This document discusses the process of ontology design 101. It explains that the key steps are to determine the domain and focus of the ontology, consider reusing existing ontologies, enumerate the important terms and concepts, and define the classes, properties, and constraints. An example ontology about wine and food pairings is used to illustrate these steps. The document emphasizes that ontology design is an iterative process without a single correct approach.
Este documento ofrece información sobre varios planes de viaje que incluyen visitas a los glaciares argentinos, el Tren de las Nubes en Argentina y Europa, además de recomendar los mejores hoteles. Los planes incluyen visa, pasaporte, tiquetes aéreos, seguro médico, pago de aduanas, alimentación y alojamiento.
Агрессивный по отношению к личности и обществу характер новых религиозных движений стал причиной столь пристального к ним внимания со стороны светской власти и ее институтов (полиции, суда и т.п.). Как отмечают авторы "Рапорта Коттрелла" - первого наиболее полного и важного документа, посвященного последствиям деятельности новых религиозных движений, - в их намерения не входило "оценивать притязаний на истинность того или иного верования", поскольку такие верования "являются делом личного выбора и не могут быть объектом вмешательства общественной власти". Авторы рапорта хотели лишь изучить те последствия, "которые имеет для общества принадлежность одного из его членов к новому религиозному движению". Авторы документа приходят к выводу, что практически все эти движения и связанные с ними организации "достаточно спорны и подозрительны. Говоря так, - пишут авторы рапорта, - мы имеем ввиду обвинения в совершении налоговых и других преступлений, распространяемой ими лжи; об отчаянии, в которое впадают семьи людей, присоединившихся к этим движениям, а также те нарушения, которые они провоцируют в психике своих адептов".
The document discusses named entity recognition, which involves locating and classifying atomic elements like names, organizations, locations, quantities, and times into predefined categories. It provides examples of entity mapping candidates for the string "Armstrong" and discusses how context, ambiguity, and accuracy are used to select the correct entity. It also discusses using semantic graphs and linked data to analyze entities and help with the selection process.
The document discusses semantic search and how it can improve on traditional keyword-based search. It describes how semantic search can extend and refine search queries using ontologies and semantic metadata. This allows for more precise and complete search results. Semantic search also enables cross-referencing related information, exploratory search through semantic navigation, and reasoning over semantic data to infer implicit facts.
The document describes t-shirts for Niemann Pick disease fundraising. The front of one shirt says "Niemann Pick, It's A Race" and the back says they need help finding a cure. The second shirt lists the birth and death dates of Faith Robbins who had the disease.
Este documento ofrece información sobre varios planes de viaje que incluyen visitas a los glaciares argentinos, el Tren de las Nubes en Argentina y Europa, además de recomendar los mejores hoteles. Los planes incluyen visa, pasaporte, tiquetes aéreos, seguro médico, pago de aduanas, alimentación y alojamiento.
Агрессивный по отношению к личности и обществу характер новых религиозных движений стал причиной столь пристального к ним внимания со стороны светской власти и ее институтов (полиции, суда и т.п.). Как отмечают авторы "Рапорта Коттрелла" - первого наиболее полного и важного документа, посвященного последствиям деятельности новых религиозных движений, - в их намерения не входило "оценивать притязаний на истинность того или иного верования", поскольку такие верования "являются делом личного выбора и не могут быть объектом вмешательства общественной власти". Авторы рапорта хотели лишь изучить те последствия, "которые имеет для общества принадлежность одного из его членов к новому религиозному движению". Авторы документа приходят к выводу, что практически все эти движения и связанные с ними организации "достаточно спорны и подозрительны. Говоря так, - пишут авторы рапорта, - мы имеем ввиду обвинения в совершении налоговых и других преступлений, распространяемой ими лжи; об отчаянии, в которое впадают семьи людей, присоединившихся к этим движениям, а также те нарушения, которые они провоцируют в психике своих адептов".
