Organisation & description

Organizing your files and folders - electronic or paper - is a time-consuming activity but, in the end, it proves to be a considerable help: it makes it easier and faster to identify, locate, retrieve or even recover your data.

A good organization consists in particular of :

Structure your folders hierarchically (classification tree)
Use clear, consistent and most meaningful naming conventions and rules

Ideally, these rules should be defined as soon as possible in the life of the project, before creating too many files and folders. To avoid being overwhelmed, remember to sort, arrange or reorganize them regularly !

When you are conducting a research project as part of a team, it is essential that the whole group agree on the structure of folders and the name of the files to be adopted. This can be recorded and documented to allow everyone to access and find stored and shared data via the same collaborative workspace.

Folder and file tree structure

Organizing your files and folders is a task that should be thought out and carried out at the very beginning of the research project. It is important to choose a clear, consistent and common organization for the different data sets.

Literally ‘data about data’, metadata is data used to define or describe other data, whatever its medium.

Metadata documents how the data was generated, under what licence and how it can be re-used. It also provides the context for appropriate interpretation by other researchers.

Every dataset collected or created should be accompanied by comprehensive metadata, respecting the standards, rules and conventions of a discipline, and also machine-readable. See Guide to writing ‘readme’ style metadata (Cornell University).

Although data managers and, increasingly, researchers are aware that good metadata is essential for accessing and re-using research data, it can be complex to determine exactly what metadata to capture. It should be borne in mind that only quality metadata supports the FAIR principles.

Minimum set of metadata

An international consortium of libraries and services specialising in information sciences, DataCite has developed a metadata schema for publishing and citing research data. In its Metadata Schema Documentation for the Publication and Citation of Research Data (Version 4.2., 2018), the minimum set of mandatory metadata to be used when describing (sets of) data is as follows:

• Identifier (of the dataset)
• Creator
• Title
• Publisher
• PublicationYear
• RessourceType

Some other metadata are optional:

• Subject
• Contributor
• Date
• RelatedIdentifier
• Description
• GeoLocation

Disciplinary metadata

Many disciplines have developed specific metadata standards. A full list is available on the Digital Curation Center website and on FAIRsharing.org.

Data Documentation Initiative (DDI)

This initiative is an international standard for describing data produced in the social, behavioural, economic and health sciences. DDI standards enable data to be documented, discovered and interoperated. Specifications and tools are available on the DDI website.

Metadata Standards Directory Working Group

The Metadata Standards Directory Working Group is supported by individuals and organisations involved in the development, implementation and use of metadata for scientific data. The overarching goal is to develop an open and collaborative repository of metadata standards for scientific data to address the challenges of data infrastructure and organisation.