Minutes [Re: ML Schema call agenda June 20, 2016]

Dear All,

Thank you for today’s call.

Below please find the minutes from the call (also included at [1]).


**Minutes from the ML Schema call June 20, 2016**

Decisions:
We have agreed that it would be good to try to finalize the draft documentation before most of us are gone for holidays.
We need to make clear in the documentation: What it is for? (maybe link to the goals of our group and use cases), Why? (again look into the goals of the group such as to align existing schemas, to avoid proliferation of very similar resources), And how can ML Schema be used? (Provide examples and how to link to other resources).
Some issues identified to achieve this:

1) Documentation - Introduction:
* to add the text on the motivation for ML Schema, e.g. to align existing ontologies and schemas (cite them in the references?), that is why we propose only highlevel, lightweight model
* to also motivate by the need for reproducible research 
* to add something on the Audience („This document is mainly addressed to ML researchers / practisioners,..”, „for them to accomplish specific goals...” etc.)

2) Documentation - linking to other resources:
* to describe (in the section after introduction of the core model), that this proposed schema is complaint with other resources and can be used together with other ontologies and resources to provide more detailed information, e.g. with: DM/ML ontologies and schemas, software ontologies, PROV, Investigation-Study-Assay, Datatype ontologies etc.

3) Documentation - other: 
* to cite OpenML and say that the example is derived from OpenML  
* add to the current example the information on the task type (that :task29 is of type ClassificationTask). Add this to the text and also add this to the example code in turtle (with another namespace outside ML Schema core). 
* explain what this schema in NOT meant for? (e.g., it is not meant to be a comprehensive ontology of ML which is going to replace existing models - those are already quite comprehensive, having various goals and are not going to be replaced)
* Incorporate the information on the envisaged use cases? They are listed on the Wiki of the group. 

The way we are going to proceed:
@Diego will be working on the points 1) and 2) until the end of the week (or next Monday the latest) and later on he will pass it to the next person who will pass it to @Larisa on July 1st. 

Other news: 
* @Tommaso and @Joaquin are working hard on openML2rdf code which is close to being complete. 


Regards and cheers,
Agnieszka

[1] https://github.com/ML-Schema/core/wiki/Call-minutes


> Wiadomość napisana przez Agnieszka Ławrynowicz <agnieszka.lawrynowicz@cs.put.poznan.pl> w dniu 20.06.2016, o godz. 11:16:
> 
> Dear All,
> 
> Below please find an agenda for the today’s call of the Machine Learning Schema W3C Community Group.
> 
> Call June 20, 2016, 1.30pm CET
> 
> Agenda 
> 
> 1. To identify missing bits and pieces to complete the documentation [1]. 
> 2. To identify missing bits and pieces regarding the converter from RDF to JSON-LD and back available from OpenML (openML2rdf code)
> 3. (optionally) Ontology Design Pattern originating from ML Schema 
> 
> We will use Google Hangout for the call [2].
> 
> Regards and Cheers,
> 
> Agnieszka
> 
> PS. The next call is scheduled for July 4, 2016, 1.30pm CET.
> 
> [1] https://github.com/ML-Schema/documentation <https://github.com/ML-Schema/documentation>
> [2] https://hangouts.google.com/call/dskyydrmpsybpvxhql5aehiht4a <https://hangouts.google.com/call/dskyydrmpsybpvxhql5aehiht4a>
>