The document describes a generic multilevel approach for designing domain ontologies based on XML schemas. It maps XML schema elements to an ontology and then maps XML instances to generated ontologies. The approach extracts semantic information from XML schemas and instances to build domain ontologies represented in OWL or RDF.
This slide is based on Object Oriented Programming Language. Here is some details about object and class. You can easily understand about object and class.
This slide is based on Object Oriented Programming Language. Here is some details about object and class. You can easily understand about object and class.
(Or, building better UX / Apps with distributed databases and data synchronisation techniques).
This was my talk at Cocoaheads Berlin 17th February 2016.
Integrating a Domain Ontology Development Environment and an Ontology Search ...Takeshi Morita
In order to reduce the cost of building domain ontologies manually, in this paper, we propose a method and a tool named DODDLE-OWL for domain ontology construction reusing texts and existing ontologies extracted by an ontology search engine: Swoogle. In the experimental evaluation, we applied the method to a particular field of law and evaluated the acquired ontologies.
MySQL Group Replication is a new 'synchronous', multi-master, auto-everything replication plugin for MySQL introduced with MySQL 5.7. It is the perfect tool for small 3-20 machine MySQL clusters to gain high availability and high performance. It stands for high availability because the fault of replica don't stop the cluster. Failed nodes can rejoin the cluster and new nodes can be added in a fully automatic way - no DBA intervention required. Its high performance because multiple masters process writes, not just one like with MySQL Replication. Running applications on it is simple: no read-write splitting, no fiddling with eventual consistency and stale data. The cluster offers strong consistency (generalized snapshot isolation).
It is based on Group Communication principles, hence the name.
Workshop on Semantic Statistics - Generic Multilevel Approach Designing Domai...Dr.-Ing. Thomas Hartmann
Workshop presentation: Semantic Statistics for Social, Behavioural, and Economic Sciences: Leveraging the DDI Model for the Web (12.09.2011 - 16.09.2011)
SQLPASS presentation on performance tuning and best practices for XML and XQuery in Microsoft SQL Server 2005, SQL Server 2008, SQL Server 2008 R2 and SQL Server 2012.
Syntax Reuse: XSLT as a Metalanguage for Knowledge Representation LanguagesTara Athan
=We present here MXSL, a subset of XSLT re-interpreted as a syntactic metalanguage for RuleML with operational semantics based on XSLT proc-essing. This metalanguage increases the expressivity of RuleML knowledge bases and queries, with syntactic access to the complete XML tree through the XPath Data Model. The metalanguage is developed in an abstract manner, as a paradigm applicable to other KR languages, in XML or in other formats.
XML Technologies for RESTful Services Developmentruyalarcon
WS-REST 2011.
Second International Workshop on RESTful Design.
Chairs: Cesare Pautasso, Erik Wilde, Rosa Alarcon.
<br>
Frameworks Session. Cornelia Davis and Tom Maguire
(Or, building better UX / Apps with distributed databases and data synchronisation techniques).
This was my talk at Cocoaheads Berlin 17th February 2016.
Integrating a Domain Ontology Development Environment and an Ontology Search ...Takeshi Morita
In order to reduce the cost of building domain ontologies manually, in this paper, we propose a method and a tool named DODDLE-OWL for domain ontology construction reusing texts and existing ontologies extracted by an ontology search engine: Swoogle. In the experimental evaluation, we applied the method to a particular field of law and evaluated the acquired ontologies.
MySQL Group Replication is a new 'synchronous', multi-master, auto-everything replication plugin for MySQL introduced with MySQL 5.7. It is the perfect tool for small 3-20 machine MySQL clusters to gain high availability and high performance. It stands for high availability because the fault of replica don't stop the cluster. Failed nodes can rejoin the cluster and new nodes can be added in a fully automatic way - no DBA intervention required. Its high performance because multiple masters process writes, not just one like with MySQL Replication. Running applications on it is simple: no read-write splitting, no fiddling with eventual consistency and stale data. The cluster offers strong consistency (generalized snapshot isolation).
It is based on Group Communication principles, hence the name.
Workshop on Semantic Statistics - Generic Multilevel Approach Designing Domai...Dr.-Ing. Thomas Hartmann
Workshop presentation: Semantic Statistics for Social, Behavioural, and Economic Sciences: Leveraging the DDI Model for the Web (12.09.2011 - 16.09.2011)
SQLPASS presentation on performance tuning and best practices for XML and XQuery in Microsoft SQL Server 2005, SQL Server 2008, SQL Server 2008 R2 and SQL Server 2012.
