Minor update on guidelines

Included two new sections on the guidelines for the Smart Data Models

$ref

Whenever possible they will be absolute references in order to provide the ability to use the data models isolated from the rest of documents

and

definitions

The section definitions will be included in the subject-schema.json name of the subject.

 

 

Help for data modellers

Some of the contributors have requested some help about creating new data models. How to do it and where to do it.

HOW TO CREATE DATA MODELS

1) If you are clear about the payloads that you want to share (you have a plain key values json payload)

i.e. https://raw.githubusercontent.com/smart-data-models/dataModel.Weather/master/WeatherObserved/example.jsonld

2) You can use this tool https://www.liquid-technologies.com/online-json-to-schema-converter (This link is always available in the Learning Zone on the upper menu, section tools)

to generate a draft version of the json schema. You will have to review (for sure).

– Whether you need some restrictions (min, max) on number properties

– The number of required properties

– The full list of options in enumeration properties

– Remove the context (it is treated as property)

– Check the Arrays (minItems, etc)

and possibly some other minor issues

WHERE TO CREATE DATA MODELS

3) We offer an open repository named pending for you to contribute while developing. Ask for access raising an issue with the option ‘Access to pending repository’

http://data-models.fiware.org/index.php/submit-an-issue-2/

Methodology for working groups to create new data models

Most of the data models come from different groups of people interested in the creation of standards in an agile way.

Here you can access a cheat sheet (Let’s call it methodology) on how to tackle these tasks.

summarized these are the steps. It takes for granted that the group is already available.

Step 0. Gather documentation

Step 1. Compile elements.

Step 2. Meet to reach a Generalization proposal

Step 3. Internal validation

Step 4. Create the technical documentation of a data model

Step 5. Submit your data model

Step 6. Review

Step 7. Disseminate