Overview

The exponential growth of scientific data across disciplines has created a pressing need for robust, flexible tools that enable harmonisation and standardisation of metadata to ensure data interoperability and reusability. A major barrier to effective data sharing lies in the heterogeneity of data formats, vocabularies, and annotation practices, which can hinder discovery, integration, and reuse. Generic data harmonisation tools, such as the Metadata Harmonisation Tool (MHT), offer a scalable and domain-agnostic approach to aligning disparate metadata schemas with community standards and ontologies. The Metadata Harmonisation Tool (MHT) is a user-friendly, flexible tool designed to help researchers and data managers standardise how data is described. It allows users to map their own data descriptions to commonly accepted formats and vocabularies, making it easier for others to find, understand, and reuse the data. MHT supports different input formats like spreadsheets and structured text, and it helps connect these with widely used data standards. By making metadata more consistent and aligned with shared practices, tools like MHT play a key role in supporting FAIR data principles—ensuring data is Findable, Accessible, Interoperable, and Reusable. By lowering the technical barriers to metadata standardisation, such tools empower data providers and users alike to adopt FAIR practices, paving the way for a more connected and reusable scientific data ecosystem.

Type of training

Virtual Webinar

Date

Intended Audience

For individuals interested in learning about resources tailored for data harmonization