Syntax Reuse: XSLT as a Metalanguage for Knowledge Representation LanguagesTara Athan
=We present here MXSL, a subset of XSLT re-interpreted as a syntactic metalanguage for RuleML with operational semantics based on XSLT proc-essing. This metalanguage increases the expressivity of RuleML knowledge bases and queries, with syntactic access to the complete XML tree through the XPath Data Model. The metalanguage is developed in an abstract manner, as a paradigm applicable to other KR languages, in XML or in other formats.
XML Technologies for RESTful Services Developmentruyalarcon
WS-REST 2011.
Second International Workshop on RESTful Design.
Chairs: Cesare Pautasso, Erik Wilde, Rosa Alarcon.
<br>
Frameworks Session. Cornelia Davis and Tom Maguire
NeXML is an exchange standard for representing phyloinformatic data — inspired by the commonly used NEXUS format, but more robust and easier to process.
Doctoral Examination at the Karlsruhe Institute of Technology (08.07.2016)Dr.-Ing. Thomas Hartmann
In this thesis, a validation framework is introduced that enables to consistently execute RDF-based constraint languages on RDF data and to formulate constraints of any type. The framework reduces the representation of constraints to the absolute minimum, is based on formal logics, consists of a small lightweight vocabulary, and ensures consistency regarding validation results and enables constraint transformations for each constraint type across RDF-based constraint languages.
The formulation of constraints and the validation of RDF data against these constraints is a common requirement and a much sought-after feature, particularly as this is taken for granted in the XML world. Recently, RDF validation as a research field gained speed due to shared needs of data practitioners from a variety of domains. For constraint formulation and RDF data validation, several languages exist or are currently developed. Yet, none of the languages is able to meet all requirements raised by data professionals.
We have published a set of constraint types that are required by diverse stakeholders for data applications. We use these constraint types to gain a better understanding of the expressiveness of solutions, investigate the role that reasoning plays in practical data validation, and give directions for the further development of constraint languages.
We introduce a validation framework that enables to consistently execute RDF-based constraint languages on RDF data and to formulate constraints of any type in a way that mappings from high-level constraint languages to an intermediate generic representation can be created straight-forwardly. The framework reduces the representation of constraints to the absolute minimum, is based on formal logics, and consists of a very simple conceptual model with a small lightweight vocabulary. We demonstrate that using another layer on top of SPARQL ensures consistency regarding validation results and enables constraint transformations for each constraint type across RDF-based constraint languages.
2016.02 - Validating RDF Data Quality using Constraints to Direct the Develop...Dr.-Ing. Thomas Hartmann
For research institutes, data libraries, and data
archives, RDF data validation according to predefined constraints
is a much sought-after feature, particularly as this is taken
for granted in the XML world. Based on our work in the
DCMI RDF Application Profiles Task Group and in cooperation
with the W3C Data Shapes Working Group, we identified and
published by today 81 types of constraints that are required
by various stakeholders for data applications. In this paper,
in collaboration with several domain experts we formulate 115
constraints on three different vocabularies (DDI-RDF, QB, and
SKOS) and classify them according to (1) the severity of an
occurring violation and (2) the complexity of the constraint
expression in common constraint languages. We evaluate the
data quality of 15,694 data sets (4.26 billion triples) of research
data for the social, behavioral, and economic sciences obtained
from 33 SPARQL endpoints. Based on the results, we formulate
several findings to direct the further development of constraint
languages.
Recently, RDF validation as a research field gained speed due to common needs of data practitioners. A typical example is the library domain that co-developed and adopted Linked Data principles very early. Although, there are multiple constraint languages (having different syntaxes and semantics) which can be used to express RDF constraints such as cardinality restrictions, there is no constraint language which can be seen as the standard. The five most promising ones on being the standard are Description Set Profiles (DSP), Resource Shapes (ReSh), Shape Expressions (ShEx), the SPARQL Inferencing Notation (SPIN), and the Web Ontology Language (OWL 2). SPARQL is generally seen as the method of choice to validate RDF data according to certain constraints. We use SPIN, a SPARQL-based way to formulate and check constraints, as basis to define a validation environment (available at http://purl.org/net/rdfval-demo) to validate RDF data according to constraints expressed by arbitrary constraint languages. Additionally, the RDF Validator can be used to validate RDF data to ensure correct syntax and intended semantics of vocabularies such as Disco, Data Cube, DCAT, and SKOS. We present how to express typical RDF constraints by multiple constraint languages and how to actually validate RDF data conforming to these constraints using the RDF Validator. The workshop participants are encouraged to use the RDF Validator during this session (only an internet browser is needed) in order to express RDF constraints they need for their individual purposes.
The New Microdata Information System (MISSY) - Integration of DDI-based Data ...Dr.-Ing. Thomas Hartmann
The New Microdata Information System (MISSY) - Integration of DDI-based Data Models, an Open-Source Software Architecture, and Independent Persistence Service Implementations
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
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Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
By Design, not by Accident - Agile Venture Bolzano 2024
EDDI 2011 - A Generic Multilevel Approach for Designing Domain Ontologies Based on XML Schemas
1. A Generic Multilevel Approach for Designing
Domain Ontologies Based on XML Schemas
3rd Annual European DDI Users Group Meeting
(EDDI 2011)
06.12.2011
Thomas Bosch
M.Sc. (TUM)
postgraduate student
http://boschthomas.blogspot.com
GESIS - Leibniz Institute for the Social Sciences
2. map
XML Schema Metamodel XML Schema Metamodel
Ontology
instanceOf ⊑
External Ontologies
map
XML Schemas Generated Ontologies (OWL) Domain Ontologies (OWL)
[XSLT]
instanceOf instanceOf instanceOf
map
XML Document Instances Generated Ontologies (RDF) Domain Ontologies (RDF)
[XSLT]
2
3. map
XML Schema Metamodel XML Schema Metamodel
Ontology
instanceOf ⊑
External Ontologies
map
XML Schemas Generated Ontologies (OWL) Domain Ontologies (OWL)
[XSLT]
instanceOf instanceOf instanceOf
map
XML Document Instances Generated Ontologies (RDF) Domain Ontologies (RDF)
[XSLT]
3
5. XML
Variable
Variable: Age
VariableName
"Age"
5
6. XML Schema XML
element Variable
type name
complexType "VariableType" "Variable"
name complexContent
"VariableType" extension
sequence
element VariableName
element
name "Age"
ref
"VariableName" "VariableName"
6
7. XML Schema XML
element Variable
type name
complexType "VariableType" "Variable"
name complexContent
"VariableType" extension
sequence
element VariableName
element
name "Age"
ref
"VariableName" "VariableName"
7
8. DDI 3.1 - XML Schema | Ontology Element DDI 3.1 - XML | RDF
⊑
Variable-Element… Variable
type name
complexType "VariableType" "Variable"
name complexContent
"VariableType" extension
sequence
element VariableName
element
name "Age"
ref
"VariableName" "VariableName"
8
9. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
Variable-Element… Variable
type name
complexType "VariableType" "Variable"
name complexContent
"VariableType" extension
sequence
element VariableName
element
name "Age"
ref
"VariableName" "VariableName"
9
10. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
Variable-Element… Variable
type name_Element_String
complexType "VariableType" "Variable"
name complexContent
"VariableType" extension
sequence
element VariableName
element
name "Age"
ref
"VariableName" "VariableName"
10
11. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
Variable-Element… Variable
type name_Element_String
complexType "VariableType" "Variable"
name complexContent
"VariableType" extension
sequence
element VariableName
element
name "Age"
ref
"VariableName" "VariableName"
11
12. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
Variable-Element… Variable
type name_Element_String
complexType "VariableType" "Variable"
name complexContent
"VariableType" extension
sequence
element VariableName
element
name "Age"
ref
"VariableName" "VariableName"
12
13. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
Variable-Element… Variable
type_Element_Type name_Element_String
complexType "VariableType" "Variable"
name complexContent
"VariableType" extension
sequence
element VariableName
element
name "Age"
ref
"VariableName" "VariableName"
13
14. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
Variable-Element… Variable
type_Element_Type name_Element_String
complexType "VariableType" "Variable"
name complexContent
"VariableType" extension
sequence
element VariableName
element
name "Age"
ref
"VariableName" "VariableName"
14
15. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
type_Element_Type
VariableType-Type… Variable-Element… Variable
complexContent
extension
sequence
element element VariableName
ref name
"Age"
"VariableName" "VariableName"
15
16. ComplexType "VariableType"
DDI 3.1 - XML | RDF
⊑ name_ComplexType_String
type_Element_Type
VariableType-Type… Variable-Element… Variable
complexContent
extension
sequence
element element VariableName
ref name
"Age"
"VariableName" "VariableName"
16
17. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
type_Element_Type
