Institutional Data Resource Management Policy.