Open session 2021-7-19

  • No new subjects, data models, or updates in data models
  • In progress
      1. Work with frictionless data accepted by authors
      2. Working regarding the adoption of Energy data models
      3. DDI-CDI integration with NGSI-LD and smart data models
  • Pending 
    • Study automation of examples conversion.
    • DCAT-AP
      • Data service
      • Open data portal. (not from standard)
  • Next session 16th of August

 

Updated the learning zone with new videos

There is a new section in the Learning zone (4th option from the left in the upper menu).

The three new videos explain how to create data models without much technical knowledge thanks to the text editor online.

Three videos to create your first data model

These 3 videos are explaining to you how to use the online editor to create a new data model.

Are the videos useful?

    Useful (***** the best, * the worst)

    DistributionDCAT-AP in the DCAT-AP subject

    DCAT-AP is the standard for the publication of information in open data portals in the EU and other countries. Based on the 2.o.1 version these data models are mapping these two classes agent into Agent and Dataset.

    In the subject datamodel.DCAT-AP there are one data model, DistributionDCAT-AP for describing these classes,

    • DistributionDCAT-AP is a distribution belonging to a dataset according to the DCAT-AP standard 2.0.1.

    Open session 5-7-21

    Presentation of the 5-7-21 in the open session. Next session on the 12th of July 14:00h CEST.

    OPEN-SESSION-SMART-DATA-MODELS(3)

    You can join the event directly here http://bit.ly/smartdatamodels

    If you want to have it on your agenda click here.

    If you want to present something these are the slides with several free slots to be filled by the people attending.

    Source code for generating NGSI-LD key values examples based on Smart Data Models released

    According to the last open session, the script for the creation of the examples of the NGSI-LD key values is available for review and use with an open license.
    It is a python 3.6 script you can access in the utils directory of the initiative.
    Source code available

    New Agent and Dataset data models in DCAT-AP subject

    DCAT-AP is the standard for publication of information in open data portals in the EU and other countries. Based on the 2.o.1 version these data models are mapping these two classes agent into AgentDCAT-AP and Dataset.

    In the subject datamodel.DCAT-AP there are two data models, Agent. and Dataset for describing these classes,

    • Agent. Agent Schema meeting DCAT-AP 2.0 specification
    • Dataset. Dataset Schema meeting DCAT-AP 2.0 specification

    New data Model TechnicalCabinetDevice in Energy domain

    In the subject dataModel.Energy there is a new data model, TechnicalCabinetDevice for describing a technical cabinet for storing different elements in an Energy system (or for another type of system as well)

    • TechnicalCabinetDevice. Technical Cabinet Device Data Model is intended to describe the technical characteristics of the device, designed to be placed in an urban or interurban environment. The main objective of these cabinets for this Data Model is to protect the electrical equipment necessary for the control, surveillance, reading, and management of urban lighting, signaling, video, and electrical distribution. The scope of use of some of these cabinets can extend to additional protection for installations of modular apparatuses of telephony, data processing, meteorological stations, photo-voltaic stations, wind turbines stations, telecommunications, networks, data, Optics, etc. Remark: This Data Model can be used directly as a main entity to describe the device Technical Cabinet or as a sub-entity of the Data Model DEVICE using a reference by the refDevice attribute. It can also refer to the list of all the components it contains, with the refDeviceList attribute, using the Data Model DEVICE

    New data model ItemFlowObserved

    In the subject dataModel.Transportation there is a new data model, ItemFlowObserved for counting items in lanes or other places that need to be counted.

    • ItemFlowObserved. The data model intended to measure an observation linked to the movement of an item at a certain location and over a given period. This Data Model proposes an evolution of two Data Model by merging them and integrating all the attributes of the initial version of [TrafficFlowObserved] and [CrowFlowObserved] and by extension any type of item that we want to analyze the movements. Attributes vehicleType and vehicleSubType are removed from the initial data Model in order to become generic itemType and itemSubType of possible values. (people, Type of vehicle, Type of boat, Type of plane, …).