• 05 Apr 17
  

  ellenm1

  semantic_web

• 16 Nov 16
  

  Anoushka Ferrari

  "Ontology Development 101: A Guide to Creating Your First Ontology"

  ontology ontologies tutorial model' Domain Driven Design

• 

  anoushkaferrari

  ontology ontologies tutorial model' Domain Driven Design

• 17 Oct 16
  

  sarashadmani

  ontology protege owl

• 03 Oct 16
  

  pleiadian53
  • an ontology is a formal explicit description of concepts in a domain of discourse (classes (sometimes called concepts)), properties of each concept describing various features and attributes of the concept (slots (sometimes called roles or properties)), and restrictions on slots (facets (sometimes called role restrictions)). An ontology together with a set of individual instances of classes constitutes a knowledge base.
• 11 Mar 16
  

  io_cicero

  sowa ontology

  • an ontology is a formal explicit description of concepts in a domain of discourse (classes (sometimes called concepts)
  • properties of each concept describing various features and attributes of the concept (slots (sometimes called roles or properties))
  • , and restrictions on slots (facets (sometimes called role restrictions))
  • An ontology together with a set of individual instances of classes constitutes a knowledge base. In reality, there is a fine line where the ontology ends and the knowledge base begins.
  • es are the focus of most ontologies. Classes describe concepts in the domain. For example, a class of wines represents all wines. Specific wines are instances of this class. The Bordeaux wine in the glass in front of you while you read this document is an instance of  the class of Bordeaux wines. A class can have subclasses that represent concepts that are more specific than the superclass. For example, we can divide the class of all wines into red, white, and ros� wines. Alternatively, we can divide a class of all wines into sparkling and non-sparkling w

  • ctical terms, developing an ontology includes:

      

    �         defining classes in the ontology,
  •    arranging the classes in a taxonomic (subclass–superclass) hierarchy
  •   defining slots and describing allowed values for these slots,

  • ing in the values for slots for instances.

      

    We can then create a knowledge base by defining individual instances of these classes filling in specific slot value information and additional slot restrictions.
  •    Ontology  development is necessarily an iterative proces
  •     Concepts  in the ontology should be close to objects (physical or logical) and relationships in your  domain of interest. These are most likely to be nouns (objects) or verbs (relationships)  in sentences that describe your domain.
  • 4.1         Ensuring that the class hierarchy is correct

  • An “is-a” relation

     

    The class hierarchy represents an “is-a” relation: a class A is  a subclass of B if every instance of B is also an instance of A

  • ansitivity of the hierarchical relations

     

    A subclass relationship is transitive:

     

    If B is a subclass of A and C is a  subclass of B, then C is a subclass of A

  •         Limiting  the scope

     

    As a final note on defining a class hierarchy, the following set of rules  is always helpful in deciding when an ontology definition is complete:

     

    The ontology should not contain all the possible information about the  domain: you do not need to specialize (or generalize) more than you need for your  application (at most one extra level each

  • .8        Disjoint  subclasses

     

    Many systems allow us to specify explicitly that several classes are disjoint. Classes are disjoint if they cannot have  any instances in common.

  • 8          Conclusions

    In this guide, we have described an ontology-development methodology for  declarative frame-based systems

  • Acknowledgments

    Prot�g�-2000 (http://protege.stanford.edu)  was developed by Mark Musen’s group at Stanford Medical Informatics. W

  16 more annotations...

• 26 Dec 15
  

  "Ontologies: Principles, Methods and Applications. "
  
  Noy, N. F., & McGuinness, D. L. (2001). Ontology development 101: A guide to creating your first ontology.

  • explicit formal specifications of the terms in the domain and relations among them (Gruber 1993)—has been moving from the realm of Artificial-Intelligence laboratories to the desktops of domain experts.
  • The ontologies on the Web range from large taxonomies categorizing Web sites (such as on Yahoo!) to categorizations of products for sale and their features (such as on Amazon.com). The WWW Consortium (W3C) is developing the Resource Description Framework (Brickley and Guha 1999), a language for encoding knowledge on Web pages to make it understandable to electronic agents searching for information.  The Defense Advanced Research Projects Agency (DARPA), in conjunction with the W3C, is developing DARPA Agent Markup Language (DAML) by extending RDF with more expressive constructs aimed at facilitating agent interaction on the Web (Hendler and McGuinness 2000).
  • Many disciplines now develop standardized ontologies that domain experts can use to share and annotate information in their fields. Medicine, for example, has produced large, standardized, structured vocabularies such as snomed (Price and Spackman 2000) and the semantic network of the Unified Medical Language System (Humphreys and Lindberg 1993).

