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Alaska Region Interim Data Management User Guide
  • Alaska Region Interim Data Management User Guide
  • Background
    • Why Data Managment?
    • The Big Picture: Integrating Data Management with Project Management
    • Definition of Project and Product (aka Data Resources)
  • Four Fundamental Activities of Data Management
    • Establish Roles and Responsibilities
    • Quality Management
    • Security and Preservation
    • Documentation
  • Alaska Data Management 101
    • Workflow
    • File Organization and Best Practices
      • Best Practices in Naming Conventions
      • Best Practices for Version Control
      • Changelog Best Practices
    • Alaska Regional Data Repository
    • Data Management Policy
  • Plan
    • Why Data Planning?
    • Data Management Plan Templates
      • Data Standards in brief
    • Project & Data Management Integration
    • Considerations for Projects with External Partners
  • ACQUIRE
    • Common Data Types
      • Open Formats
      • Best Practices in Tabular Data
      • Best Practices in Databases
      • Best Practices in Geospatial Data
      • Best Practices with Collections of Similar Types of Data
      • Best Practices with Source Data
    • Quality Management Procedures
      • Incorporating Data Standards
      • Using Unique Identifiers
  • MAINTAIN
    • Update Metadata
  • Access & Share
    • Open Data Requirements
      • Obtaining a Digital Object Identifier (DOI)
      • Obtaining a URL
      • Sharing without a URL
  • Long-term Storage Options
    • Using the Regional Data Repository
    • Public Accessible Repositories
  • Records Schedule & Disposition
  • Data Management Actions Quick Guide
  • Glossary
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  1. Plan

Project & Data Management Integration

Framework for integration of project management with data management

PreviousData Standards in briefNextConsiderations for Projects with External Partners

Last updated 3 years ago

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Project management is the application of knowledge, skills, tools, and techniques to oversee a project to completion in the desired time and to a specified quality. Data management is concerned with the handling of data to ensure long-lasting integrity and usability. Despite the fundamental difference, project management and data management lifecycles work in tandem. Data management is most effective when fully integrated into project workflows, project oversight, and staff supervision (i.e., project management).

Lifecycle comparison between project management and data management.