-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathcdi4pan-full.obo
200 lines (169 loc) · 19.2 KB
/
cdi4pan-full.obo
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
format-version: 1.2
data-version: http://www.purl.org/cdi4pan/cdpn/releases/2024-11-06/cdi4pan-full.owl
idspace: dce http://purl.org/dc/elements/1.1/
idspace: dcterms http://purl.org/dc/terms/
idspace: skos http://www.w3.org/2004/02/skos/core#
ontology: http://www.purl.org/cdi4pan/cdpn/cdi4pan-full.owl
property_value: dcterms:description "None" xsd:string
property_value: dcterms:license https://creativecommons.org/licenses/CC0
property_value: dcterms:title "CDI for PaN data" xsd:string
property_value: owl:versionInfo "2024-11-06" xsd:string
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/Concept
name: Concept
comment: Definition n============ nUnit of thought differentiated by characteristics (from the Generic Statistical Information Model version 1.2: https://statswiki.unece.org/display/clickablegsim/Concept). nnExamples n========== nVelocity, Distance, Poverty, Income, Household Relationship, Family, Gender, Business Establishment, Satisfaction, Mass, Air Quality, etc.nnnExplanatory notes n=================== nMany DDI-CDI classes are subtypes of the concept class including category, universe, unit type, conceptual variable.
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ConceptualVariable
name: ConceptualVariable
comment: Definition n============ nA variable at the highest level of abstraction.n nExamples n========== nA gender variable defining two categories – "male" and "female" allowing relating each of these to concepts having description of how these categories are decided.nnExplanatory notes n=================== nThe conceptual variable allows for describing the domain of concepts it can take on as well as the type of unit that can be measured. A conceptual variable for blood pressure might, for example describe the conditions under which the pressure is to be taken (sitting as opposed to standing) and a conceptual value domain as height of mercury – without units. One represented variable would further refine this by specifying inches as the unit of measurement for the height. Another might specify that the height be represented in centimeters. Both represented variables could reference the same conceptual variable to indicate in what way they are comparable.
is_a: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/Concept ! Concept
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataSet
name: DataSet
comment: Definition n============ nOrganized collection of data based on keys.
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructure
name: DataStructure
comment: Definition n============nData organization based on reusable data structure components.
is_a: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructureComponent ! DataStructureComponent
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructureComponent
name: DataStructureComponent
comment: Definition n============ nRole given to a represented variable in the context of a data structure. nnExplanatory notes n=================== nA represented variable can have different roles in different data structures. For instance, the variable sex can be a measure in a wide data structure and a dimension in a dimensional data structure.
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ForeignKey
name: ForeignKey
comment: Definitionn============nRole of a set of data structure components for content referencing purposesnnExplanatory notesn===================nEquivalent to foreign key in the relational model.nIt can be used in conjunction with primary key to link data structures and their related data sets.
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ForeignKeyComponent
name: ForeignKeyComponent
comment: Definitionn============nRole of a data structure component for content referencing purposesnnExplanatory notesn===================nEquivalent to a foreign key attribute (i.e. column) in the relational model.nIt can be used in conjunction with a primary key component to link data structures and their related data sets.
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/InstanceVariable
name: InstanceVariable
comment: Definitionn==========nUse of a represented variable within a data set. nnExamplesn======== n1. Gender: Dan Gillman has gender <m, male>, Arofan Gregory has gender <m, male>, etc.n2. Number of employees: Microsoft has 90,000 employees; IBM has 433,000 employees, etc.n3. Endowment: Johns Hopkins has endowment of <3, $1,000,000 and above>, Yale has endowment of <3, $1,000,000 and above>, etc.n4. A tornado near Winterset, Iowa, had a peak wind speed of 170 mph. Two instance variables of a person's height reference the same represented variable. This indicates that they are intended to: be measured with the same unit of measurement, have the same intended data type, have the same substantive value domain, use a sentinel value domain drawn from the same set of sentinel value domains, have the same sentinel (missing value) concepts, and draw their population from the same universe. In other words, the two instance variables should be comparable.nnExplanatory notesn================= nThe instance variable class inherits all of the properties and relationships of the represented variable class and, in turn, the conceptual variable class. This means that an instance variable can be completely populated without the need to create an associated represented variable or conceptual variable. If, however, a user wishes to indicate that a particular instance variable is patterned after a particular represented variable or a particular conceptual variable that may be indicated by including a relationship to the represented variable and/or conceptual variable. Including these references is an important method of indicating that multiple instance variables have the same representation, measure the same concept, and are drawn from the same universe. If two instance variables of a person's height reference the same represented variable. This indicates that they are intended to: be measured with the same unit of measurement, have the same intended data type, have the same substantive value domain, use a sentinel value domain drawn from the same set of sentinel value domains, have the same sentinel (missing value) concepts, and draw their population from the same universe. In other words, the two instance variables should be comparable. The instance variable describes actual instances of data that have been collected.
is_a: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/RepresentedVariable ! RepresentedVariable
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/Key
name: Key
comment: Definition n============ nCollection of data instances that uniquely identify a collection of data points in a dataset.