The document discusses named entity recognition, which involves locating and classifying atomic elements like names, organizations, locations, quantities, and times into predefined categories. It provides examples of entity mapping candidates for the string "Armstrong" and discusses how context, ambiguity, and accuracy are used to select the correct entity. It also discusses using semantic graphs and linked data to analyze entities and help with the selection process.
The document discusses semantic search and how it can improve on traditional keyword-based search. It describes how semantic search can extend and refine search queries using ontologies and semantic metadata. This allows for more precise and complete search results. Semantic search also enables cross-referencing related information, exploratory search through semantic navigation, and reasoning over semantic data to infer implicit facts.
The document describes t-shirts for Niemann Pick disease fundraising. The front of one shirt says "Niemann Pick, It's A Race" and the back says they need help finding a cure. The second shirt lists the birth and death dates of Faith Robbins who had the disease.
This document discusses ontology design and development. It describes the ontology development process, which includes pre-development, development, and post-development activities. Development activities involve specification, conceptualization, formalization, and implementation. The document also outlines methodologies for ontology design, which guide the construction of consistent ontologies through management, development-oriented, and support activities. These activities work together to efficiently develop complex ontologies.
The document describes the key components and processes involved in building a data warehousing and business intelligence capability. It involves extracting, transforming, and loading data from operational systems into data repositories and a data warehouse. From there, data is organized into data marts and analytics are performed on the data through online analytical processing, data mining, reporting, and visualization to provide insights. A meta-data repository tracks and manages the movement and transformation of data throughout the process.
The document discusses exploratory semantic search using linked open data. It describes how a user could browse related entities in a knowledge graph starting from a book, following links to the author, other authors influenced by or influencing the first author, and their notable works. This allows the user to serendipitously discover related information without having to formulate a precise search query. The document also provides examples of exploring topics like space flights and accidents. Finally, it mentions exploratory search tools that augment video search using linked open data.
This document provides an overview of the mobile value added services (VAS) market in India. It estimates the current size of the Indian mobile VAS market to be Rs. 2850 crore growing at 60% annually to reach Rs. 4560 crore by the end of 2007. The market is currently dominated by entertainment services such as P2P SMS, ringtones, games, and music. Factors driving the growth of the VAS market include India's growing economy, increased comfort with mobile phones, personalization of devices, and lower mobile call rates. The document also discusses the revenue sharing model and outlines some challenges and future opportunities for the VAS sector in India.
The document discusses creating and using ontologies. It defines an ontology as a representation of things in a domain, their characteristics and relationships. Ontologies are used to share a common understanding of a domain among people and machines. They make domain assumptions and knowledge explicit and separate domain knowledge from operational knowledge. The document provides an overview of the ontology development process including requirements analysis, conceptualization, and implementation. It discusses finding existing ontologies and provides examples of competency questions for requirements analysis.
1) Ontology technology can help integrate big data by annotating labels from different databases with terms from common controlled vocabularies, providing benefits for search, integration, and potential reasoning.
2) However, this approach often fails because it is easy to create many incompatible ontologies in siloed ways, undermining semantic integration goals.
3) For ontologies to succeed, we need an incremental process where good ontologies survive and spread, and people are incentivized to reuse high-quality, tested ontologies rather than creating new ones.
The document discusses methods for evaluating ontologies. It proposes developing objective metrics to evaluate ontologies based on three criteria: correctness, completeness, and utility. Correctness evaluates how well an ontology expresses its design objectives. Completeness evaluates how fully an ontology captures required semantic components. Utility combines correctness and completeness and evaluates an ontology's usefulness for its intended use case. Examples are provided to illustrate evaluating ontologies based on the proposed metrics. The goal is to develop standardized evaluation methods to facilitate ontology development and reuse across different domains.
