Category: Smart Environment domain

Updating all specifications to make it easier to be updated

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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

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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

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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

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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

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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

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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.

 

Announcements widget. Just thanks

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Not all changes in the data models are reported with a blog post, Twitter dissemination o LinkedIn post. But if you notice there is a widget in the right part of the front page (scroll down till Announcements) where these tiny changes are reported (see the image or browse the front page).

Most of them are issues, suggestions or PR solved thanks to the collaboration of the community. They make the data models better for all.

We cannot say thanks individually to all of them but please feel our gratitude.

You can download all of the tiny annoncements from this simple text file.

Just thanks

3 new data models for environment (and mobility)

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There are 3 new data models coming from the collaboration with the GreenMov project.

They are located at the Environment subject.

  • NoisePollutionForecast. Noise Pollution forecast stores the expectation about noise pollution based on some input elements and the noise elements present.

  • TrafficEnvironmentImpact. Environmental Impact of traffic based on the vehicles traffic and their emission characteristics

  • TrafficEnvironmentImpactForecast. Environmental Impact of traffic based on the vehicles’ traffic expectations and their emission characteristics

Vista aérea de las colas de acceso a Gibraltar (9460862160) (5)

Connecting Open Data Soft open data with Smart Data Models for drafting new data models

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Many of the datasets published in open data portals are extensively used elsewhere. Well-maintained portals have managers that document the data structure and provide definitions of the types and contents of every field in these datasets. These are some of the requirements for the successful publication of a new Smart Data Model.

With this simple python script (and others to come) at the utils folder it can be drafted a JSON schema compliant with the Smart Data Models Program contribution manual. It is an early version (not everything is updated) but you can check it out.

 Parameters:
– base url of the ODS portal
– dataset_id of the dataset
Returns:
A draft json schema compliant with Smart Data Models Program,

some limitations: it does not translate descriptions (required in English)
some data types
It prints the schema and also returns (if possible a file named schema.json)

test it with this command
SDM_OpenDataSoft_schema_converter.py https://data.ameli.fr/ effectifs