Quick Start Guide: Tags for data and topic search 🇬🇧

Général
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Tags and Their Usage

To enhance content discoverability and improve forum organization, participants are encouraged to use the following tags effectively:

Dataset Tags

  • [dataset] (general tag for all dataset discussions)
    • [dataset-second], [dataset-minute], [dataset-hour], [dataset-day]
      • Use these tags to specify the temporal granularity of the dataset being discussed.
    • [individual], [aggregated], [national], [sub-national]
      • Use these tags to specify the scale or type of dataset.
    • [electricity], [heat]
      • Indicate the energy domain of the dataset.

Example Usage:

  • [dataset] [dataset-hour] [aggregated] [electricity]
    • This tag combination could describe a discussion on hourly aggregated electricity datasets.

Study-Specific & Project-Specific Tags

  • [etudelec]: For topics related to the EtudELEC study.
  • [flex-tase]: For topics related to the FlexTASE project

Marketplace Tags

  • [data request]: For requests seeking specific datasets.
  • [data supply]: For participants offering datasets for others to use.

Support Tags

  • [how-to]: Use this tag for guides, explanations, and support-related topics.
  • [q&a]: For question-and-answer threads focused on specific topics, studies, or datasets.

Example Usage:

  • [q&a] [data request]: Indicates a Q&A topic focused on a data request.
  • [how-to] [dataset-hour]: Indicates a guide or discussion about using hourly datasets.

Best Practices for Tagging

  1. Be Specific: Use multiple tags to clarify the content of your post. For example, combine a dataset tag with a study-specific or time-related tag.
  2. Avoid Over-Tagging: Stick to the tags most relevant to your discussion.
  3. Review Existing Topics: Before creating a new post, search for existing topics with similar tags to avoid duplication.
  4. Use [q&a] for Questions: Use the Q&A tag to highlight posts seeking answers or clarifications.

By following this structure and tagging strategy, the forum will remain organized, searchable, and user-friendly for all participants.