Ontology Engineering for the Semantic Web and beyondPeter Geil
This document provides an overview of ontology engineering and developing ontologies. It discusses what an ontology is, why develop ontologies, and provides a step-by-step process for developing an ontology about wines and wineries. Some key aspects covered include determining the domain and scope, reusing existing ontologies, defining classes and class hierarchies, defining properties and constraints of classes, and creating instances. Common problems in ontology engineering like multiple inheritance and disjoint classes are also discussed.
= Finding a Good Ontology: The Open Ontology Repository Initiative =
Can you find a good ontology to use or extend for your application?
Building on previous registry and repository efforts, the Open Ontology Repository Initiative is a community effort developing open source software for finding, using, and maintaining open source and other ontologies.
The initial implementation of OOR is based on BioPortal (http://bioportal.bioontology.org), which is used to access and share ontologies that are actively used in biomedical communities and currently supports OWL, OBO, and Protege ontologies, LexGrid and RRF vocabularies, and ontology mapping. BioPortal has been developed by the National Center for Biomedical Ontology with support from the NIH Roadmap, but its infrastructure is domain-independent and being extended in various directions.
This presentation will include the following:
* A demonstration of the current public OOR instance
* OOR requirements and challenges
* On-going and planned development efforts (Common Logic support, federation, gatekeeping, provenance, governance, etc.)
* Details on how you can become involved
it's our presentation during the third international conference of information systems and technologies ICIST 2013 held at Tangier, Morocco in which we propose a new approach for human assessment of ontologies using an online questionnaire.
A breakout discussion led by David Klatte at the Pistoia Alliance Information Ecosystem Workshop proposed a number of potential projects. The workshop was held in October 2011.
ESWC SS 2012 - Tuesday Tutorial Elena Simperl: Creating and Using Ontologieseswcsummerschool
Here are the steps I would suggest for aligning the ontologies:
1. Representatives present their ontology and explain key concepts and relationships.
2. Editor records all concepts and relationships on a whiteboard in a concept map format without evaluation.
3. Representatives discuss each concept and relationship to reach agreement on meaning and resolve any conflicts or ambiguities.
4. Editor incorporates agreed upon concepts and relationships into a single ontology, resolving any structural issues.
5. Representatives review the aligned ontology and provide feedback.
6. Editor incorporates final changes to produce the aligned ontology for use by all groups.
The goal is to understand each perspective, identify areas of overlap and conflict, and work together iteratively
This document discusses the goals and activities of the Wf4Ever project, which aims to preserve scientific workflows and enable their efficient retrieval and reuse. The project will develop technological infrastructure for archiving, classifying, indexing and providing access to workflows and related materials across multiple disciplines. Key goals include enabling reproducibility, repeatability, and collaboration around scientific experiments. The document outlines considerations for preserving workflows, and provides an update on the Wf4Ever architecture and development of user tools to facilitate contribution and reuse of research objects.
This document discusses knowledge engineering and the use of knowledge on the web. It covers web data representation using standards like RDF, HTML5 and SKOS. It discusses categorizing knowledge from different sources and aligning categories. It also discusses using knowledge through techniques like visualization, graph-based search across linked data, and improving search through vocabulary alignment and location-based queries.
This document discusses research objects as a framework for facilitating the exchange and reuse of digital knowledge. Research objects are defined as semantically rich aggregations of resources that support a research objective. They allow for workflows, data, documents and other resources to be bundled together and shared. The document outlines several motivating projects, challenges in developing research object models and vocabularies, and a vision for how research objects could allow research to be more efficient, effective and ethical through increased reuse of digital knowledge.
1) The document presents a new ontology-based question answering method using query templates for the dining domain.
2) A dining ontology is developed to represent concepts like cuisine, facilities, meals, and their relationships.
3) Query templates are generated from the dining ontology and stored to enable faster retrieval of answers from the ontology compared to using SPARQL queries. This improves reusability.
This document discusses ontology design and development. It describes the ontology development process, which includes pre-development, development, and post-development activities. Development activities involve specification, conceptualization, formalization, and implementation. The document also outlines methodologies for ontology design, which guide the construction of consistent ontologies through management, development-oriented, and support activities. These activities work together to efficiently develop complex ontologies.