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/KeyValueStructure
name: KeyValueStructure
comment: Definitionn============nStructure of a key-value datastore (organized collection of key-value data). It is described by identifier, contextual, synthetic id, dimension, variable descriptor and variable value components.nnExamplesn==========nThe structure described by [Income distribution, Unit id, Period, Income] where Income distribution is the contextual component, Unit id identifies a statistical unit, period is a effective period and Income is the variable of interest.
is_a: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructure ! DataStructure
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/LongDataSet
name: LongDataSet
comment: Definitionn============nOrganized collection of long data. It is structured by a long data structure.nnExamplesn==========nA unit dataset where each row corresponds to a set of data points capturing different characteristics of a unit, some of which can be transposed into variable descriptor and variable value components.
is_a: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataSet ! DataSet
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/LongDataStructure
name: LongDataStructure
comment: Definitionn============nStructure of a long dataset (organized collection of long data). It is described by identifier, measure, attribute, variable descriptor and variable value components.nnExamplesn==========nThe structure described by [Unit id, Income, Province, Variable name, Variable value] where Unit id identifies a statistical unit, Income and Province are two instance variables capturing characteristics, and other instance variables are represented by Variable name (a variable descriptor component) and Variable Value (a variable value component).
is_a: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructure ! DataStructure
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/LongKey
name: LongKey
comment: Definitionn============nCollection of data instances that uniquely identify a collection of data points in a long dataset.nnExamplesn==========nCollection containing the single "K1Z1C1" string in a long dataset where rows are identified by postal code representations.
is_a: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/Key ! Key
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/PrimaryKeyComponent
name: PrimaryKeyComponent
comment: Definitionn============nRole of a data structure component for content identification purposesnnExplanatory notesn===================nEquivalent to a primary key attribute (i.e. column) in the relational model.nIt can be used in conjunction with a foreign key component to link data structures and their related datasets.
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/RepresentedVariable
name: RepresentedVariable
comment: Definition n========== nConceptual variable with a substantive value domain specified. nnExamples n========== nThe pair (Number of Employees, Integer), where "Number of Employees" is the characteristic of the population (variable) and "Integer" is how that measure will be represented (value domain). nnExplanatory notes n=================== nExtends from conceptual variable and can contain all descriptive fields without creating a conceptual variable. By referencing a conceptual variable it can indicate a common relationship with represented variables expressing the same characteristic of a universe measured in another way, such as Age of Persons in hours rather than years. Represented variable constrains the coverage of the unit type to a specific universe. In the above case the universe with the measurement of Age in hours may be constrained to Persons under 5 days (120 hours old). Represented variable can define sentinel values for multiple storage systems which have the same conceptual domain but specialized value domains.
is_a: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ConceptualVariable ! ConceptualVariable
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/Unit
name: Unit
comment: Definitionn==========nIndividual object of interest for some statistical activity, such as data collection.nnExamplesn========nHere are 3 examples:nn1. Individual US person (i.e., Arofan Gregory, Dan Gillman, Barack Obama, etc.)n2. Individual US computer companies (i.e., Microsoft, Apple, IBM, etc.)n3. Individual US universities (i.e., Johns Hopkins, University of Maryland, Yale, etc.) [GSIM 1.1]nnExplanatory notesn=================nIn a traditional data table each column might represent some variable (measurement). Each row would represent the entity (Unit) to which those variables relate. Height measurements might be made on persons (unit type) of primary school age (Universe) at Pinckney Elementary School on September 1, 2005 (population). The height for Mary Roe (Unit) might be 139 cm.nnThe Unit is not invariably tied to some value. A median income might be calculated for a block in the U.S. but then used as an attribute of a person residing on that block. For the initial measurement the Unit was the block. In the reuse the unit would be that specific person to which the value was applied.nnIn a big data table each row represents a unit/variable double. Together a unit identifier and a variable identifier define the key. And for each key there is just one value – the measure of the unit on the variable.nnA big data table is sometimes referred to as a column-oriented data store whereas a traditional database is sometimes referred to as a row-oriented data store. The unit plays an identifier role in both types of data stores.
