This group represents a collaborative, community effort with a mission to develop, maintain, and promote standard schemas for data mining and machine learning algorithms, datasets, and experiments. Our target is a community agreed schema as a basis for ontology development projects, markup languages and data exchange standards; and an extension model for the schema in the area of data mining and machine learning.
The goals of this group are:
To define a simple shared schema of data mining/ machine learning (DM/ML) algorithms, datasets, and experiments that may be used in many different formats: XML, RDF, OWL, spreadsheet tables.
Collect use cases from the academic community and industry
Use this schema as a basis to align existing DM/ML ontologies and develop more specific ontologies with specific purposes/applications
Prevent a proliferation of incompatible DM/ML ontologies
Turn machine learning algorithms and results into linked open data
Promote the use of this schema, including involving stakeholders like ML tool developers
Apply for funding (e.g. EU COST, UK Research Councils, Horizon2020 Coordination and Support Actions) to organize workshops, and for dissemination
ML-Schema/Group's public email, repo and wiki activity over time
Note: Community Groups are proposed and run by the community. Although W3C hosts these
conversations, the groups do not necessarily represent the views of the W3C Membership or staff.
We are using GitHub to coordinate the creation of ML Schema: https://github.com/ML-Schema/core
There you can find the latest information, working guidelines, conference call times, and the issues that we are currently working on. We will still publish reports regularly here on W3C, but we use GitHub for day to day work.
I’m looking forward to seeing you there. Please let me know if you have more questions about ML Schema or how to contribute.
This group represents a collaborative, community effort with a mission to develop, maintain, and promote standard schemas for data mining and machine learning algorithms, datasets, and experiments. Our target is a community agreed schema as a basis for ontology development projects, markup languages and data exchange standards; and an extension model for the schema in the area of data mining and machine learning.
The goals of this group are:
To define a simple shared schema of data mining/ machine learning (DM/ML) algorithms, datasets, and experiments that may be used in many different formats: XML, RDF, OWL, spreadsheet tables.
Collect use cases from the academic community and industry
Use this schema as a basis to align existing DM/ML ontologies and develop more specific ontologies with specific purposes/applications
Prevent a proliferation of incompatible DM/ML ontologies
Turn machine learning algorithms and results into linked open data
Promote the use of this schema, including involving stakeholders like ML tool developers
Apply for funding (e.g. EU COST, UK Research Councils, Horizon2020 Coordination and Support Actions) to organize workshops, and for dissemination
This is a community initiative. This group was originally proposed on 2015-09-28 by Joaquin Vanschoren. The following people supported its creation: Joaquin Vanschoren, Agnieszka Lawrynowicz, Diego Esteves, Panče Panov, Diego Moussallem, Carmen Popoviciu. W3C’s hosting of this group does not imply endorsement of the activities.
ML-Schema/