4.2 Essential data management concepts

Overview     Introduction     Essential data management concepts   Resources  Results and next steps

Key Protocol Elements for Data Handling, Analysis and Reporting 

These key elements are essential when designing an approach for managing monitoring program data and ultimately planning for the linked analysis/interpretation and reporting steps (directly adapted from Salmonid Field Protocols Handbook).

• Metadata procedure— Metadata describe the key features about the monitoring program's data that are necessary for ensuring an understanding about their characteristics and appropriate use. Metadata descriptions typically include attributes like database fields and sizes; sample collection information; site description; quality assurance; source;and time frame.  See PNAMP Metadata Guidance for detailed information for this step.  Procedures for defining these key data characteristics should be part of any system design and implementation.
• Database design— This design creates the data system architecture that will facilitate meeting program goals and objectives in an effective and accountable manner.  The structure should illustrate relationships between different data sets, components and tables but also should anticipate and incorporate the ability to apply data at various scales, including the potential to link program data sets to larger regional efforts.
• Data entry— Explicit data entry procedures, including verification and editing of data, are an essential feature of the overall data management system.

Click here for further detail on key steps for developing a comprehensive data structure.

In considering these data system design components it is important to ensure that the approach will directly support analysis, interpretation and reporting plans outlined in Interpret and Report steps of the monitoring wheel.

• Data summaries and analysis —The data system should anticipate the procedures for how monitoring data will be summarized and statistically analyzed.  The analysis approach should be linked to a robust design for answering specific objectives and questions of the monitoring program.

• Report format— A comprehensive program design will anticipate how the data system will facilitate reporting of results, such as a planned report format with examples of summary tables and figures.

Finally make provisions to help ensure that collected data will be accessible long after the project's completion:

• Archival procedures— Planning for the archive of program data is essential for its long-term institutional existence, access and use. 

Establishing Project Data Structure

1. Outline core questions that will be asked ask of a data structure (refer to Step 1, Goals).
2. Define units and terms of data and data types being collected.
3. Create a consistent process for developing an observation based data project (specifically, preparing a needs assessment and writing a data collection and management plan).
4. Determine office and field procedures needed for entering data, and also for Quality Assurance/Quality Control (QA/QC) protocols, analysis, reporting, and data maintenance.
5. Design data forms.
6. Create data fields (elements) and identify those that are required or recommended.
7. Categorize fields or elements as either data or mapping.

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