Release source code for some of the services. For python developers.

In the tools option of the main menu, there are a few services to help you to use, create and debug your data models.

Although working, some of these services are limited. We are releasing the code for some of the services to allow you to contribute with improvments.

It appears by the end of the page with texts like this:

“source code of this service if you want to improve it.”

Source code has an hyperlink pointing to the specific script in the utils directory.

They are created in python and connected to the WP forms in each option

Specifically

List of Adopters (use cases) and contributors available at Community menu

On the front page under the Community menu, there are two new entries
Adopters: Lists the use cases documented in the different data models. It includes searchable facilities. It contains these fields:  adopter, description, mail, organization, project, comments, start date, subject and data model.

If you want to be listed, just make a PR on the file ADOPTERS.yaml of the data model folder. (The PR has to include an example ‘payload’ on how you use it)

Contributors: Lists the people. It contains these fields:  name, surname, mail, organization, project, comments, year, and subject.

If you want to be listed you have to have contributed to any of the data models of the subject and then make a PR on the CONTRIBUTORS.yaml at the root of the subject.

In both cases the attributes are not mandatory so they can be empty.

New information customized for the different profiles

In the documentation menu (Home -> documentation -> Basic info for:), there are now 4 new options to provide you with the basic information depending on your profile

  • User. For those visitors with limited knowledge about what are the Smart Data Models
  • Contributor. For those visitors willing to extend or to contribute with new data models
  • Developer. For those visitors willing to integrate the data models with other tools or initiatives
  • Researcher. For those visitors whose aim is to understand what is agile standardization and how it is implemented at the Smart Data Models Program

If you have some of these profiles and you miss some information please let us know

Updating all specifications to make it easier to be updated

Initially, you will see few changes in the specifications of all data models,(it is in progress because it will last around 2 days to get it completed)

– The inclusion of the model for those attributes having it.

– Including the data type (when there is only one) for the attributes. ”

– A footer with some useful links, etc

Smart Data Models +++ Contribution Manual +++ About

but there is another hidden relevant change. The specifications are now divided into sections by these tags:

<!– section name –>

<!– /section name –>

It makes easier to update part of the specification without disrupting the rest of the content, and in most markdown viewers it is unnoticed. Besides this, it also allows the extension of the specification (if needed in a coming future) with new sections.

And, of course, everything can be done automatically. Thus we can keep being agile according to our principles.

Therefore, if you see that the specifications are presenting an update don’t worry, Initially, it is just the format and this new trick.

And welcome to the Chinese translation which is using this new format already.

 

Year of contribution at the CONTRIBUTORS.yaml

All the CONTRIBUTORS.yaml files across all subjects have been extended with a new attribute year. This year means the year of the contribution.
It will help us to give recognition to the contributors.
By default, it has been set to 2022 (it was much work to find out when the last contribution was submitted for each one of the several contributors across the 60 subjects).

It has been also changed in the template of the CONTRIBUTORS file in the templates folder.

Contributors: Updated the service for checking your schema

In order to create a new data model or to update an existing one, Check your schema before contributing it, to check the schema on the front page.

The service has been updated to check not only the attributes of the payload but also the schema metadata (schema version, license, derivedFrom, title, description) so it will be easier to complete it before submission.

The code is available at the directory utils in the data-model repository.

Presentations of the Smart Data Models session at FIWARE summit

Here you can have the presentation of the people presenting at the Smart Data Models session of the FIWARE summit.

1.- Fernando Lopez (FIWARE Foundation) SDMX towards context information: achieving interoperability
2.- David Garcia (NTT Data) Public resources monitoring and management through innovative solutions based on extension of smart data models
3.- Mannix manglani (Mannixonline) TOURISM DATA MODELS
4.- Alberto Abella (FIWARE Foundation) Water data models
5.- Antonino Sirchia (Engineering) How FIWARE and Smart Data Models can make a City resilient on Flooding Risks
6.- Romain Magnani (EGM) The NGSI-LD data lab: an engaging interface for building NGSI-LD data configuration
7.- Clara Pezuela (ATOS) GreenMov: Green and smart mobility services
8.- Andrea Cruciani.(FIWARE SmartAgriFood MSC ) Agrigateway
9.- Hugo Miguel Serra (Deloitte) Smart Buildings data models

Training on Smart Data models

Tomorrow at day 0 of the FIWARE summit there will be a training session about Smart Data Models.
Slides are freely shared here

This training will be delivered face to face.

  • Intro:
    • Board and what is Smart Data Models Program
    • Current Status
    • Contributos and dissemintions
  • Agile standardization
    • Current standardization status
    • M.A.S.: Manifesto for agile standardizationç
    • Standardization in a digital market
  • Data model contents
    • Contents of a data model
    • Schema: review
    • Additional documents: examples, contributors, adopters, notes*
    • Generated documents: model.yaml, examples, README, context
  • Data Model creation
    • Incubated repository.
    • From csv, json or open data portals
    • Tests
  • Data Model moderation
    • Data model moderation
  • Future
    • pysmartdatamodels
    • New services. Integration
    • New data models. Mapping of standardizations
    • Other services for the contributors

MAS: Manifesto for Agile Standardization

The Manifesto for Agile Standardization (MAS) describes the 7 principles that we apply to the Smart Data Models program.

0. Don't just standardize, be agile and standardize
1. Do not reinvent the wheel
2. Normalize real cases
3. Be open
4. Don't be overly specific
5. Flat not Deep
6. Sustainability is key

If you want to read the agile standardization manifesto’s complete explanation a one-page document is located at the root of our data models repository.