  • �         To share common understanding of the structure of information among people or software agents

      

    �         To enable reuse of domain knowledge

      

    �         To make domain assumptions explicit

      

    �         To separate domain knowledge from the operational knowledge

      

    �         To analyze domain knowledge
  • Broad general-purpose ontologies are emerging as well. For example,  the United Nations Development Program and Dun & Bradstreet combined their efforts to develop the UNSPSC ontology which provides terminology for products and services (www.unspsc.org)
  • An ontology defines a common vocabulary for researchers who need to share information in a domain. It includes machine-interpretable definitions of basic concepts in the domain and relations among them.
  • For example, suppose several different Web sites contain medical information or provide medical e-commerce services. If these Web sites share and publish the same underlying ontology of the terms they all use, then computer agents can extract and aggregate information from these different sites. The agents can use this aggregated information to answer user queries or as input data to other applications.
  • Enabling reuse of domain knowledge was one of the driving forces behind recent surge in ontology research. For example, models for many different domains need to represent the notion of time. This representation includes the notions of time intervals, points in time, relative measures of time, and so on. If one group of researchers develops such an ontology in detail, others can simply reuse it for their domains. Additionally, if we need to build a large ontology, we can integrate several existing ontologies describing portions of the large domain. We can also reuse a general ontology, such as the UNSPSC ontology, and extend it to describe our domain of interest.
  • Making explicit domain assumptions underlying an implementation makes it possible to change these assumptions easily if our knowledge about the domain changes. Hard-coding assumptions about the world in programming-language code makes these assumptions not only hard to find and understand but also hard to change, in particular for someone without programming expertise. In addition, explicit specifications of domain knowledge are useful for new users who must learn what terms in the domain mean
  • Separating the domain knowledge from the operational knowledge is another common use of ontologies. We can describe a task of configuring a product from its components according to a required specification and implement a program that does this configuration independent of the products and components themselves
  • Analyzing domain knowledge is possible once a declarative specification of the terms is available.  Formal analysis of terms is extremely valuable when both attempting to reuse existing ontologies and extending them (McGuinness et al. 2000)
  • Often an ontology of the domain is not a goal in itself. Developing an ontology is akin to defining a set of data and their structure for other programs to use. Problem-solving methods, domain-independent applications, and software agents use ontologies and knowledge bases built from ontologies as data.
  • For example, in this paper we develop an ontology of wine and food and appropriate combinations of wine with meals. This ontology can then be used as a basis for some applications in a suite of restaurant-managing tools:
  • One application could create wine suggestions for the menu of the day or answer queries of waiters and customers. Another application could analyze an inventory list of a wine cellar and suggest which wine categories to expand and which particular wines to purchase for upcoming menus or cookbooks.
  • The Artificial-Intelligence literature contains many definitions of an ontology; many of these contradict one another. For the purposes of this guide an ontology is a formal explicit description of concepts in a domain of discourse (classes (sometimes called concepts)), properties of each concept describing various features and attributes of the concept (slots (sometimes called roles or properties)), and restrictions on slots (facets (sometimes called role restrictions)). An ontology together with a set of individual instances of classes constitutes a knowledge base. In reality, there is a fine line where the ontology ends and the knowledge base begins.
  • Classes describe concepts in the domain. For example, a class of wines represents all wines. Specific wines are instances of this class. The Bordeaux wine in the glass in front of you while you read this document is an instance of  the class of Bordeaux wines. A class can have subclasses that represent concepts that are more specific than the superclass. For example, we can divide the class of all wines into red, white, and ros� wines. Alternatively, we can divide a class of all wines into sparkling and non-sparkling wines. 
  • Slots describe properties of classes and instances:

  • In practical terms, developing an ontology includes:

      

    �         defining classes in the ontology,

      

    �         arranging the classes in a taxonomic (subclass–superclass) hierarchy,

      

    �         defining slots and describing allowed values for these slots,

      

    �         filling in the values for slots for instances.
  • here  is no one correct way to model a domain— there are always viable alternatives. The  best solution almost always depends on the application that you have in mind and the  extensions that you anticipate

  17 more annotations...

• 21 Dec 15
  

  James Humffray

  ontology semantic web

• 17 Dec 15
  

  Mathieu Saby

  "Ontology Development 101: A Guide to Creating Your First Ontology"

  ontologies guide

• 24 Aug 15
  

  V S
  • The Artificial-Intelligence literature contains many definitions of an ontology; many of these contradict one another. For the purposes of this guide an ontology is a formal explicit description of concepts in a domain of discourse (classes (sometimes called concepts)), properties of each concept describing various features and attributes of the concept (slots (sometimes called roles or properties)), and restrictions on slots (facets (sometimes called role restrictions)). An ontology together with a set of individual instances of classes constitutes a knowledge base. In reality, there is a fine line where the ontology ends and the knowledge base begins.
• 19 Aug 15
  

  Laurent Alquier

  ontology tutorial

• 29 Apr 15
  

  edsonluque
  • Why develop an ontology?
• 25 Nov 14
  

  sugarbyheart

  “本体”的概念，如何形成本体，本体的开源资源
• 23 Sep 14
  

  akash1600
  • licit formal specifications of the terms in the domain and relations among them (Gruber 1993)
• 16 Sep 14
  

  Vladimir Goloubtzoff

  Thésaurus

• 14 Jun 14
  

  Felix Griewald

  Ontology Howto and Wine Example

  semantic-web ontologies owl howto tutorial protege

• 19 May 14
  

  Arnaud Foucher
• 06 Mar 14
  

  Angelo Vermeulen

  ontology artificialintelligence knowledgebase stanford sead

• 11 Nov 13
  

  theo theo

  ontology

• 23 Oct 13
  

  rudy van bree

  ontologies semantic_web

• 16 Oct 13
  

  pauline charbonnier

  Ontology Development : A guide to creating your first ontology
  

  ontologie

• 05 Oct 13
  

  encima

  Pocket reference ontology

• 29 Sep 13
  

  MFIZI Ephrem

  GUIDE FOR FIRST ONTOLOGY CREATION

• 07 Sep 13
  

  eternaldon
  • An ontology defines a common vocabulary for researchers who need to share information in a domain. It includes machine-interpretable definitions of basic concepts in the domain and relations among them
  • Sharing common understanding of the structure of information among people or software agents  is one of the more common goals in developing ontologies (Musen 1992; Gruber 1993)
• 02 Jun 13
  

  Kelly Jurkowski

  ontology

• 21 Mar 13
  

  J. Smith

  • �         To share common understanding of the structure of information among people or software agents

      

    �         To enable reuse of domain knowledge

      

    �         To make domain assumptions explicit

      

    �         To separate domain knowledge from the operational knowledge

      

    �         To analyze domain knowledge
  • operational
  • structural
  • a formal explicit description of concepts in a domain of discourse
  • concepts)
  • classes
  • roles or properties
  • slots
  • properties of each concept describing various features and attributes of the concept
  • restrictions on slots (facets
  • knowledge base
  • Classes are the focus of most ontologies. Classes describe concepts in the domain.
  • subclasses
  • an instance of  the class
  • Slots describe properties of classes and instances

  • �         defining classes in the ontology,

      

    �         arranging the classes in a taxonomic (subclass–superclass) hierarchy,

      

    �         defining slots and describing allowed values for these slots,

      

    �         filling in the values for slots for instances.
  • knowledge base
  • terative

  • 1)      There  is no one correct way to model a domain— there are always viable alternatives. The  best solution almost always depends on the application that you have in mind and the  extensions that you anticipate.

     

    2)      Ontology  development is necessarily an iterative process.

     

    3)      Concepts  in the ontology should be close to objects (physical or logical) and relationships in your  domain of interest. These are most likely to be nouns (objects) or verbs (relationships)  in sentences that describe your domain.
  • an ontology is a model of reality of the world  and the concepts in the ontology must reflect this reality
  • evaluate and debug
  • define
  • domain  and scope

  • �          What is the domain that the ontology will cover?

     

    �          For what  we are going to use  the ontology?

     

    �          For what types of questions the information in the ontology should provide  answers?

     

    �          Who will use and maintain the ontology?
  • natural-language processing
  • synonyms and part-of-speech information for concepts
  • sketch a list  of questions that a knowledge base based on the ontology should be able to answer, competency questions
  • almost always worth considering what someone else has done and  checking if we can refine and extend
  • needs to interact with  other applications
  • Ontolingua ontology library
  • DAML ontology library
  • write down a list of all terms we would like either to  make statements about or to explain to a user.
  • without worrying about overlap
  • A top-down
  • bottom-up
  • combination
  • None of these three methods is inherently better than any of the others.
  • objects having independent existence rather than terms  that describe these objects
  • we usually start by defining classes
  • will become  anchors in the class hierarchy
  • properties of classes—slots
  • everal types of object properties that can become  slots
  •    “intrinsic”
  •    “extrinsic”
  •   parts, if the object is structured
  •     relationships to other individuals
  • A slot should be attached at the most general class that can have that  property.
  • value type, allowed values,  the number of the values (cardinality), and other features of the values the slot can  take
  • how many values a slot can have
  • single cardinality
  • multiple  cardinality
  • Minimum cardinality of N
  • value-type facet describes what types of values can fill in the slot
  • String
  •   Number
  • Boolean
  • simple  yes–no flags
  • Enumerated
  • list  of specific allowed values
  •   Instance-type slots
  • definition of relationships between individuals.
  • Allowed classes for slots of type Instance are often called a range of a slot.
  • The classes to which a slot is attached or a classes which property a slot  describes, are called the domain of the slot.
  • When defining a domain or a range for a slot, find the most general  classes or class that can be respectively the domain or the range for the slots .
  • 1) choosing a class, (2)  creating an individual instance of that class, and (3) filling in the slot values.
  • individual instances of classes
  • “is-a” relation
  • A single wine is not a subclass of all wines
  • always to use either singular or plural in naming  classes
  • Transitivity
  • If B is a subclass of A and C is a  subclass of B, then C is a subclass of A
  • direct subclass is the “closest”  subclass
  • domains  evolve.
  • Classes represent concepts in the  domain and not the words that denote these concepts.
  • Synonyms for the same concept do not  represent different classes
  • Many systems allow associating a list of synonyms,
  • Avoiding class cycles
  • avoid cycles in the  class hierarchy.
  • lasses that are direct subclasses of the same class
  • between two and a dozen direct  subclasses
  • If a class has only one direct  subclass
  • If there are more than a dozen  subclasses
  • multiple inheritance
  • a  class can be a subclass of several classes.
  • The Port  class will inherit its slots and their facets from both its parents.
  • In other words, we  introduce a new class in the hierarchy usually only when there is something that we can  say about this class that we cannot say about the superclass.
  • Classes in terminological hierarchies  do not have to introduce new properties

  85 more annotations...

• 18 Feb 13
  

  karmickoala
  •   What is the domain that the ontology will cover?
  • For what  we are going to use  the ontology?
  • For what types of questions the information in the ontology should provide  answers?
  •     Who will use and maintain the ontology?
  • lmost always worth considering what someone else has done and  checking if we can refine and extend existing source

  3 more annotations...

• 06 Feb 13
  

  tysonjh
  • One of the ways to determine the scope of the ontology is to sketch a list  of questions that a knowledge base based on the ontology should be able to answer, competency questions (Gruninger and Fox 1995).
  • DAML ontology library (http://www.daml.org/ontologies/)
  • Ontolingua ontology library (http://www.ksl.stanford.edu/software/ontolingua/)
  • commercial ontologies (e.g., UNSPSC (www.unspsc.org), RosettaNet (www.rosettanet.org),  DMOZ (www.dmoz.org))
  • write down a list of all terms we would like either to  make statements about or to explain to a user.
  • developing the class hierarchy and defining  properties of concepts (slots)
  • In general, there are several types of object properties that can become  slots in an ontology:

  5 more annotations...

• 09 Jan 13
  

  d216136

  ontology

  • Why would someone want to develop an ontology? Some of the reasons are:

      

    �         To share common understanding of the structure of information among people or software agents

      

    �         To enable reuse of domain knowledge

      

    �         To make domain assumptions explicit

      

    �         To separate domain knowledge from the operational knowledge

      

    �         To analyze domain knowledge
• 04 Oct 12
  

  Ruth M.

  Info Design ontologies

  • The ontologies on the Web range from large taxonomies categorizing Web sites (such as on Yahoo!) to categorizations of products for sale and their features (such as on Amazon.com)
  • Many disciplines now develop standardized ontologies that domain experts can use to share and annotate information in their fields.
  • An ontology defines a common vocabulary for researchers who need to share information in a domain
  • It includes machine-interpretable definitions of basic concepts in the domain and relations among them.
  • Sharing common understanding of the structure of information among people or software agents
  • share and publish the same underlying ontology of the terms they all use
  • t Web sites contain medical information or provide medical e-commerce services.
  • extract and aggregate information from these different sites
  • Enabling reuse of domain knowledge
  • as one of the driving forces behind recent surge in ontology research.
  • If one group of researchers develops such an ontology in detail, others can simply reuse it for their domains
  • reuse a general ontology,
  • we can integrate several existing ontologies describing portions of the large domain
  • underlying an implementation makes it possible to change these assumptions easily if our knowledge about the domain change
  • Making explicit domain assumptions
  • Separating the domain knowledge from the operational knowledge
  • Analyzing domain knowledge
  •  Formal analysis of terms is extremely valuable when both attempting to reuse existing ontologies and extending them (McGuinness et al. 2000)
  • Developing an ontology is akin to defining a set of data and their structure for other programs to use
  • Problem-solving methods, domain-independent applications, and software agents use ontologies and knowledge bases built from ontologies as data
  • For the purposes of this guide an ontology is a formal explicit description of concepts in a domain of discourse (classes (sometimes called concepts)), properties of each concept describing various features and attributes of the concept (slots (sometimes called roles or properties)), and restrictions on slots (facets (sometimes called role restrictions)). An ontology together with a set of individual instances of classes constitutes a knowledge base. In reality, there is a fine line where the ontology ends and the knowledge base begins.
  • Classes are the focus of most ontologies.
  • Classes describe concepts in the domain

  • In practical terms, developing an ontology includes:

      

    ÿfd         defining classes in the ontology,

      

    ÿfd         arranging the classes in a taxonomic (subclass–superclass) hierarchy,

      

    ÿfd         defining slots and describing allowed values for these slots,

      

    ÿfd         filling in the values for slots for instances.

      

    We can then create a knowledge base by defining individual instances of these classes filling in specific slot value information and additional slot restrictions.
  • We describe an iterative approach to ontology  development: we start with a rough first pass at the ontology.
  • We then revise and refine  the evolving ontology and fill in the details. Along the way, we discuss the modeling  decisions that a designer needs to make, as well as the pros, cons, and implications of  different solutions.
  • There  is no one correct way to model a domain
  • iterative process.
  • or verbs (relationships)  in sentences that describe your domain.
  • be nouns (objects)
  • should be close to objects (physical or logical) and relationships in your  domain of interest
  • what we are going to use the ontology for, and how  detailed or general the ontology is going to be will guide many of the modeling decisions  down the road
  • which one  would work better for the projected task, be more intuitive, more extensible, and more  maintainable.
  • This process of  iterative design will likely continue through the entire lifecycle of the ontology.
  • We suggest starting the development of an ontology by defining its domain  and scope

  • ÿfd          What is the domain that the ontology will cover?

     

    ÿfd          For what  we are going to use  the ontology?

     

    ÿfd          For what types of questions the information in the ontology should provide  answers?

     

    ÿfd          Who will use and maintain the ontology?
  • One of the ways to determine the scope of the ontology is to sketch a list  of questions that a knowledge base based on the ontology should be able to answer, competency questions
  • Does the ontology contain enough  information to answer these types of questions?
  • It is almost always worth considering what someone else has done and  checking if we can refine and extend existing sources for our particular domain and task
  • It is useful to write down a list of all terms we would like either to  make statements about or to explain to a user.
  • . Initially, it is important to get a comprehensive list of  terms without worrying about overlap between concepts they represent, relations among the  terms, or any properties that the concepts may have, or whether the concepts are classes  or slots..
  • The next two steps—developing the class hierarchy and defining  properties of concepts (slots)—are closely intertwined
  • . Typically, we create a few definitions of the concepts in the  hierarchy and then  continue by describing  properties of these concepts and so on. These two steps are also the most important  steps in the ontology-design process. We will  describe them here briefly and then spend the next two sections discussing the more  complicated issues that need to be considered, common pitfalls, decisions to make, and so  on.
  • several possible approaches
  •     A top-down development process  starts with the definition of the most general concepts in the domain and subsequent  specialization of the concept
  •   A bottom-up development process  starts with the definition of the most specific classes, the leaves of the hierarchy, with  subsequent grouping of these classes into more general concepts.
  •    A combination development process  is a combination of the top-down and bottom-up approaches: We define the more salient  concepts first and then generalize and specialize them appropriately

  45 more annotations...

• 30 Aug 12
  

  an88zi

  ontologies tutorial taxonomy owl protege

  • Deciding whether a particular concept is a class in an ontology or an  individual instance depends on what the potential applications of the ontology are.  Deciding where classes end and individual instances begin starts with deciding what is the  lowest level of granularity in the representation
  • at most one extra level each way
• 16 May 12
  

  jennybento

  taxonomy tutorials alataxoclass09 instructional ontologies

• 08 May 12
  

  Sinéad Moloney

  ontology

• 24 Apr 12
  

  Dave Dennis

  SemanticWeb

• 01 Apr 12
  

  yellowbag

  taxonomy tutorial semanticweb ontology

• 18 Mar 12
  

  geographica

  ontology

  • Separating the domain knowledge from the operational knowledge
  • An ontology together with a set of individual instances of classes constitutes a knowledge base.
• 28 Feb 12
  

  João Fernandes

  ontology

• 16 Jan 12
  

  feedmyego

  ontology ontologies semanticweb tutorial taxonomy

• 02 Dec 11
  

  Alex Milinovich

  ontology semanticweb owl rdf

• 10 Sep 11
  

  Jesse Wind

  ontology

• 18 Aug 11
  

  Cameron McLean

  " primarily around methods on classes"

  ontology ontologies tutorial

• 11 May 11
  

  ontology tutorial owl taxonomy semantic merged

• 03 May 11
  

  Joaquim Jorge Pereira
• 05 Mar 11
  

  kumyaa kumyaa

  ontology semanticweb tutorial taxonomy

• 11 Feb 11
  

  Greg Osinoff

  ontology semanticweb ontologies semantic_web taxonomy

• 11 Jan 11
  

  Dante-Gabryell Monson

  ontology protege howto

• 31 Dec 10
  

  Brian TheLion

  ontologies protege

• 16 Dec 10
  

  pradheap

  ontology semanticweb design semantic tutorial howto programming web ontologies taxonomy

• 23 Sep 10
  

  Zaid Al Wandawi
  • Object-oriented programming centers primarily around methods on classes—a programmer makes design decisions based on the operational properties of a class, whereas an ontology designer makes these decisions based on the structural properties of a class
  • it may be important to include  synonyms and part-of-speech information for concepts in the ontology
  • will be used to assist in  natural-language processing of articles in wine magazines
  • Competency questions
  • sketch a list  of questions that a knowledge base based on the ontology should be able to answer
  • possible competency  questions
  • What properties do those terms have? What would we like to say about those terms?
  • What are the terms we would like to talk  about?
  • None of these three methods is inherently better than any of the others
  • there are several types of object properties that can become  slots in an ontology
  • cardinality
  • value type
  • allowed values
  • how many values a slot can have
  • relationships
  • Allowed classes for slots of type Instance
  • The classes to which a slot is attached or a classes which property a slot  describes, are called the domain of the slot
  • depends on what the potential applications of the ontology are
  • what is the  lowest level of granularity in the representation
  • what are the most  specific items that are going to be represented in the knowledge base?
  • deciding when an ontology definition is complete
  • The ontology should not contain all the possible information about the  domain
  • need for your  application
  • concepts
  • Biological  organisms
  • It is true that an  experimenter, as a person, also happens to be a biological organism
  • Experimenter
  • Classes are disjoint if they cannot have  any instances in common
  • Dessert  wine
  • White  wine
  • he same name space for classes, slots, and instances?
  • the same name space for classes, slots, and instances?
  • case-sensitive?
  • The analysis that Chimaera performs  includes both a check for logical correctness of an ontology and diagnostics of common  ontology-design errors
  • declarative frame-based systems
  • here  is no single correct ontology for any domain

  34 more annotations...

• 02 Aug 10
  

  Mary Whelan

  Guide to Creating Ontology with OWL and Protege

  SKOS OWL

• 25 Jul 10
  

  Mary Fran Prottsman

  protoge ontology development

• 22 Jul 10
  

  soulfx
  • ontologies—explicit formal specifications of the terms in the domain and relations among them
  • The Artificial-Intelligence literature contains many definitions of an ontology; many of these contradict one another.
• 08 Jun 10
  

  Ryan Brinkworth

  information architecture ontology

• 24 May 10
  

  Grant Slade

  http://ksl-web.stanford.edu/people/axf/tutorial.pdf

  ontologies tutorials

• 20 Apr 10
  

  nicopace

  ontology creation guide semanticweb owl design semantic

• 12 Mar 10
  

  nas827

  semantic_web

• 26 Feb 10
  

  ontology tutorial owl taxonomy semantic

• 

  ontology modelling factModel taxonomy classModel

  • One of the hardest decisions to make during modeling is when to introduce  a new class or when to represent a distinction through different property values. It is  hard to navigate both an extremely nested hierarchy with many extraneous classes and a  very flat hierarchy that has too few classes with too much information encoded in slots.  Finding the appropriate balance though is not easy.
  • ubclasses of a class usually (1) have additional properties that the  superclass does  not have, or (2) restrictions  different from those of the superclass, or (3) participate in different relationships than  the superclasses
  • Deciding whether a particular concept is a class in an ontology or an  individual instance depends on what the potential applications of the ontology are

  1 more annotation...

• 05 Feb 10
  

  Sub Proletarian

  ontology semanticweb tutorial ontologies owl taxonomy semantic information

• 29 Jan 10
  

  Martin Davtyan

  ontology

• 10 Nov 09
  

  shingo nakayama

  ontology protege tutorial

• 28 Sep 09
  

  jenmccarrick

  writing content_development

• 20 Jun 09
  

  raphinou

  semanticweb ontology tutorial

• 16 Jun 09
  

  St Dix

  imported Bookmarks Ontology

• 13 Jun 09
  

  Vasenta Narkia

  ontology design ontologies TUTORIAL academic semweb semantics edu owl howto whatis architecture university ai tutorials article semantic_web popular

• 08 Jun 09
  

  Violeta Damjanovic

  Ontology Development 101: A Guide to Creating Your First Ontology

  ontologies

• 22 Apr 09
  

  J M

  informatics

• 26 Feb 09
  

  owen walton

  owl protege

• 13 Jan 09
  

  Ontologie

• 19 Dec 08
  

  Alexandra N

  Menu_des_marque-pages Educatie Informatica Semantic_Web

• 06 Dec 08
  

  Konstantin Läufer

  research cuerp semanticweb

• 12 Nov 08
  

  radubcrisan

  article ontology OWL

• 10 Nov 08
  

  Jean Stephan

  Ontology need

• 29 Oct 08
  

  Rick Hart

  Ontology

• 17 Jul 08
  

  Teague Allen

  Late 20th century explanation of what an ontology is and how it might be useful. Possibly the source of the wine cellar scenario used to demonstrate semantic web several other places.

  information language article ontology semanticweb taxonomy web3.0

• 

  Chris Lynnes

  tiwg radar semanticweb tiwg-radar

• 

  Parelius T

  Ontology Development 101: A Guide to Creating Your First Ontology

  ontology tutorial protégé

• 24 Apr 08
  

  Roman grup Algos

  tutorials

• 20 Mar 08
  

  btlgs2000 btlgs2000

  ia ontology semanticweb tutorial

• 06 Mar 08
  

  Martin Martyn

  kb-xjobb

• 16 Feb 08
  

  yarden

  ontology

  • ontologies—explicit formal specifications of the terms in the domain and relations among them (Gruber 1993)
  • Medicine, for example, has produced large, standardized, structured vocabularies such as snomed (Price and Spackman 2000) and the semantic network of the Unified Medical Language System (Humphreys and Lindberg 1993).
  • Why would someone want to develop an ontology?
  • Sharing common understanding of the structure of information among people or software agents
  • Enabling reuse of domain knowledge
  • UNSPSC ontology
  • Making explicit domain assumptions
  • Separating the domain knowledge from the operational knowledge
  • Analyzing domain knowledge
  • Often an ontology of the domain is not a goal in itself. Developing an ontology is akin to defining a set of data and their structure for other programs to use. Problem-solving methods, domain-independent applications, and software agents use ontologies and knowledge bases built from ontologies as data.
  • a programmer makes design decisions based on the operational properties of a class, whereas an ontology designer makes these decisions based on the structural properties of a class.
  • An ontology together with a set of individual instances of classes constitutes a knowledge base. In reality, there is a fine line where the ontology ends and the knowledge base begins.

  10 more annotations...

• 07 Jan 08
  

  forrestrunning

  semantic-web

• 10 Aug 07
  

  Judy O'Connell

  Sharing common understanding of the structure of information among people or software agents is one of the more common goals in developing ontologies

  semanticweb Web3.0 InformationArchitecture

• 25 Apr 07
  

  Ontology Development 101: A Guide to Creating Your First Ontology

  ontologies websem

• 13 Apr 07
  

  Donald Fleming

  Ontology

• 21 Jan 07
  

  Taxonomy Ontology SimmonsTaxo

• 24 Nov 06
  

  Matti Narkia

  ontology design ontologies TUTORIAL academic semweb semantics edu owl howto whatis architecture university ai tutorials article semantic_web popular

• 29 Oct 06
  

  Mart

  dissertation ontology

• 11 Oct 06
  

  Terry Kuny

  Pinboard ontology semantic_web design ia Delicious import

• 02 Oct 06
  

  Gary Burge

  An ontology defines a common vocabulary for researchers who need to share information in a domain. It includes machine-interpretable definitions of basic concepts in the domain and relations among them.

  ontology taxonomy folksonomy tagging articles

• 02 Aug 06
  

  Jason Fleming

  lis6726 ontology semanticweb taxonomy

• 19 Apr 06
  

  Claudio Bergamini

  semantic tutorial ontology

• 12 Apr 06
  

  michischwalbe

  semanticweb ontology

• 10 Mar 06
  

  Fabio Escargo

  Tutorial on creating ontologies
  

  ontology semanticweb owl

• 21 Nov 05
  

  Sam

  research information ontology

• 15 Nov 05
  

  John Doe

  semantic-web introduction overview ontology-design

• 13 Sep 05
  

  billpapa

  programming ontology

• 01 Dec 04
  

  tadej zontar

  Ontology

  • Ontology Development 101: A Guide to Creating Your First Ontology  Natalya F. Noy and Deborah L. McGuinness  Stanford University, Stanford, CA, 94305  noy@smi.stanford.edu and dlm@ksl.stanford.edu
  • Ontology Development 101: A Guide to Creating Your First Ontology  Natalya F. Noy and Deborah L. McGuinness  Stanford University, Stanford, CA, 94305  noy@smi.stanford.edu and dlm@ksl.stanford.edu
  • Ontology Development 101: A Guide to Creating Your First Ontology  Natalya F. Noy and Deborah L. McGuinness  Stanford University, Stanford, CA, 94305  noy@smi.stanford.edu and dlm@ksl.stanford.edu

  1 more annotation...

• 30 Sep 04
  

  memoriaTechnica

  Knowledge_Work

  • Ontology Development 101: A Guide to Creating Your First Ontology
• 01 Jan 04
  

  cshirky

  Almost self-critiquing in its prescriptions...
  

  semweb ontology

Page Comments

• 
  Jason Fleming on 2006-08-02
  working on folksonomy paper

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