Guide to Documenting Research Data

Purpose: This guide provides detailed instructions for authors on how to properly document research data, facilitating its understanding, use, and reuse by the scientific community and the general public.

 Scope: It applies to all research data, including quantitative and qualitative data, large and small datasets, and related materials such as software codes and protocols, submitted alongside manuscripts to [Journal Name].

Basic Principles of Documentation:

  1. Clarity: Documentation should be clear and easy to understand.
  2. Comprehensiveness: Include all necessary information to understand, evaluate, and use the data.
  3. Accessibility: Ensure that documentation is easily accessible along with the dataset.

Essential Elements of Documentation

Descriptive Metadata

  • Dataset Title: Clear and descriptive, reflecting the content of the dataset.
  • Author(s): Full names and institutions of those who generated the data.
  • Creation Date: When the data was generated or collected.
  • Version: If applicable, the version of the dataset.
  • Location: Repository where the data is hosted and its persistent identifier (e.g., DOI).

Data Context

  • General Description: An explanation of the nature of the data and the (type of) research for which it was generated.
  • Keywords: Terms facilitating dataset search and retrieval.
  • Temporal and Geographic Coverage: The time period and geographic location of the data.

Methodology

  • Data Collection and Processing: Describe data collection, processing, and analysis.
  • Standards and Calibrations: Any standards used or calibrations performed.
  • Instrumentation and Software: Details of any specialized equipment or software used.

Data Structure and Format

  • File Format: Specify the format of the data and the reasons for its choice.
  • Data Structure: Describe the organization of the data, including the description of variables, codes, and units of measurement.

Access and Use

  • Usage License: Details on how the data can be used, including any restrictions.
  • Access Guide: How to access the data and any software needed for its visualization or analysis.

Support and Contact

  • Support Contact: Contact information for queries or clarifications about the data.

Best Practices

  • Use recognized metadata standards to facilitate interoperability.
  • Include examples of data citation and reuse.
  • Ensure privacy and ethics, especially with sensitive data.

Conclusion: Proper data documentation is essential for transparency, replicability, and the advancement of scientific knowledge. [Journal Name] encourages authors to follow these guidelines to maximize the impact and accessibility of their research.