The document describes the key components and processes involved in building a data warehousing and business intelligence capability. It involves extracting, transforming, and loading data from operational systems into data repositories and a data warehouse. From there, data is organized into data marts and analytics are performed on the data through online analytical processing, data mining, reporting, and visualization to provide insights. A meta-data repository tracks and manages the movement and transformation of data throughout the process.
The document discusses exploratory semantic search using linked open data. It describes how a user could browse related entities in a knowledge graph starting from a book, following links to the author, other authors influenced by or influencing the first author, and their notable works. This allows the user to serendipitously discover related information without having to formulate a precise search query. The document also provides examples of exploring topics like space flights and accidents. Finally, it mentions exploratory search tools that augment video search using linked open data.
This document provides an overview of the mobile value added services (VAS) market in India. It estimates the current size of the Indian mobile VAS market to be Rs. 2850 crore growing at 60% annually to reach Rs. 4560 crore by the end of 2007. The market is currently dominated by entertainment services such as P2P SMS, ringtones, games, and music. Factors driving the growth of the VAS market include India's growing economy, increased comfort with mobile phones, personalization of devices, and lower mobile call rates. The document also discusses the revenue sharing model and outlines some challenges and future opportunities for the VAS sector in India.
The document discusses creating and using ontologies. It defines an ontology as a representation of things in a domain, their characteristics and relationships. Ontologies are used to share a common understanding of a domain among people and machines. They make domain assumptions and knowledge explicit and separate domain knowledge from operational knowledge. The document provides an overview of the ontology development process including requirements analysis, conceptualization, and implementation. It discusses finding existing ontologies and provides examples of competency questions for requirements analysis.
1) Ontology technology can help integrate big data by annotating labels from different databases with terms from common controlled vocabularies, providing benefits for search, integration, and potential reasoning.
2) However, this approach often fails because it is easy to create many incompatible ontologies in siloed ways, undermining semantic integration goals.
3) For ontologies to succeed, we need an incremental process where good ontologies survive and spread, and people are incentivized to reuse high-quality, tested ontologies rather than creating new ones.
The document discusses methods for evaluating ontologies. It proposes developing objective metrics to evaluate ontologies based on three criteria: correctness, completeness, and utility. Correctness evaluates how well an ontology expresses its design objectives. Completeness evaluates how fully an ontology captures required semantic components. Utility combines correctness and completeness and evaluates an ontology's usefulness for its intended use case. Examples are provided to illustrate evaluating ontologies based on the proposed metrics. The goal is to develop standardized evaluation methods to facilitate ontology development and reuse across different domains.
Ontology Engineering for the Semantic Web and beyondPeter Geil
This document provides an overview of ontology engineering and developing ontologies. It discusses what an ontology is, why develop ontologies, and provides a step-by-step process for developing an ontology about wines and wineries. Some key aspects covered include determining the domain and scope, reusing existing ontologies, defining classes and class hierarchies, defining properties and constraints of classes, and creating instances. Common problems in ontology engineering like multiple inheritance and disjoint classes are also discussed.
= Finding a Good Ontology: The Open Ontology Repository Initiative =
Can you find a good ontology to use or extend for your application?
Building on previous registry and repository efforts, the Open Ontology Repository Initiative is a community effort developing open source software for finding, using, and maintaining open source and other ontologies.
The initial implementation of OOR is based on BioPortal (http://bioportal.bioontology.org), which is used to access and share ontologies that are actively used in biomedical communities and currently supports OWL, OBO, and Protege ontologies, LexGrid and RRF vocabularies, and ontology mapping. BioPortal has been developed by the National Center for Biomedical Ontology with support from the NIH Roadmap, but its infrastructure is domain-independent and being extended in various directions.
