'Ontology Design Patterns' - User contributions [en]

Ontology:Recommendation Ontology

2011-03-30T20:30:45Z

BobFerris:

{{Ontology
|Name=Recommendation Ontology
|OntologyAuthor=Bob Ferris, Kurt Jacobson
|Description=The Recommendation Ontology specification provides basic concepts and properties for describing recommendations on/ for the Semantic Web.
|SubmittedBy=BobFerris
|OntologyPurpose=For describing recommendations of all kinds.
|OntologyURI=http://purl.org/ontology/rec/core
|LongDescription=The Recommendation Ontology is an ontology for modeling high level recommendations on/ for the Semantic Web. Thereby, the ontology hook up parts of the Similarity Ontology, DCMI Metadata Terms, the Association Ontology and the Ordered List Ontology.
The core of the Recommendation Ontology is the rec:Recommendation concept. A rec:Recommendation instance can consist of

* an item or agent relation (rec:Recommendation or its inverse property rec:for) to associate the resource, for which the recommendation was made
* an recommender relation (rec:recommender or its inverse property rec:recommends) to associate the instance, which provided or calculated the recommendation, e.g. an is:InfoService instance
* recommendation object relations (rec:recommendation_object or its inverse property rec:recommended_in) to associate appropriated objects to the recommendation subject
* recommendation audience relations (rec:recommendation_audience to associate groups or stereotypes, which are probably appropriated as target group for this recommendation.

Since rec:Recommendation is a sub class of ao:LikeableAssociation, it is also possible to like (ao:likeminded), rate (rev:rating) or give a feedback (rev:Feedback) to a recommendation. Furthermore, one can also relate detailed association (sim:Association) or similarity statements (sim:Similarity) to a recommendation by using the property ao:included_association.
As an extension of rec:Recommendation, we built the rec:RankedRecommendation concept to enable also ordered (ranked) recommendations at a high level. rec:RankedRecommendation is not only a sub class of rec:Recommendation. Furthermore, it is also a sub class of olo:OrderedList, which enables all features of an ordered list also to this concept. Following this design, a rec:ranked_recommendation is not only a sub property of rec:recommendation_object, but also a sub property of olo:slot. That means the recommendation objects are now related by using the property olo:item.
|Justification=The Recommendation Ontology hooks up parts of the Similarity Ontology, the DCMI Metadata Terms, the Association Ontology and the Ordered List Ontology.
|OntologyDomain=Recommendation,
|Scenario=Federated Recommendations
}}

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Ontology:Cognitive Characteristics Ontology

2011-03-30T20:30:10Z

BobFerris:

{{Ontology
|Name=Cognitive Characteristics Ontology
|OntologyAuthor=Dan Brickley, Libby Miller, Toby Inkster, Yi Zeng, Yan Wang, Danica Damljanovic, Zhisheng Huang, Sheila Kinsella, John Breslin, Bob Ferris
|Description=The Cognitive Characteristics Ontology specification provides a vocabulary for describing cognitive pattern within contexts, their temporal dynamics and their origins, on/ for the Semantic Web.
|SubmittedBy=BobFerris
|OntologyPurpose=Description of personal cognitive pattern in a simple and extended way.
|OntologyURI=http://purl.org/ontology/cco/core
|LongDescription=The Cognitive Characteristics Ontology includes two opportunities to model cognitive patterns. The first one is the representation of cognitive characteristics by using the semantic relation cco:cognitive_characteristic or better its more specialised sub properties (see graphic cco:cognitive_characteristic property as graph with relations) to associate the topics of the cognitive patterns to the users. The second opportunity is the property-oriented context reification of cco:cognitive_characteristic, cco:CognitiveCharacteristic, which is a general multiple purpose cognitive characteristic concept to describe cognitive patterns more in detail for a specific user or user group.
As one can see in graphic cco:CognitiveCharacteristic concept as graph with relations, the specialised sub properties of cco:cognitive_characteristic, the cognitive patterns, currently are

* interest (cco:interest), that means, a certain area of interest or preference, which is equivalent to foaf:topic_interest,
* compentence (cco:competence), that means, the compentence to (be able to) do or know something or
* setting (cco:setting), often regarding a specific environment, e.g. an application.

One can also refine the semantic relation of a competence association by using the sub properties of cco:competence, which are currently:

* cco:skill: the ability or skill to (be able to) do something, e.g. to walk, to play the piano or to work in a team
* cco:expertise: the knowledge or expertise in a certain domain or a specific topic, e.g. football, programming languages or music
* cco:belief: an uncertain relation for competence representation, that means beliefs, persuasions or opinions, which can also be misconceptions

One can see the second opportunity to model cognitive patterns, cco:CognitiveCharacteristic in graphic cco:CognitiveCharacteristic concept as simplified graph with relations. This concept can be used to associate any foaf:Agent instance to (a) cco:CognitiveCharacteristic instance(s) with help of the properties cco:habit and cco:agent. The topics of a cco:CognitiveCharacteristic instance are related to it by using the property cco:topic, so that a property chain of cco:habit and cco:topic will also direct to topics of a cognitive pattern of an user or user group. That means, a statement that is modelled with the simple semantic relation approach based on cco:cognitive_characteristic can also be represented by an instance of cco:CognitiveCharacteristic, which has a cco:agent or cco:habit, a cco:topic and a cco:characteristic relation. The last property in this row is used to associate the applied cognitive pattern relation (sub properties of cco:cognitive_characteristic).
Different statistics can be made on cognitive characteristics. These are currently:

