Another important aspect of research data management is developing effective file management practices. Proper file management helps in identifying, locating, and maintaining data efficiently and effectively.
Furthermore, establishing consistent naming conventions is crucial for distinguishing between files. This becomes especially important when dealing with multiple files in various formats, as it allows for quick and easy retrieval.
Organizing electronic files systematically and consistently in folders will save you time when you and your research partners are searching for them. Additionally, applying file naming conventions (FNC) helps bring order to a complex group of files, allowing you to logically group files with similar information.
You don't have to include all of these elements, but a good file name may include:
Versioning occurs when you make changes to an existing file, resulting in saving a new copy. It is crucial to document new versions so the latest version can be easily identified. Use ordinal numbers for major versions and decimals for minor changes (e.g., v1, v1.1, v2.6).
Metadata is critical for managing, discovering, and understanding datasets. It provides essential information about the data, making it easier for users to find, use, and interpret the data effectively. Here's a summary on creating metadata for a dataset:
Metadata is data about data. It includes descriptions and attributes that provide context and meaning to the dataset, such as the who, what, when, where, why, and how of the data.
When creating metadata for a dataset, include the following key elements:
Title:
Creator:
Description:
Date:
Format:
Keywords:
Methodology:
Usage Rights:
Contact Information:
Geographical Coverage:
Subject:
Identifier:
Language:
Metadata Formats and Standards
When determining the appropriate metadata schema for your dataset, there are a few valuable resources to consult.
The Digital Curation Centre offers a comprehensive catalog of metadata standards organized by discipline, which can be accessed on their website: Digital Curation Centre Metadata Standards.
The Research Data Alliance (RDA) also provides a useful "Metadata Directory," listing potential metadata standards by discipline. You can explore their offerings at: RDA Metadata Directory.
Links to Commonly Used Metadata Schemas
Minimum Information About a Microarray Experiment (MIAME): Standards for microarray data to ensure that the data can be easily interpreted and verified.
Data Documentation Initiative (DDI): Standard for documenting social, behavioral, economic, and health sciences data.
Minimum Information Required by Biological and Biomedical Investigations (MIBBI): A set of guidelines for the reporting of biological and biomedical research.
Federal Geographic Data Committee (FGDC): Standards for documenting geospatial data.
ISO 19115: An international standard for the description of geographic information and services.
Climate and Forecast (CF) Metadata Conventions: Standards for climate and forecast data.
Data Documentation Initiative (DDI): A metadata standard for documenting and managing data in the social, behavioral, economic, and health sciences.
Text Encoding Initiative (TEI): Guidelines for encoding and exchanging digital texts.
Health Level 7 (HL7): Standards for the exchange of clinical and administrative data.
Clinical Data Interchange Standards Consortium (CDISC): Standards for clinical research data.
Categories for the Description of Works of Art (CDWA): Standards for describing works of art and cultural objects.
VRA Core: A data standard for the description of works of visual culture as well as the images that document them.