VariableType-Type… Variable-Element… Variable
complexContent
extension
sequence
element element VariableName
ref name
"Age"
"VariableName" "VariableName"
17
18. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
type_Element_Type
VariableType-Type… Variable-Element… Variable
contains_ComplexType_ComplexContent
ComplexContent…
extension
sequence
element element VariableName
ref name
"Age"
"VariableName" "VariableName"
18
19. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
type_Element_Type
VariableType-Type… Variable-Element… Variable
contains_ComplexType_ComplexContent
ComplexContent…
extension
sequence
element element VariableName
ref name
"Age"
"VariableName" "VariableName"
19
20. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
type_Element_Type
VariableType-Type… Variable-Element… Variable
contains_ComplexType_ComplexContent
ComplexContent…
contains_ComplexContent_Extension
Extension…
sequence
element element VariableName
ref name
"Age"
"VariableName" "VariableName"
20
21. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
type_Element_Type
VariableType-Type… Variable-Element… Variable
contains_ComplexType_ComplexContent
ComplexContent…
contains_ComplexContent_Extension
Extension…
sequence
element element VariableName
ref name
"Age"
"VariableName" "VariableName"
21
22. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
type_Element_Type
VariableType-Type… Variable-Element… Variable
contains_ComplexType_ComplexContent
ComplexContent…
contains_ComplexContent_Extension
Extension…
contains_Extension_Sequence
Sequence…
element element VariableName
ref name
"Age"
"VariableName" "VariableName"
22
23. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
type_Element_Type
VariableType-Type… Variable-Element… Variable
contains_ComplexType_ComplexContent
ComplexContent…
contains_ComplexContent_Extension
Extension…
contains_Extension_Sequence
Sequence…
element element VariableName
ref name
"Age"
"VariableName" "VariableName"
23
24. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
type_Element_Type
VariableType-Type… Variable-Element… Variable
contains_ComplexType_ComplexContent
ComplexContent…
contains_ComplexContent_Extension
Extension…
contains_Extension_Sequence
Sequence…
contains_Sequence_Element
VariableName-Element-Reference… element VariableName
ref name
"Age"
"VariableName" "VariableName"
24
25. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
type_Element_Type
VariableType-Type… Variable-Element… Variable
contains_ComplexType_ComplexContent
ComplexContent…
contains_ComplexContent_Extension
Extension…
contains_Extension_Sequence
Sequence…
contains_Sequence_Element
VariableName-Element-Reference… element VariableName
ref name
"Age"
"VariableName" "VariableName"
25
26. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
type_Element_Type
VariableType-Type… Variable-Element… Variable
contains_ComplexType_ComplexContent
ComplexContent…
contains_ComplexContent_Extension
Extension…
contains_Extension_Sequence
Sequence…
contains_Sequence_Element
VariableName-Element-Reference… element VariableName
ref_Element_Element name
"Age"
"VariableName" "VariableName"
26
27. DDI 3.1 - XML Schema | Ontology DDI 3.1 - XML | RDF
type_Element_Type
VariableType-Type… Variable-Element… Variable
contains_ComplexType_ComplexContent
ComplexContent…
contains_ComplexContent_Extension
Extension…
contains_Extension_Sequence
Sequence…
contains_Sequence_Element
VariableName-Element-Reference… element VariableName
ref_Element_Element name
"Age"
"VariableName" "VariableName"
27
38. DDI 3.1 Ontology DDI 3.1 RDF
b a type_Element_Type b a
VariableType-Type… Variable-Element… Variable-Age
contains_ComplexType_ComplexContent
ComplexContent…
contains_ComplexContent_Extension
Extension…
contains_Extension_Sequence
Sequence…
contains_Sequence_Element
VariableName-Element-Reference… VariableName-Element…
ref_Element_Element
value_Element_String
String-Type… "Age"
38
39. DDI 3.1 Ontology DDI 3.1 RDF
b a type_Element_Type b a
VariableType-Type… Variable-Element… Variable-Age
b contains_ComplexType_ComplexContent c
c
ComplexContent…
contains_ComplexContent_Extension
Extension…
contains_Extension_Sequence
Sequence…
contains_Sequence_Element
VariableName-Element-Reference… VariableName-Element…
ref_Element_Element
value_Element_String
String-Type… "Age"
39
40. DDI 3.1 Ontology DDI 3.1 RDF
b a type_Element_Type b a
VariableType-Type… Variable-Element… Variable-Age
