The description should provide context for the dataset. While the dataset description is similar to an abstract or project brief for an article or project, your description should not simply re-state research findings. Good dataset descriptions help future researchers identify the characteristics of your data and determine whether they can re-use your data for their own research.

Examples of how to start off your description: "This dataset was generated from a survey that studied…," or "This dataset includes sequencing data from…"

e.g. This dataset includes data from a mixed-methods research study involving librarians and information professionals in health sciences libraries. The dataset comprises of demographic characteristics of subjects, de-identified survey results, and focus group questions and transcripts. 

You can optionally include more metadata that describes your research study and dataset:

• Data Type(s): Select all that apply
  • Administrative/Operational – Institutional records such as billing, claims, HR, student data, workflows
  • Clinical – Patient data including EHR extracts, clinical trials, lab results, clinical registries
  • Derived/Analytical – Aggregated or processed datasets from raw sources
  • Demographic/Population – Census, population surveys, or demographic summaries
  • Device – Data from wearables, monitors, or research instruments
  • Image – Visual datasets such as MRI, microscopy, pathology, or blots
  • Environmental/Geospatial – GIS, satellite, or environmental measurements
  • Experimental – Controlled lab or research data from designed interventions
  • Observational – Cohort or longitudinal datasets collected without intervention
  • Omics – High-throughput sequencing or molecular profiling datasets
  • Qualitative – Non-numeric data such as transcripts, notes, audio, video
  • Simulation/Modeling – Data generated from models, simulations, or synthetic outputs
  • Survey – Structured questionnaire or interview response data. 
  • Other
• Study Type(s): Select Interventional or Observational or Other
• Keywords
• Timeframe: Input Data Collection Start Year and Data Collection End Year. If data collection is still ongoing, you can leave the End Year blank.  
• Dataset Formats: For example: .csv, .sav, .pdf
• Grant Support, including grant number (if applicable)
• Other Resources: These might include links to additional resources or associated datasets

These fields are all OPTIONAL, but they may enhance the discoverability and reusability of your dataset. We also welcome any Additional Comments. We may reach out to you with questions about your dataset submission.