This presentation will include the following:
* A demonstration of the current public OOR instance
* OOR requirements and challenges
* On-going and planned development efforts (Common Logic support, federation, gatekeeping, provenance, governance, etc.)
* Details on how you can become involved
it's our presentation during the third international conference of information systems and technologies ICIST 2013 held at Tangier, Morocco in which we propose a new approach for human assessment of ontologies using an online questionnaire.
A breakout discussion led by David Klatte at the Pistoia Alliance Information Ecosystem Workshop proposed a number of potential projects. The workshop was held in October 2011.
ESWC SS 2012 - Tuesday Tutorial Elena Simperl: Creating and Using Ontologieseswcsummerschool
Here are the steps I would suggest for aligning the ontologies:
1. Representatives present their ontology and explain key concepts and relationships.
2. Editor records all concepts and relationships on a whiteboard in a concept map format without evaluation.
3. Representatives discuss each concept and relationship to reach agreement on meaning and resolve any conflicts or ambiguities.
4. Editor incorporates agreed upon concepts and relationships into a single ontology, resolving any structural issues.
5. Representatives review the aligned ontology and provide feedback.
6. Editor incorporates final changes to produce the aligned ontology for use by all groups.
The goal is to understand each perspective, identify areas of overlap and conflict, and work together iteratively
This document discusses the goals and activities of the Wf4Ever project, which aims to preserve scientific workflows and enable their efficient retrieval and reuse. The project will develop technological infrastructure for archiving, classifying, indexing and providing access to workflows and related materials across multiple disciplines. Key goals include enabling reproducibility, repeatability, and collaboration around scientific experiments. The document outlines considerations for preserving workflows, and provides an update on the Wf4Ever architecture and development of user tools to facilitate contribution and reuse of research objects.
This document discusses knowledge engineering and the use of knowledge on the web. It covers web data representation using standards like RDF, HTML5 and SKOS. It discusses categorizing knowledge from different sources and aligning categories. It also discusses using knowledge through techniques like visualization, graph-based search across linked data, and improving search through vocabulary alignment and location-based queries.
This document discusses research objects as a framework for facilitating the exchange and reuse of digital knowledge. Research objects are defined as semantically rich aggregations of resources that support a research objective. They allow for workflows, data, documents and other resources to be bundled together and shared. The document outlines several motivating projects, challenges in developing research object models and vocabularies, and a vision for how research objects could allow research to be more efficient, effective and ethical through increased reuse of digital knowledge.
1) The document presents a new ontology-based question answering method using query templates for the dining domain.
2) A dining ontology is developed to represent concepts like cuisine, facilities, meals, and their relationships.
3) Query templates are generated from the dining ontology and stored to enable faster retrieval of answers from the ontology compared to using SPARQL queries. This improves reusability.
This tutorial tries to answer the following questions:
What is the best practice for ontology reuse?
Is it fine to use external ontology entities to model my local entities?
Should I import the ontologies that I reuse?
What if I only need a part of an ontology?
What if an external ontology that I reused, changes?
Ontology Maturing for Searching, Managing, and Retrieving ResourcesSimone Braun
presentation of the paper "Using the Ontology Maturing Proces Model for Searching, Managing, and Retrieving Resources with Semantic Technologies" at the ODBASE 2008 conference, Monterrey, Mexico, Nov 13 2008
This is a plain english overview of the Sensemaker software developed by Cognitive Edge, put together by Emerging Options Pty Ltd (http://www.emergingoptions.com.au). It is a leading edge product allowing organisations to make sense of their world in order to make decisions in a time of rapid and constant change. It makes the invisible voice visible.
