Explore the ASAM ODS Data Model#

In this example Notebook, we show you how to explore the data model of your Peak ODS Server.

Understanding the data model is important once it comes to query (instance) data from your Peak ODS Server.

The first sections is on inspecting the base model. The programming fun starts with “Explore the ASAM ODS Application Model”.

ASAM ODS Base Model#

The ASAM ODS Base Model defines the sematic or building blocks of an ASAM ODS Application Model. It defines the fundamental entities, attributes, and relations that are used to describe and structure measurement and test data in a standardized way.

The ASAM ODS BaseModel Viewer below lets you interactively inspect the base model.

Have fun 😊 exploring the base model.

Click here to open the ASAM ODS BaseModel Viewer in a separate window.

# The ASAM ODS BaseModel Viewer HTML file is locally installed in the curriculum
# We use an IFrame to display it in the notebook
#  
base_model_viewer = "../_static/asam_ods_basemodel_viewer.html"

from IPython.display import IFrame
IFrame(src=base_model_viewer, width='100%', height=600)

ASAM ODS Application Model#

The ASAM ODS application model use the building blocks of the base model to define an application specific data model - tailored to your needs.

Establish session#

The ODS HTTP API is a session based API. The session ID is called con_i in the ODS documentation. The ASAM ODSBox uses con_i as API object representing the session. Close this session to release the connection license. Otherwise the session will be auto closed after 30 minutes of inactivity.

try:  
  import odsbox
except:
  !pip install odsbox 

from odsbox.con_i import ConI

con_i = ConI(url='https://docker.peak-solution.de:10032/api', auth=('Demo','mdm'))

Explore the Data Model#

The data model describes the way your data is stored in the Peak ODS Server. The data model consists of entities (you can compare them to class-definitions) and their according attributes and relations to other entities.

model = con_i.model()

List all Entities#

Entities are the major building blocks of the data model. You typically query for instances of entities to explore your data. Let’s list all entities to see what we have

for entity in model.entities:
  print(entity)
TplTestEquipmentRoot
TplParameterSet
MDMRole
TplSubMatrix
UserParameter
CatSensor
StructureLevel
Role
ProjectDomain
TplTestStep
TplSensorAttr
DynToken
ActionRun
MeaQuantity
CatTestSequenceComp
ExtSystemAttr
TplTestSequenceComp
MDMTagParameter
TestEquipment
MDMLocalization
Workflow
CatTestEquipmentComp
MDMLog
TplGroup
ValueList
ToAction
Project
AttributeMap
MDMTagParameterSet
CatUnitUnderTestAttr
Condition
InitToken
TplSensor
MeaResult
MDMAttr
FavouriteLists
TestSequence
WorkflowParameter
TokenType
Action
TestStep
CatTestSequenceAttr
CatUnitUnderTestComp
ToCondition
MDMGroup
LocalColumn
TplParameter
TplTestSequenceRoot
Test
ExternalComponent
TplTestEquipmentComp
CatTestEquipmentAttr
TplTestSequenceAttr
Unit
ExtSystem
TplTestStepUsage
MDMFunction
TplUnitUnderTestAttr
MDMTag
TplTestEquipmentAttr
Environment
Quantity
ValueListValue
TplUnitUnderTestComp
SubMatrix
User
TplUnitUnderTestRoot
NameMap
ResultParameter
Domain
TplTest
StatusValidity
PhysDimension
UnitUnderTest
TplMeaResult
SystemParameter
CatSensorAttr
WorkflowRun
Classification
Status
ResultParameterSet
WorkflowParameterSet

Examine a specific entitiy#

The entitiy definition contains some information of the entity itself and all attributes and references of this entity.

Have a specifc look to the base_name - in other data models your specific entity may have a diferent name. You can use the base_name for data model agnostic queries.

Also the aid can be of importance of you deal directly with the ASAM ODS REST API, not using JAQueL.

model.entities["Unit"]
name: "Unit"
base_name: "AoUnit"
aid: 54
attributes {
  key: "dB"
  value {
    name: "dB"
    data_type: DT_BOOLEAN
    length: 1
    id: 7
  }
}
attributes {
  key: "dB_reference_factor"
  value {
    name: "dB_reference_factor"
    data_type: DT_FLOAT
    length: 1
    id: 8
  }
}
attributes {
  key: "Offset"
  value {
    name: "Offset"
    base_name: "offset"
    data_type: DT_DOUBLE
    length: 1
    obligatory: true
    id: 6
  }
}
attributes {
  key: "Name"
  value {
    name: "Name"
    base_name: "name"
    data_type: DT_STRING
    length: 50
    obligatory: true
    unique: true
    id: 1
  }
}
attributes {
  key: "MimeType"
  value {
    name: "MimeType"
    base_name: "mime_type"
    data_type: DT_STRING
    length: 256
    obligatory: true
    id: 2
  }
}
attributes {
  key: "Id"
  value {
    name: "Id"
    base_name: "id"
    data_type: DT_LONGLONG
    length: 1
    obligatory: true
    unique: true
    autogenerated: true
  }
}
attributes {
  key: "Factor"
  value {
    name: "Factor"
    base_name: "factor"
    data_type: DT_DOUBLE
    length: 1
    obligatory: true
    id: 5
  }
}
attributes {
  key: "Description"
  value {
    name: "Description"
    base_name: "description"
    data_type: DT_STRING
    length: 500
    id: 3
  }
}
attributes {
  key: "DateCreated"
  value {
    name: "DateCreated"
    base_name: "version_date"
    data_type: DT_DATE
    length: 30
    id: 4
  }
}
relations {
  key: "WorkflowParameter"
  value {
    name: "WorkflowParameter"
    base_name: "parameters"
    inverse_name: "Unit"
    inverse_base_name: "unit"
    entity_name: "WorkflowParameter"
    entity_aid: 73
    virtual_reference: true
    range_max: -1
    inverse_range_max: 1
    relation_type: RT_INFO
    relationship: RS_INFO_FROM
  }
}
relations {
  key: "TplParameter"
  value {
    name: "TplParameter"
    base_name: "parameters"
    inverse_name: "Unit"
    inverse_base_name: "unit"
    entity_name: "TplParameter"
    entity_aid: 71
    virtual_reference: true
    range_max: -1
    inverse_range_max: 1
    relation_type: RT_INFO
    relationship: RS_INFO_FROM
  }
}
relations {
  key: "ResultParameter"
  value {
    name: "ResultParameter"
    base_name: "parameters"
    inverse_name: "Unit"
    inverse_base_name: "unit"
    entity_name: "ResultParameter"
    entity_aid: 66
    virtual_reference: true
    range_max: -1
    inverse_range_max: 1
    relation_type: RT_INFO
    relationship: RS_INFO_FROM
  }
}
relations {
  key: "Quantities"
  value {
    name: "Quantities"
    base_name: "quantities"
    inverse_name: "Unit"
    inverse_base_name: "default_unit"
    entity_name: "Quantity"
    entity_aid: 55
    virtual_reference: true
    range_max: -1
    inverse_range_max: 1
    relation_type: RT_INFO
    relationship: RS_INFO_FROM
  }
}
relations {
  key: "PhysDimension"
  value {
    name: "PhysDimension"
    base_name: "phys_dimension"
    inverse_name: "Units"
    inverse_base_name: "units"
    entity_name: "PhysDimension"
    entity_aid: 47
    range_min: 1
    range_max: 1
    inverse_range_max: -1
    relation_type: RT_INFO
    relationship: RS_INFO_TO
  }
}
relations {
  key: "MeaQuantities"
  value {
    name: "MeaQuantities"
    base_name: "measurement_quantities"
    inverse_name: "Unit"
    inverse_base_name: "unit"
    entity_name: "MeaQuantity"
    entity_aid: 80
    virtual_reference: true
    range_max: -1
    inverse_range_max: 1
    relation_type: RT_INFO
    relationship: RS_INFO_FROM
  }
}
relations {
  key: "MDMTagParameter"
  value {
    name: "MDMTagParameter"
    base_name: "parameters"
    inverse_name: "Unit"
    inverse_base_name: "unit"
    entity_name: "MDMTagParameter"
    entity_aid: 65
    virtual_reference: true
    range_max: -1
    inverse_range_max: 1
    relation_type: RT_INFO
    relationship: RS_INFO_FROM
  }
}

Examine Attributes#

Looking at the attributes is also important when examine the data model. Like entities, also attributes can have a base_name to be used for data model agnostsic queries.

Furthermore data_type and obligatory information is important - especially when it comes to writing data

model.entities["Unit"].attributes["Name"]
name: "Name"
base_name: "name"
data_type: DT_STRING
length: 50
obligatory: true
unique: true
id: 1

Examine Relations#

Relations describe the connection between entities. In a data model relations are important for exploring the data neighbors. Relations have names to identify them (think of identifying a specific tire like “front left”) and the definition of the entity they’re pointing to: the entity_name. With range_min and range_max you can determine whether a relation is obligatory. In case a relation has also a (parallel) backward relation, the inverse_name contains this information.

model.entities["Unit"].relations["PhysDimension"]
name: "PhysDimension"
base_name: "phys_dimension"
inverse_name: "Units"
inverse_base_name: "units"
entity_name: "PhysDimension"
entity_aid: 47
range_min: 1
range_max: 1
inverse_range_max: -1
relation_type: RT_INFO
relationship: RS_INFO_TO

Close session#

Don’t forget to close the session to release the connection license. Otherwise the session will be auto closed after 30 minutes of inactivity.

con_i.logout()

License#

Copyright © 2025 Peak Solution GmbH

The training material in this repository is licensed under a Creative Commons BY-NC-SA 4.0 license. See LICENSE file for more information.

Notebook: 📓 Back to ASAM ODS Overview