Run Metadata for Machines workshops
The purpose of M4M workshops
There is no FAIR data without machine-actionable metadata. The overall goal of Metadata for Machines workshops (M4M) is to make routine use of machine-actionable metadata in a broad range of fields.
Typically, M4M workshops are lightweight, fast-track events where policy and domain experts can build new, or make informed choices regarding the reuse of already existing metadata schema as part of their overall FAIRification efforts.
Although M4M workshops can serve many purposes, they are usually intended to kick-start FAIRification efforts with minimally viable metadata components that are modular, reusable, and can be later extended as needed. Although metadata needs are as complex and open ended as is human activity, M4M workshops encourage participants to design modular components that can be used by fellow data stewards working within that community, but will later invite widespread reuse and open source development within other domain communities. By providing an open standard for component metadata that specifically address the FAIR Principles, the M4M framework accelerates the FAIRification ‘on-boarding’ process and guarantees widespread, automated interoperation.
The M4M workshops format
The M4M workshop format teams up domain experts (who are able and willing to represent a domain community) with metadata experts (data stewards) who guide a discussion leading to the definition of metadata requirements that meet the FAIR data needs of that domain community.
The M4M workshops are agile, hackathon-style events that make it easy for humans to make metadata for machines.
They bring together domain experts with metadata and technical specialists to accomplish 5 objectives:
- Assess the state of metadata practices in the various scientific communities, look for improvements of the current fragmentation and promote good FAIR compliant practices.
- Using the FAIR principles as a guide, define essential metadata elements and standards to support F, A, I, and R by machines, drawing on the deep domain knowledge of existing communities.
- Formulate these decisions as machine-actionable templates in a unified way.
- Register these templates such that they are FAIR and openly accessible and available for re-use by tools that can render these templates in familiar, easy to use web forms, APIs, or other capture tools.
- Bundle appropriate M4M metadata categories and register them as FAIR compliant metadata components, ensuring higher degrees of Findability, Accessibility, Interoperability, and Reusability by machines.
These 5 objectives result in domain-specific, community built, FAIR metadata schema that compose in part the overall FAIR Implementation Profile of that domain community.
Previous M4M Workshops
Examples of metadata reuse between M4M stakeholders have been highlighted in the GO FAIR/ CODATA Convergence Symposium, November 30 to December 4, 2020.
As of July 2021, 17 M4M workshops have been completed, covering diverse of disciplines (e.g., wind energy, socio-economic research, clinical and laboratory studies of infectious disease, veterinary science and others). The success of the M4M methods has resulted in uptake of the M4M workshop in numerous international funding organisations to ensure grantees produce FAIR research data. These funders include, the Dutch ZonMw, the Danish DeiC, the UK’s Wellcome Trust and National Institute for Health Research, the Austrian Science Fund, the Canadian Institutes of Health Research, the Swiss National Science Foundation and US National Institutes of Health (link). We have now a growing list of requests from specialised groups requesting M4Ms for their domain.
Three-point FAIRification icons
The official icons for the Three-Point FAIRification Framework (Metadata for Machines Workshops, FAIR Implementation Profile and FAIR Data Point) have been registered at Zenodo under the Creative Commons Attribution Share Alike 4.0 International license.