1. Semantic Web
Technologies
Lecture 6: Applications in the Web of Data
03: Ontology Design 101
Dr. Harald Sack
Hasso Plattner Institute for IT Systems Engineering
University of Potsdam
Spring 2013
This file is licensed under the Creative Commons Attribution-NonCommercial 3.0 (CC BY-NC 3.0)
2. 2
Lecture 6: Applications in the Web of Data
Open HPI - Course: Semantic Web Technologies
Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
3. 3
03 - Ontology Design 101
Open HPI - Course: Semantic Web Technologies - Lecture 6: Applications in the Web of Data
Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
4. (Noy, McGuinness, 2000)
Ontology Development 101
•Example of a wine and food ontology
4
Which wine is the right one for fish?
French wine-growing
regions and wines
A shared
ontology on
wine and food
Californian
wine-growing regions
and wines
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
5. (Noy, McGuinness, 2000)
Ontology Development 101
•Example of a wine and food ontology
5
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
6. The Ontology Development 101 Process
determine consider enumerate define define define create
scope reuse terms classes properties constraints instances
6
•in practice an iterative process that repeats continuously and
improves the ontology
•there are always different approaches for modelling an
ontology
•in practice the designated application decides about the
modelling approach
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
7. The Ontology Development 101 Process
determine consider enumerate define define define create
scope reuse terms classes properties constraints instances
6
•in practice an iterative process that repeats continuously and
improves the ontology
•there are always different approaches for modelling an
ontology
•in practice the designated application decides about the
modelling approach
„There is no one cor
rect way to
model a domain.
There are always vi
able alternativ es.“
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
8. Determine Domain and Focus
determine consider enumerate define define define create
scope reuse terms classes properties constraints instances
7
•Which domain should be covered by the ontology?
•What should the ontology be used for?
•What types of questions should be answered by the
knowledge represented in the ontology?
•Who will use and maintain the ontology?
•Formulation of competence questions
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
9. Determine Domain and Focus
determine consider enumerate define define define create
scope reuse terms classes properties constraints instances
7
•Which domain should be covered by the ontology?
•What should the ontology be used for?
•What types of questions should be answered by the
knowledge represented in the ontology?
•Who will use and maintain the ontology?
•Formulation of competence questions
These Questions migh
t change
within the ontology
life cycle
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
10. Determine Domain and Focus
determine consider enumerate define define define create
scope reuse terms classes properties constraints instances
8
Competence Questions (Wine Ontology)
•Which properties of the wine should be considered for modelling?
•Is Bordeaux a white wine or a red wine?
•Does a Sauvignon Blanc match with fish?
•Which wine matches best for grilled meat?
•Which properties of a wine do influence whether it matches with a
specific dish?
•Does the bouquet of a wine change with different vintages?
•...
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
11. Consider Reuse
determine consider enumerate define define define create
scope reuse terms classes properties constraints instances
9
•Why should we consider reuse?
•in order to save cost
•in order to apply tools that are applied for other existing
ontologies also for our own ontology
•in order to reuse ontologies that have been validated by their
application
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
12. Consider Reuse
determine consider enumerate define define define create
scope reuse terms classes properties constraints instances
9
•Why should we consider reuse?
•in order to save cost
•in order to apply tools that are applied for other existing
ontologies also for our own ontology
•in order to reuse ontologies that have been validated by their
application
If you don‘t f
ind a suitabl
adaption is t e ontology or
oo complex th if the
en create a n
ew ontology!
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
13. Develop a Terminology
determine consider enumerate define define define create
scope reuse terms classes properties constraints instances
10
•About which concepts are we talking?
•What do we want to say about these concepts?
•Which properties do these concepts have?
Example: Wine Ontology
•wine, grape, winery, location,...
•a wine‘s color, body, flavor, sugar content,...
•subtypes of wine: white wine, red wine, Bordeaux wine,...
•types of food: seafood, fish, meat, vegetables, cheese,...
•...
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
14. Develop Classes and Class Hierarchies
determine consider enumerate define define define create
scope reuse terms classes properties constraints instances
11
•Classes are concepts in the designated domain
•class of wines
•class of wineries
•class of red wines
•...