* cco:overall_weight, which reflects the overall interest in a topic and should be different from the actual weight (associated by the property wo:weight) of a cognitive characteristic
* cco:longest_duration, which is the longest continuous interval of attention for a cognitive pattern, e.g. for an interest, if it appears in the following years: 1990, 1991, 1995, 1996, 1997, 1998, 2001, then the longest duration is 4 years
* cco:ultimative_duration, which is the overall duration of attention for a cognitive pattern, e.g. for an interest, if it appears in the following years: 1990, 1991, 1995, 1996, 1997, 1998, 2001, then the longest duration is 7 years

Besides these statistics, one can also associate a concrete activity (by using the property cco:activity), to differentiate e.g. between football playing (topic = football; activity = playing) and football watching (topic = football; activity = watching), and further statistical items (by using the property cco:statistical_item) to a cognitive pattern description, which is itself also a sub class of scovo:Item.
It is also important, to be able to describe dynamics of a cognitive characteristic. In the Cognitive Characteristics Ontology they can be described with help of the cco:CharacteristicDynamics concept, which is a sub class of wo:Weight, and can be related to a cco:CognitiveCharacteristic instance by using the property cco:characteristic_dynamics. Thereby, one can relate

* concrete appear times (time instants or intervals, by using the property cco:appear_time), when a cognitive pattern gets attention by someone, or
* an evidence description (by using the property cco:evidence), where this characteristic or dynamics was derived from.

to a cco:CognitiveCharacteristic or cco:characteristic_dynamics instance.
Due to the two modelling opportunities of cognitive pattern in the Cognotive Characteristics Ontology, there is a need for formal semantics to associate statements with a shortcut relation and instances of the reification class that belonging together or to infer such knowledge with a reasoning engine. The Property Reification Vocabulary fulfil these requirements.
|Justification=The Cognitive Characteristics Ontology is built on top of the Weighted Interests Vocabulary v0.5 and should probably substitute this ontology in the near future. That means all concepts and properties are imported from this ontology. Some of them are also redefined and renamed to broaden their meaning. Furthermore, the Cognitive Characteristics Ontology is inspired by the Unified User Context Model, the General User Model Ontology, the User Modelling for Information Retrieval Language and all their fundamental sources, and finally, the discussions on the FOAF developers mailing list.
The Weighted Interests Vocabulary v0.5 is an union of the Weighted Interest Vocabulary, the E-foaf:interest Vocabulary and the Interest Mining Ontology. That means, all interest related ontologies are now merged under one hood and some concepts are proper modeled now. The design of this interest ontology is also strongly influenced by the outcome of the User (weighted) Interests Ontology working group from Hypios VoCamp Paris 2010.
|OntologyDomain=Personalization
|Scenario=User Profiling
}}

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Ontology:Property Reification Vocabulary

2011-03-30T20:29:05Z

BobFerris:

{{Ontology
|Name=Property Reification Vocabulary
|OntologyAuthor=Jiří Procházka, Richard Cyganiak, Toby Inkster, Bob Ferris
|Description=The Property Reification Vocabulary specification provides a vocabulary for describing the ontology design pattern of property reification on/ for the Semantic Web.
|SubmittedBy=BobFerris
|OntologyPurpose=Enable reification descriptions on the vocabulary level. Can be used for ontology mapping.
|OntologyURI=http://purl.org/ontology/prv/core
|LongDescription=It seems that there is still a lack in modelling contextual information for Semantic Graph triples and deploying this knowledge representation reusable in a distributed Linked Data environment. Although, there exists probably applicable solutions for representing external context*, e.g. Named Graphs or N-Quads. However, these methods are not really appropriated to represent internal context* by keeping clear semantics regarding their described Semantic Graph triples (information resource). Even the existing method for RDF statements, RDF Reification (statement reification), has no clear semantics between the statement triple(s) and their reification information resource(s). Furthermore, this method is intended to be applied at the instance level. Although, it might be good to be able to apply reification definition also on the vocabulary level. That means, to reify the semantic relation that is established by a property. This kind of reification is then called property reification.
Therefore, the simple semantic relation, represented by subject, predicate and object, is now defined as shortcut relation. Thereby, the predicate is always the same property for a single shortcut relation definition. Beyond, the class that enables a detailed description of such a n-ary relation is called reification class.
Due to the reason, that there wasn’t a published vocabulary that addresses a mapping and its semantics between shortcut relations and reification classes and vice versa, Bob Ferris co-designed the Property Reification Vocabulary. This vocabulary is designed after a proposal made by Jiří Procházka, Richard Cyganiak and Toby Inkster and was also extended by Bob Ferris to enable further functionality. It should reflect the important use case and ontology design pattern of property reification. This gives ontology designers the freedom to separate such property reification definitions from their core ontology definition and enable hence the opportunity to make them optional.
|Justification=The Property Reification Vocabulary is design after a proposal made by Jiří Procházka, Richard Cyganiak and Toby Inkster and extended by Bob Ferris. It should reflect the important use case and ontology design pattern of property reification, which is different from statement reification (see also background and this explanation). This gives ontology designers the freedom to separate such property reification definitions from their core ontology and enable hence the opportunity to make them optional.
|OntologyDomain=Ontology Alignment, Ontology, Vocabulary,
|Scenario=Ontology mapping
}}

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Ontology:Ordered List Ontology

2011-03-30T20:28:35Z

BobFerris:

{{Ontology
|Name=Ordered List Ontology
|OntologyAuthor=Samer A. Abdallah, Bob Ferris
|Description=The Ordered List Ontology Specification provides basic concepts and properties for describing ordered lists as semantic graph.
|SubmittedBy=BobFerris
|OntologyPurpose=To get rid of RDF sequences ;) and to enable typed sequences for special purposes, e.g. playlists
|OntologyURI=http://purl.org/ontology/olo/core
|LongDescription=There is a need to describe typed ordered lists or sequences of information resources. The existing approach in the RDF vocabulary, rdf:Seq, has some drawbacks regarding defining explicitly a range for items of a sequence and to query them efficiently with SPARQL, because every slot of a sequence is related by a separate property of the form rdf:_N, where N is a positive integer number, e.g. rdf:_1 (cf. RDF Vocabulary Description Language 1.0: RDF Schema and RDF Semantics ). That’s why, I co-designed the Ordered List Ontology according to a proposal made by Samer A. Abdallah. This ontology should overcome the drawbacks of the existing ordered list modelling approach by enabling more semantics to describe sequences of information resources.
As one can see in graphic 'olo:OrderedList concept as graph with relations', the Ordered List Ontology consists of two concepts - olo:OrderedList and olo:Slot. That means an ordered list is a composite of all slots, which are part of this ordered list (related by the property olo:slot). Although, the Ordered List Ontology is OWL based, the ontology also provides "backward" compatibility to the RDFS world.
The initial and primary access method to single slots in an ordered list should be olo:index, because this property represents the fixed index of a slot in an ordered list. Thereby, the property olo:length relates to the length of an ordered list, the number of included slots. The secondary access method is its (currently) optional iterator olo:next as shortcut to the next slot in the list. The items, which are arranged in an ordered list, are associated by the property olo:item to a slot.
On the basis of the ordered list concept defined in the Ordered List Ontology one can define more specific ordered list definitions, e.g. for media playlist (see the Play Back Ontology) or ranked recommendations (see the Recommendation Ontology).
|Justification=To get rid of RDF sequences ;)
|OntologyDomain=Knowledge engineering, Parts and Collections,
}}

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Ontology:Weighting Ontology

2011-03-30T20:28:01Z

BobFerris:

{{Ontology
|Name=Weighting Ontology
|OntologyAuthor=Bob Ferris
|Description=The Weighting Ontology specification provides a vocabulary for describing weightings and their referenced scales, on/ for the Semantic Web.
|SubmittedBy=BobFerris
|OntologyPurpose=To have a concept to describe weights not only with a value.
|OntologyURI=http://purl.org/ontology/wo/core
|LongDescription=The Weighting Ontology includes a general multiple purpose weight concept. This concept can be used to associate any concept to a wo:Weight instance(s) with the property wo:weight. The second property of wo:Weight is wo:weight_value, which is a simple xsd:decimal based datatype property to associate the numeric value of the weighting.
Furthermore, this ontology includes a wo:Scale, which is modeled as a sub class of scovo:Dimension to relate it to its specified scovo:Item based concept (wo:Weight) via wo:scale. To define the range of this scale the properties wo:min_weight and wo:min_weight can be used. These are sub properties of the related minimum and maximum properties of the Statistical Core Vocabulary (scovo:min and scovo:max) and the Review Vocabulary (rev:minRating and rev:maxRating). Finally one can define a step size (wo:step_size) for the weighting scales.
|Justification=The Weighting Ontology includes a multiple purpose weighting concept on top of Statistical Core Vocabulary.
}}

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Ontology:Info Service Ontology

2011-03-30T20:27:28Z

BobFerris:

{{Ontology
|Name=Info Service Ontology
|OntologyAuthor=Bob Ferris
|Description=The Information Service Ontology Specification provides basic concepts and properties for describing different information services, e.g. Wikipedia, MusicBrainz, Freebase or Discogs, on/ for the Semantic Web.
|SubmittedBy=BobFerris
|OntologyPurpose=For describing, rating and categorizing information services of all kind.
|OntologyURI=http://purl.org/ontology/is/core
|LongDescription=The Info Service Ontology consists of a basic is:InfoService concept (which could maybe related to prv:DataProvidingService, bibo:Collection, sioc:Space or void:Dataset instances) and some additional ones for describing such an information service (currently: is:InfoServiceQuality, is:InfoServiceType and is:InfoServiceContributorType – the specific individuals are currently only proof-of-concept examples).

The main hook re. specific websites from an information service is is:info_service, which associates an is:InfoService instance to e.g. a owl:Thing (or e.g. sub class of owl:Thing, e.g. foaf:Document) instance (e.g. a website link).

Furthermore, I defined some is:InfoService individuals, especially isi:musicbrainz (see the graphic above and code below) as proof-of-concept example. Therefore, I used also some category definitions from DBpedia (important is also the property is:main_subject for associating a main subject of an Information Service).
|Justification=There is a need to describe information services of all kind, not only semantic web information services.
|OntologyDomain=Knowledge engineering,
}}

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Ontology:Play Back Ontology

2011-03-30T20:27:00Z

BobFerris:

{{Ontology
|Name=Play Back Ontology
|OntologyAuthor=Bob Ferris, Kurt Jacobson
|Description=The Play Back Ontology specification provides basic concepts and properties for describing concepts that are related to the play back domain, e.g. an playlist, play back count and skip counter, on/ for the Semantic Web.
|SubmittedBy=BobFerris
|OntologyPurpose=Addresses concepts of a specific media domain, the play back domain.
|OntologyURI=http://purl.org/ontology/pbo/core
|LongDescription=The Play Back Ontology provides basic concepts and properties for describing concepts that are related to the play back domain, e.g. a playlist, play back and skip counter, on/ for the Semantic Web.

The play back domain could be seen as a subset of the media domain - it deals with playing back some media, e.g. videos, music tracks or slideshows, somehow.

On the basis of this definition the objects that are included into this domain are media objects. That means all concepts of the Play Back Ontology are somehow related to at least one media object. The range of these media objects is currently restricted to the concepts bibo:Document and frbr:Endeavour, incl. all their sub classes, e.g. mo:Track.
The pbo:Playlist concept is a sub class of olo:OrderedList and hence, a specialized ordered list of the media domain. Therefore, a pbo:Playlist instance consists of pbo:PlaylistSlot instances (related by pbo:playlist_slot), which are related to at least one media item by using the property pbo:playlist_item. pbo:Playlist has a further sub class, pbo:FixedPlaylist, to described playlists or sections of playlists, which have a strict order, e.g. a section of music tracks that should be played always one after another, or that are somehow related to each other. Furthermore, pbo:Playlist instances can be related to something by using the property pbo:playlist.
The Play Back Ontology consists further more of a couple of media action counters, which are represented by pbo:MediaActionCounter. Sub classes of this concept are pbo:PlayBackCounter and pbo:SkipCounter. Due to the property pbo:media_object, which is a sub property of co:object, it is possible to only associate media objects to pbo:MediaActionCounter instances.
The Play Back Ontology and the illustrated examples above demonstrates the reutilization, specialization and application of concepts of existing ontologies (Ordered List Ontology, Counter Ontology, Association Ontology, Music Ontology, Similarity Ontology, DCMI Metadata Terms, ...). Please feel free to create further, more specialized concepts and properties, which are based on the introduced ontologies, e.g. describing transition of music tracks in dj mixes (as discussed here).
|Justification=The Play Back Ontology is a an extension of the Ordered List Ontology and the Counter Ontology to represent play back specific concepts and relations.
|OntologyDomain=Multimedia
}}

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Ontology:Association Ontology

2011-03-30T20:26:19Z

BobFerris:

{{Ontology
|Name=Association Ontology
|OntologyAuthor=Bob Ferris, Toby Inkster
|Description=The Association Ontology specification provides basic concepts and properties for describing specific association statements to something,e.g. an occasion, a genre or a mood, and enables furthermore,a mechanism to like/rate and feedback these associations
|SubmittedBy=BobFerris
|OntologyPurpose=Providing various general association relation types and a concept for feedback-able personal associations.
|OntologyURI=http://purl.org/ontology/ao/core
|LongDescription=The Association Ontology combines features of the Similarity Ontology, the Review Ontology and DCMI Metadata Terms. The intend behind this ontology is to provide a mechanism to append (personal) association statements (sim:Association) to something by using the relation sim:association. This step of indirection is neccessary to enable:

* reusable association statements and
* voting, rating and reviewing of association statements in a specific context.

Therefore, the sub class ao:LikeableAssociation was created, which combines the concepts of sim:Association and rev:Review. Simple voting (the "like button") can be realized by using the property ao:likeminded, which creates a relation between an association statement and an individuum (foaf:Agent). Ratings and reviews can be realized by using the features of the Review Ontology, e.g. rev:rating or rev:Feedback.
To address associations of a specific domain, e.g. genre, mood or occasion, new sub properties based on dcterms:subject were created. These are:

* ao:genre: a hook for genres descriptions of all kind,
* ao:mood: a hook for mood descriptions and
* ao:occasion: a hook for occasion descriptions.

They are intendend to be an abstact and general hook into their specific domains (genre, mood, occasion). Furthermore, new, more specific sub properties based on these properties should be created to provide a hook in more specific domains, e.g. mo:genre for music genres/styles (this sub property relation isn't currently the case).
To enable voting, rating and reviewing of a reusable association statements in a specific context, the property ao:included_association was created. By using this relation one can include a reusable association statement into another association statement (preferable based on ao:LikeableAssociation). Please have also a look at the example in this document, which illstrates this use case.
|Justification=The Association Ontology hooks up parts of the Similarity Ontology, the Review Ontology and DCMI Metadata Terms.
|OntologyDomain=Knowledge engineering
}}

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Ontology:Counter Ontology

2011-03-30T20:25:55Z

BobFerris:

{{Ontology
|Name=Counter Ontology
|OntologyAuthor=Yves Raimond, Mats Skillingstad, Bob Ferris
|Description=The Counter Ontology specification provides basic concepts and properties for describing a general counter concept and some important sub counters, e.g. an event counter, on/ for the Semantic Web.
|SubmittedBy=BobFerris
|OntologyPurpose=To describe counters of all kinds and events that are related to a specific counter.
|OntologyURI=http://purl.org/ontology/co/core
|LongDescription=The Counter Ontology includes a general multiple purpose counter concept. This concept could be uses to associate any concept to a co:Counter instance(s) with the property co:counter or a specific sub property of it. The second property of co:Counter is co:count, which is a simple xsd:integer based datatype property. That means you could use this concept for things like for example play counter, skip counter or website hit counter.
Furthermore, this ontology includes already a predefined property to associate event specific ( event:Event) counter to its related events (co:event_counter,), e.g. a co:ScrobbleEvent to scrobble something. This enables the opportunity to trace back all related events, which are responsible for a specific count. Of course, this is also possible with all other concepts ;)
|Justification=The Counter Ontology is a generalisation of the Playcount Ontology from Yves Raimond.
|OntologyDomain=Knowledge engineering
}}

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Community:Ontology-based models

2011-02-02T23:54:06Z

BobFerris:

{{TitleDescription Template
|Title=AlexandraGalatescu
|Description=Patterns for building ontology-based models for applications, by inter-ontology relationships, constraints and rules.
General patterns for inference and search on ontology-based models.
}}
{{Graphical representation}}
{{Modeling Issue Template
|Author=AlexandraGalatescu, BobFerris
|Domain=Ontology-based modeling
|Scenario=Property reification, reification on the vocabulary level (see http://purl.org/ontology/prv/core#).
|ProposedSolution=http://purl.org/ontology/prv/core#
}}
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Community:Ontology-based models

2011-02-02T23:52:53Z

BobFerris:

{{TitleDescription Template
|Title=AlexandraGalatescu
|Description=Patterns for building ontology-based models for applications, by inter-ontology relationships, constraints and rules.
General patterns for inference and search on ontology-based models.
}}
{{Graphical representation}}
{{Modeling Issue Template
|Author=AlexandraGalatescu, BobFerris
|Domain=Ontology-based modeling
|ProposedSolution=http://purl.org/ontology/prv/core#
}}
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Community:Ontology-based models

2011-02-02T23:52:38Z

BobFerris:

{{TitleDescription Template
|Title=AlexandraGalatescu
|Description=Patterns for building ontology-based models for applications, by inter-ontology relationships, constraints and rules.
General patterns for inference and search on ontology-based models.
}}
{{Graphical representation}}
{{Modeling Issue Template
|Author=AlexandraGalatescu, BobFerris
|Domain=Ontology-based modeling
}}
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Community:References/Property Reification RDF Vocabulary

2011-02-02T23:51:04Z

BobFerris: New page: {{Reference |Subject=Ontology:Property Reification Vocabulary |Label=Property Reification RDF Vocabulary |Description=The working page of the Property Reification Vocabulary on the ESW wik...

{{Reference
|Subject=Ontology:Property Reification Vocabulary
|Label=Property Reification RDF Vocabulary
|Description=The working page of the Property Reification Vocabulary on the ESW wiki.
|Type=Wiki
|URL=http://esw.w3.org/PropertyReificationVocabulary
}}

Ontology:Property Reification Vocabulary

2011-02-02T23:49:33Z

BobFerris: New page: {{Ontology |Name=Property Reification Vocabulary |OntologyAuthor=Jiří Procházka, Richard Cyganiak, Toby Inkster, Bob Ferris |Description=The Property Reification Vocabulary specificatio...

{{Ontology
|Name=Property Reification Vocabulary
|OntologyAuthor=Jiří Procházka, Richard Cyganiak, Toby Inkster, Bob Ferris
|Description=The Property Reification Vocabulary specification provides a vocabulary for describing the ontology design pattern of property reification on/ for the Semantic Web.
|SubmittedBy=BobFerris
|OntologyPurpose=Enable reification descriptions on the vocabulary level. Can be used for ontology mapping.
|OntologyURI=http://purl.org/ontology/prv/core#
|LongDescription=It seems that there is still a lack in modelling contextual information for Semantic Graph triples and deploying this knowledge representation reusable in a distributed Linked Data environment. Although, there exists probably applicable solutions for representing external context*, e.g. Named Graphs or N-Quads. However, these methods are not really appropriated to represent internal context* by keeping clear semantics regarding their described Semantic Graph triples (information resource). Even the existing method for RDF statements, RDF Reification (statement reification), has no clear semantics between the statement triple(s) and their reification information resource(s). Furthermore, this method is intended to be applied at the instance level. Although, it might be good to be able to apply reification definition also on the vocabulary level. That means, to reify the semantic relation that is established by a property. This kind of reification is then called property reification.
Therefore, the simple semantic relation, represented by subject, predicate and object, is now defined as shortcut relation. Thereby, the predicate is always the same property for a single shortcut relation definition. Beyond, the class that enables a detailed description of such a n-ary relation is called reification class.
Due to the reason, that there wasn’t a published vocabulary that addresses a mapping and its semantics between shortcut relations and reification classes and vice versa, Bob Ferris co-designed the Property Reification Vocabulary. This vocabulary is designed after a proposal made by Jiří Procházka, Richard Cyganiak and Toby Inkster and was also extended by Bob Ferris to enable further functionality. It should reflect the important use case and ontology design pattern of property reification. This gives ontology designers the freedom to separate such property reification definitions from their core ontology definition and enable hence the opportunity to make them optional.
|Justification=The Property Reification Vocabulary is design after a proposal made by Jiří Procházka, Richard Cyganiak and Toby Inkster and extended by Bob Ferris. It should reflect the important use case and ontology design pattern of property reification, which is different from statement reification (see also background and this explanation). This gives ontology designers the freedom to separate such property reification definitions from their core ontology and enable hence the opportunity to make them optional.
|OntologyDomain=Ontology Alignment, Ontology, Vocabulary,
|Scenario=Ontology mapping
}}

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Community:Ordered Lists

2011-02-02T23:41:46Z

BobFerris:

{{TitleDescription Template
|Title=Ordered Lists
|Description=This problem originates from the W3C Decision Incubator activity, however it is not restricted to the decision-making domain, but more general.

The problem is how to best represent ordered lists in RDF/OWL. In the decision representation domain the problem arises when modeling options, where one of the options will be selected, i.e., it will be the decision.

RDF contains native constructs for sets and lists. There are also some proposals for OWL models of sets and lists to be found at http://swan.mindinformatics.org/spec/1.2/collections.html What would be the best way to model this?
}}
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{{Modeling Issue Template
|Author=EvaBlomqvist, JeffWaters, BobFerris,
|Domain=General, Decision-making, Parts and Collections,
|CompetencyQuestion=What is the first element in this ordered list? What is the next element after this one? What criteria has been used to order the elements?
|Scenario=For instance, we may start out with a dataset about earthquakes, and ask ourselves: What areas are the most prone to earthquakes? Then we would like to order our options, i.e., the areas in the dataset, based on the number or perhaps severity of the earthquakes. In a sense we are re-organizing a set of triples, by ordering them based on some criteria. How do we best represent such orderings?
|ProposedSolution=http://purl.org/ontology/olo/core#
}}
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{{Submission to event
|Event=WOP:2010
}}

Community:Describing Lists and Sublists

2011-02-02T23:40:41Z

BobFerris:

{{TitleDescription Template
|Title=Sublist ontology
|Description=An ontology for describing lits and sublists
}}
{{Graphical representation}}
{{Modeling Issue Template
|Author=BobFerris
|Domain=Parts and Collections
|ProposedSolution=http://scm.trialox.org/main/org.trialox.rdf.ontologies/raw-file/61291aaf8079/src/main/resources/org/trialox/rdf/ontologies/list.rdf, http://purl.org/ontology/olo/core#
}}
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{{My references}}
{{Modeling Issue toolbar}}

Community:Describing Lists and Sublists

2011-02-02T23:40:05Z

BobFerris:

{{TitleDescription Template
|Title=Sublist ontology
|Description=An ontology for describing lits and sublists
}}
{{Graphical representation}}
{{Modeling Issue Template
|Domain=Parts and Collections
|ProposedSolution=http://scm.trialox.org/main/org.trialox.rdf.ontologies/raw-file/61291aaf8079/src/main/resources/org/trialox/rdf/ontologies/list.rdf, http://purl.org/ontology/olo/core#
}}
{{Additional information header}}

{{My references}}
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Community:References/Ordered List Ontology announcement 2

2011-02-02T23:37:28Z

BobFerris: New page: {{Reference |Subject=Community:Ordered Lists |Label=Ordered List Ontology announcement |Description=A blog post about the Ordered List Ontology with examples and graphics. |Type=Other |Typ...

{{Reference
|Subject=Community:Ordered Lists
|Label=Ordered List Ontology announcement
|Description=A blog post about the Ordered List Ontology with examples and graphics.
|Type=Other
|TypeOther=Weblog post
|URL=http://smiy.org/2010/07/15/the-ordered-list-ontology/
}}

Community:Ordered Lists

2011-02-02T23:36:42Z

BobFerris:

{{TitleDescription Template
|Title=Ordered Lists
|Description=This problem originates from the W3C Decision Incubator activity, however it is not restricted to the decision-making domain, but more general.

The problem is how to best represent ordered lists in RDF/OWL. In the decision representation domain the problem arises when modeling options, where one of the options will be selected, i.e., it will be the decision.

RDF contains native constructs for sets and lists. There are also some proposals for OWL models of sets and lists to be found at http://swan.mindinformatics.org/spec/1.2/collections.html What would be the best way to model this?
}}
{{Graphical representation}}
{{Modeling Issue Template
|Author=EvaBlomqvist, JeffWaters,
|Domain=General, Decision-making, Parts and Collections,
|CompetencyQuestion=What is the first element in this ordered list? What is the next element after this one? What criteria has been used to order the elements?
|Scenario=For instance, we may start out with a dataset about earthquakes, and ask ourselves: What areas are the most prone to earthquakes? Then we would like to order our options, i.e., the areas in the dataset, based on the number or perhaps severity of the earthquakes. In a sense we are re-organizing a set of triples, by ordering them based on some criteria. How do we best represent such orderings?
|ProposedSolution=http://purl.org/ontology/olo/core#
}}
{{Additional information header}}

{{My references}}
{{Modeling Issue toolbar}}
{{Submission to event
|Event=WOP:2010
}}

Ontology:Ordered List Ontology

2011-02-02T23:32:39Z

BobFerris:

{{Ontology
|Name=Ordered List Ontology
|OntologyAuthor=Samer A. Abdallah, Bob Ferris
|Description=The Ordered List Ontology Specification provides basic concepts and properties for describing ordered lists as semantic graph.
|SubmittedBy=BobFerris
|OntologyPurpose=To get rid of RDF sequences ;) and to enable typed sequences for special purposes, e.g. playlists
|OntologyURI=http://purl.org/ontology/olo/core#
|LongDescription=There is a need to describe typed ordered lists or sequences of information resources. The existing approach in the RDF vocabulary, rdf:Seq, has some drawbacks regarding defining explicitly a range for items of a sequence and to query them efficiently with SPARQL, because every slot of a sequence is related by a separate property of the form rdf:_N, where N is a positive integer number, e.g. rdf:_1 (cf. RDF Vocabulary Description Language 1.0: RDF Schema and RDF Semantics ). That’s why, I co-designed the Ordered List Ontology according to a proposal made by Samer A. Abdallah. This ontology should overcome the drawbacks of the existing ordered list modelling approach by enabling more semantics to describe sequences of information resources.
As one can see in graphic 'olo:OrderedList concept as graph with relations', the Ordered List Ontology consists of two concepts - olo:OrderedList and olo:Slot. That means an ordered list is a composite of all slots, which are part of this ordered list (related by the property olo:slot). Although, the Ordered List Ontology is OWL based, the ontology also provides "backward" compatibility to the RDFS world.
The initial and primary access method to single slots in an ordered list should be olo:index, because this property represents the fixed index of a slot in an ordered list. Thereby, the property olo:length relates to the length of an ordered list, the number of included slots. The secondary access method is its (currently) optional iterator olo:next as shortcut to the next slot in the list. The items, which are arranged in an ordered list, are associated by the property olo:item to a slot.
On the basis of the ordered list concept defined in the Ordered List Ontology one can define more specific ordered list definitions, e.g. for media playlist (see the Play Back Ontology) or ranked recommendations (see the Recommendation Ontology).
|Justification=To get rid of RDF sequences ;)
|OntologyDomain=Knowledge engineering, Parts and Collections,
}}

{{My references}}

Ontology:Weighting Ontology

2011-02-02T23:28:52Z

BobFerris: New page: {{Ontology |Name=Weighting Ontology |OntologyAuthor=Bob Ferris |Description=The Weighting Ontology specification provides a vocabulary for describing weightings and their referenced scales...

{{Ontology
|Name=Weighting Ontology
|OntologyAuthor=Bob Ferris
|Description=The Weighting Ontology specification provides a vocabulary for describing weightings and their referenced scales, on/ for the Semantic Web.
|SubmittedBy=BobFerris
|OntologyPurpose=To have a concept to describe weights not only with a value.
|OntologyURI=http://purl.org/ontology/wo/core#
|LongDescription=The Weighting Ontology includes a general multiple purpose weight concept. This concept can be used to associate any concept to a wo:Weight instance(s) with the property wo:weight. The second property of wo:Weight is wo:weight_value, which is a simple xsd:decimal based datatype property to associate the numeric value of the weighting.
Furthermore, this ontology includes a wo:Scale, which is modeled as a sub class of scovo:Dimension to relate it to its specified scovo:Item based concept (wo:Weight) via wo:scale. To define the range of this scale the properties wo:min_weight and wo:min_weight can be used. These are sub properties of the related minimum and maximum properties of the Statistical Core Vocabulary (scovo:min and scovo:max) and the Review Vocabulary (rev:minRating and rev:maxRating). Finally one can define a step size (wo:step_size) for the weighting scales.
|Justification=The Weighting Ontology includes a multiple purpose weighting concept on top of Statistical Core Vocabulary.
}}

{{My references}}

Community:References/Info Service Ontology announcement

2011-02-02T23:25:02Z

BobFerris: New page: {{Reference |Subject=Ontology:Info Service Ontology |Label=Info Service Ontology announcement |Description=A blog post about the Info Service Ontology with examples and graphics. |Type=Oth...

{{Reference
|Subject=Ontology:Info Service Ontology
|Label=Info Service Ontology announcement
|Description=A blog post about the Info Service Ontology with examples and graphics.
|Type=Other
|TypeOther=Weblog post
|URL=http://infoserviceonto.smiy.org/2010/06/22/welcome/
}}

Ontology:Info Service Ontology

2011-02-02T23:23:50Z

BobFerris: New page: {{Ontology |Name=Info Service Ontology |OntologyAuthor=Bob Ferris |Description=The Information Service Ontology Specification provides basic concepts and properties for describing differen...

{{Ontology
|Name=Info Service Ontology
|OntologyAuthor=Bob Ferris
|Description=The Information Service Ontology Specification provides basic concepts and properties for describing different information services, e.g. Wikipedia, MusicBrainz, Freebase or Discogs, on/ for the Semantic Web.
|SubmittedBy=BobFerris
|OntologyPurpose=For describing, rating and categorizing information services of all kind.
|OntologyURI=http://purl.org/ontology/is/core#
|LongDescription=The Info Service Ontology consists of a basic is:InfoService concept (which could maybe related to prv:DataProvidingService, bibo:Collection, sioc:Space or void:Dataset instances) and some additional ones for describing such an information service (currently: is:InfoServiceQuality, is:InfoServiceType and is:InfoServiceContributorType – the specific individuals are currently only proof-of-concept examples).