b contains_ComplexType_ComplexContent c
c
ComplexContent…
c contains_ComplexContent_Extension d
d
Extension…
contains_Extension_Sequence
Sequence…
contains_Sequence_Element
VariableName-Element-Reference… VariableName-Element…
ref_Element_Element
value_Element_String
String-Type… "Age"
40
41. DDI 3.1 Ontology DDI 3.1 RDF
b a type_Element_Type b a
VariableType-Type… Variable-Element… Variable-Age
b contains_ComplexType_ComplexContent c
c
ComplexContent…
c contains_ComplexContent_Extension d
d
Extension…
d contains_Extension_Sequence e
e
Sequence…
contains_Sequence_Element
VariableName-Element-Reference… VariableName-Element…
ref_Element_Element
value_Element_String
String-Type… "Age"
41
42. DDI 3.1 Ontology DDI 3.1 RDF
b a type_Element_Type b a
VariableType-Type… Variable-Element… Variable-Age
b contains_ComplexType_ComplexContent c
c
ComplexContent…
c contains_ComplexContent_Extension d
d
Extension…
d contains_Extension_Sequence e
e
Sequence…
e contains_Sequence_Element f
f
VariableName-Element-Reference… VariableName-Element…
ref_Element_Element
value_Element_String
String-Type… "Age"
42
43. DDI 3.1 Ontology DDI 3.1 RDF
b a type_Element_Type b a
VariableType-Type… Variable-Element… Variable-Age
b contains_ComplexType_ComplexContent c
c
ComplexContent…
c contains_ComplexContent_Extension d
d
Extension…
d contains_Extension_Sequence e
e
Sequence…
e contains_Sequence_Element f
f g
VariableName-Element-Reference… VariableName-Element…
f ref_Element_Element g
value_Element_String
String-Type… "Age"
43
44. DDI 3.1 Ontology DDI 3.1 RDF
b a type_Element_Type b a
VariableType-Type… Variable-Element… Variable-Age
b contains_ComplexType_ComplexContent c
c
ComplexContent…
c contains_ComplexContent_Extension d
d
Extension…
d contains_Extension_Sequence e
e
Sequence…
e contains_Sequence_Element f
f g
VariableName-Element-Reference… VariableName-Element… VariableName-Element… ( g )
f ref_Element_Element g
value_Element_String
String-Type… "Age"
44
45. DDI 3.1 Ontology DDI 3.1 RDF
b a type_Element_Type b a
VariableType-Type… Variable-Element… Variable-Age
b contains_ComplexType_ComplexContent c
c
ComplexContent…
c contains_ComplexContent_Extension d
d
Extension…
d contains_Extension_Sequence e
e
Sequence…
e contains_Sequence_Element f
f g
VariableName-Element-Reference… VariableName-Element… VariableName-Element… ( g )
f ref_Element_Element g
g value_Element_String h
h
String-Type… "Age"
45
46. DDI 3.1 Ontology DDI 3.1 RDF
b a type_Element_Type b a
VariableType-Type… Variable-Element… Variable-Age
b contains_ComplexType_ComplexContent c
c
ComplexContent…
c contains_ComplexContent_Extension d
d
Extension… a hasVariableName h
d contains_Extension_Sequence e
e
Sequence…
e contains_Sequence_Element f
f g
VariableName-Element-Reference… VariableName-Element… VariableName-Element… ( g )
f ref_Element_Element g
g value_Element_String h
h
String-Type… "Age"
46
47. DDI 3.1 Ontology DDI 3.1 RDF
b a type_Element_Type b a
VariableType-Type… Variable-Element… Variable-Age
b contains_ComplexType_ComplexContent c
c
ComplexContent…
c contains_ComplexContent_Extension d
d
Extension… a hasVariableName h
d contains_Extension_Sequence e
e
Sequence… --> Variable-Age hasVariabeName "Age"
e contains_Sequence_Element f
f g
VariableName-Element-Reference… VariableName-Element… VariableName-Element… ( g )
f ref_Element_Element g
g value_Element_String h
h
String-Type… "Age"
47
48. DDI 3.1 Ontology DDI 3.1 RDF
b a type_Element_Type b a
VariableType-Type… Variable-Element… Variable-Age
b contains_ComplexType_ComplexContent c
c Variable ( a )
ComplexContent… Variable
c contains_ComplexContent_Extension d
d
Extension… a hasVariableName h
d contains_Extension_Sequence e
e
Sequence…
e contains_Sequence_Element f
f g
VariableName-Element-Reference… VariableName-Element… VariableName-Element… ( g )
f ref_Element_Element g
g value_Element_String h
h
String-Type… "Age"
48
49. DDI 3.1 Ontology DDI 3.1 RDF
b a type_Element_Type b a
VariableType-Type… Variable-Element… Variable-Age
b contains_ComplexType_ComplexContent c
c Variable ( a )
ComplexContent… Variable
--> Variable ( Variable-Age )
c contains_ComplexContent_Extension d
d
Extension… a hasVariableName h
d contains_Extension_Sequence e
e
Sequence…
e contains_Sequence_Element f
f g
VariableName-Element-Reference… VariableName-Element… VariableName-Element… ( g )
f ref_Element_Element g
g value_Element_String h
h
String-Type… "Age"
49