•Classes are collections of objects with similar properties
•Choose an approach to model class hierarchies
•top-down:
start with most general concept with subsequent specialization
•bottom-up:
start with most specific concepts with subsequent grouping into
more general concepts
•middle-out:
start with most imnportant concepts with subsequent
specialization and generalization
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
15. Define Properties
determine consider enumerate define define define create
scope reuse terms classes properties constraints instances
12
•Properties in a class definition describe attributes of instances
•every wine has a color, residual sugar, producer, etc...
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
16. Define Property Constraints
determine consider enumerate define define define create
scope reuse terms classes properties constraints instances
13
•Property constraints (restrictions) describe or restrict the set of
possible property values
•The name of a wine is a string
•The producer is an instance of winemaker
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
17. Definition of Individuals
determine consider enumerate define define define create
scope reuse terms classes properties constraints instances
14
•Create individuals populating the classes
•every class directly becomes the type of its individuals
•every superclass of a type is also a type of its individuals
•Create instances for properties, i.e. assignment of property
values for the individuals according to the given constraints
•„the glass of red wine that I drank last supper...“
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
18. The Ontology Development 101 Process
determine consider enumerate define define define create
scope reuse terms classes properties constraints instances
15
•in practice an iterative Process that repeats continuously
and improves the ontology
•Attention:
•Further refinement should include the formulation of axioms
•Not well suited for large scale industrial ontology engineering
•version control, evaluation, quality assurance, etc.
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
19. The Ontology Development 101 Process
determine consider enumerate define define define create
scope reuse terms classes properties constraints instances
15
•in practice an iterative Process that repeats continuously
and improves the ontology
•Attention:
•Further refinement should include the formulation of axioms
•Not well suited for large scale industrial ontology engineering
•version control, evaluation, quality assurance, etc.
„There is no one cor
rect way to
model a domain.
There are always vi
able alternativ es.“
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
20. 16
Further Ontology Design Methodologies
Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
21. Unified Process for Ontology Building De Nicola, Missikoff, Navigli (2005)
17
•Based on Unified Process (UP) methodology in software
development and Unified Modelling Language (UML)
•Use-Case driven, i.e. more suitable for application ontologies
than for domain ontologies
•Goals:
•Reduction of time and cost in the development of large scale
ontologies
•Quality improvement of the developed ontology via progressive
validation of intermediate results
•Methodology for efficient collaboration of knowledge engineers
and domain experts with clear separation of roles
•Intermediate results can already be evaluated by the user
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
22. Unified Process for Ontology Building De Nicola, Missikoff, Navigli
(2005)
•Development is divided into cycles, which are subdivided into
4 phases of iterations (Inception, Elaboration, Construction,
18 Transition). Each iteration results in a new prototype.
•Each iteration consists of 5 workflows (Requirements, Analysis,
Design, Implementation, Test)
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
23. Unified Process for Ontology Building De Nicola, Missikoff, Navigli (2005)
•Workflows and phases are almost orthogonal, i.e. involvement
of single workflows in different phases of ontology
19 development does vary
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
24. Ontology Design Patterns (Gangemi et al., 2005)
•Adapting an idea originally from architecture
•recurring modeling problems
20
•providing a set of adaptable standard solutions
•Ontology Design Patterns provide
•small reusable (abstract) ontology templates with explicit
documentation
•searchable repository ordered by competence questions
http://ontologydesignpatterns.org/
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
25. Ontology Design Patterns - A Simple Example
•Example: taking over a temporary role
21
•e.g.: Basil Rathbone played Sherlock Holmes in the 1939 movie
„The Hound of the Baskervilles“
•Analyze the sentence, detect the modeling issues, and match to
the Content ODPs
•A person •represent objects and
plays a character
the roles they play
Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam http://ontologydesignpatterns.org/
26. 03 - Ontology Design 101
22
Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam
27. 23
04 - Linked Data Engineering
Open HPI - Course: Semantic Web Technologies - Lecture 6: Applications in the Web of Data
Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam