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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. ACQUIRE
  2. Common Data Types

Best Practices with Source Data

PreviousBest Practices with Collections of Similar Types of DataNextQuality Management Procedures

Last updated 5 years ago

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Source data refers to those data resources used by the project but not created by the project. Source data is commonly used as input in the creation of new data products. Examples include base layers used in GIS processing or sensor input used to generate analytical output. If the source data is discoverable and permanently accessible through another means (e.g. USGS Streamflow data), this data does not need to be maintained in a project archive folder. However, if the source data is not readily available in the form used by the project it would be appropriate to save that information in the archive folder by following the best practices for each data type as described in prior sections of this guide.

‌In either case, a metadata record for the source data, obtained from the original source or written in the mdEditor, must be in the source data folder of the archive. The relationship between source data and products are described in the of the product metadata record.

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