[Term]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/UnitType
name: UnitType
comment: Definitionn==========nUnit type is a type or class of objects of interest (units).nnExamplesn========nPerson, Establishment, Household, State, Country, Dog, Automobile, Neutrino.nnExplanatory notesn=================nUnit type is the most general in the hierarchy of unit type, universe, and population. It is a description of the basic characteristics for a general set of Units. A universe is a set of entities defined by a specialization of a unit type. A Population further narrows the specification to a specific time and geography.nnA unit type is used to describe a class or group of Units based on a single characteristic with no specification of time and geography. For example, the unit type of "Person" groups together a set of Units based on the characteristic that they are "Persons".nnIt concerns not only unit types used in dissemination, but anywhere in the statistical process. E.g. using administrative data might involve the use of a fiscal unit. [GSIM 1.1].
is_a: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/Concept ! Concept
[Typedef]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/Concept_uses_Concept
name: uses
comment: The uses association is intended to describe specific relationships between Concepts and several of its sub-classes. This is documented in section VII.D.5 of the "DDI-Cross Domain Integration: Detailed Model" document.
property_value: skos:altLabel "Concept_uses_Concept" xsd:string
domain: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/Concept ! Concept
range: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/Concept ! Concept
[Typedef]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ConceptualVariable-unitOfMeasureKind
name: unitOfMeasureKind
comment: Kind of unit of measure, so that it may be prone to translation to equivalent UOMs. Example values include "acceleration," "temperature," "salinity", etc. This description exists at the conceptual level, indicating a limitation on the type of representations which may be used for the variable as it is made more concrete.
domain: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ConceptualVariable ! ConceptualVariable
range: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ControlledVocabularyEntry
[Typedef]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ConceptualVariable_measures_UnitType
name: measures
comment: The measures association is intended to describe specific relationships between the ConceptualVariable and UnitType classes, and similar relationships between their sub-classes. This is documented in section VII.D.5 of the "DDI-Cross Domain Integration: Detailed Model" document.
property_value: skos:altLabel "ConceptualVariable_measures_UnitType" xsd:string
domain: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ConceptualVariable ! ConceptualVariable
range: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/UnitType ! UnitType
[Typedef]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataSet_isStructuredBy_DataStructure
name: isStructuredBy
property_value: skos:altLabel "DataSet_isStructuredBy_DataStructure" xsd:string
domain: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataSet ! DataSet
range: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructure ! DataStructure
[Typedef]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructureComponent-identifier
name: identifier
comment: Identifier for objects requiring short- or long-lasting referencing and management.
domain: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructureComponent ! DataStructureComponent
range: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/Identifier
[Typedef]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructureComponent_isDefinedBy_RepresentedVariable
name: isDefinedBy
comment: Data structure component is defined by zero to one represented variable.
property_value: skos:altLabel "DataStructureComponent_isDefinedBy_RepresentedVariable" xsd:string
domain: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructureComponent ! DataStructureComponent
range: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/RepresentedVariable ! RepresentedVariable
[Typedef]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructure_has_DataStructureComponent
name: has
property_value: skos:altLabel "DataStructure_has_DataStructureComponent" xsd:string
domain: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructure ! DataStructure
range: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructureComponent ! DataStructureComponent
[Typedef]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructure_has_ForeignKey
name: has
property_value: skos:altLabel "DataStructure_has_ForeignKey" xsd:string
domain: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructure ! DataStructure
range: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ForeignKey ! ForeignKey
[Typedef]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ForeignKey-identifier
name: identifier
comment: Identifier for objects requiring short- or long-lasting referencing and management.
domain: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ForeignKey ! ForeignKey
range: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/Identifier
[Typedef]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ForeignKeyComponent_correspondsTo_DataStructureComponent
name: correspondsTo
property_value: skos:altLabel "ForeignKeyComponent_correspondsTo_DataStructureComponent" xsd:string
domain: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ForeignKeyComponent ! ForeignKeyComponent
range: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/DataStructureComponent ! DataStructureComponent
[Typedef]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ForeignKeyComponent_references_PrimaryKeyComponent
name: references
property_value: skos:altLabel "ForeignKeyComponent_references_PrimaryKeyComponent" xsd:string
domain: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/ForeignKeyComponent ! ForeignKeyComponent
range: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/PrimaryKeyComponent ! PrimaryKeyComponent
[Typedef]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/PrimaryKeyComponent-identifier
name: identifier
comment: Identifier for objects requiring short- or long-lasting referencing and management.
domain: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/PrimaryKeyComponent ! PrimaryKeyComponent
range: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/Identifier
[Typedef]
id: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/Unit_has_UnitType
name: has
comment: The unit type of the unit.
property_value: skos:altLabel "Unit_has_UnitType" xsd:string
domain: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/Unit ! Unit
range: http://ddialliance.org/Specification/DDI-CDI/1.0/RDF/UnitType ! UnitType