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
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
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.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
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.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
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!
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
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