The main hook re. specific websites from an information service is is:info_service, which associates an is:InfoService instance to e.g. a owl:Thing (or e.g. sub class of owl:Thing, e.g. foaf:Document) instance (e.g. a website link).

Furthermore, I defined some is:InfoService individuals, especially isi:musicbrainz (see the graphic above and code below) as proof-of-concept example. Therefore, I used also some category definitions from DBpedia (important is also the property is:main_subject for associating a main subject of an Information Service).
|Justification=There is a need to describe information services of all kind, not only semantic web information services.
|OntologyDomain=Knowledge engineering,
}}

{{My references}}

Community:References/Association Ontology announcement

2011-02-02T23:16:59Z

BobFerris:

{{Reference
|Subject=Ontology:Association Ontology
|Label=Association Ontology announcement
|Description=A blog post about the Association Ontology with examples and graphics.
|Type=Other
|TypeOther=Weblog post
|URL=http://smiy.org/2010/07/26/the-association-ontology/
}}

Community:References/Play Back Ontology announcement

2011-02-02T23:16:23Z

BobFerris: New page: {{Reference |Subject=Ontology:Play Back Ontology |Label=Play Back Ontology announcement |Description=A blog post about the Recommendation Ontology with examples and graphics. |Type=Other |...

{{Reference
|Subject=Ontology:Play Back Ontology
|Label=Play Back Ontology announcement
|Description=A blog post about the Recommendation Ontology with examples and graphics.
|Type=Other
|TypeOther=Weblog post
|URL=http://smiy.org/2010/07/27/the-play-back-ontology/
}}

Ontology:Play Back Ontology

2011-02-02T23:15:14Z

BobFerris: New page: {{Ontology |Name=Play Back Ontology |OntologyAuthor=Bob Ferris, Kurt Jacobson |Description=The Play Back Ontology specification provides basic concepts and properties for describing concep...

{{Ontology
|Name=Play Back Ontology
|OntologyAuthor=Bob Ferris, Kurt Jacobson
|Description=The Play Back Ontology specification provides basic concepts and properties for describing concepts that are related to the play back domain, e.g. an playlist, play back count and skip counter, on/ for the Semantic Web.
|SubmittedBy=BobFerris
|OntologyPurpose=Addresses concepts of a specific media domain, the play back domain.
|OntologyURI=http://purl.org/ontology/pbo/core#
|LongDescription=The Play Back Ontology provides basic concepts and properties for describing concepts that are related to the play back domain, e.g. a playlist, play back and skip counter, on/ for the Semantic Web.

The play back domain could be seen as a subset of the media domain - it deals with playing back some media, e.g. videos, music tracks or slideshows, somehow.

On the basis of this definition the objects that are included into this domain are media objects. That means all concepts of the Play Back Ontology are somehow related to at least one media object. The range of these media objects is currently restricted to the concepts bibo:Document and frbr:Endeavour, incl. all their sub classes, e.g. mo:Track.
The pbo:Playlist concept is a sub class of olo:OrderedList and hence, a specialized ordered list of the media domain. Therefore, a pbo:Playlist instance consists of pbo:PlaylistSlot instances (related by pbo:playlist_slot), which are related to at least one media item by using the property pbo:playlist_item. pbo:Playlist has a further sub class, pbo:FixedPlaylist, to described playlists or sections of playlists, which have a strict order, e.g. a section of music tracks that should be played always one after another, or that are somehow related to each other. Furthermore, pbo:Playlist instances can be related to something by using the property pbo:playlist.
The Play Back Ontology consists further more of a couple of media action counters, which are represented by pbo:MediaActionCounter. Sub classes of this concept are pbo:PlayBackCounter and pbo:SkipCounter. Due to the property pbo:media_object, which is a sub property of co:object, it is possible to only associate media objects to pbo:MediaActionCounter instances.
The Play Back Ontology and the illustrated examples above demonstrates the reutilization, specialization and application of concepts of existing ontologies (Ordered List Ontology, Counter Ontology, Association Ontology, Music Ontology, Similarity Ontology, DCMI Metadata Terms, ...). Please feel free to create further, more specialized concepts and properties, which are based on the introduced ontologies, e.g. describing transition of music tracks in dj mixes (as discussed here).
|Justification=The Play Back Ontology is a an extension of the Ordered List Ontology and the Counter Ontology to represent play back specific concepts and relations.
|OntologyDomain=Multimedia
}}

{{My references}}

Community:References/Association Ontology announcement

2011-02-02T23:12:04Z

BobFerris: New page: {{Reference |Subject=Ontology:Association Ontology |Label=Association Ontology announcement |Description=A blog post about the Association Ontology with examples and graphics. |Type=Other ...

Ontology:Association Ontology

2011-02-02T23:10:54Z

BobFerris: New page: {{Ontology |Name=Association Ontology |OntologyAuthor=Bob Ferris, Toby Inkster |Description=The Association Ontology specification provides basic concepts and properties for describing spe...

{{Ontology
|Name=Association Ontology
|OntologyAuthor=Bob Ferris, Toby Inkster
|Description=The Association Ontology specification provides basic concepts and properties for describing specific association statements to something,e.g. an occasion, a genre or a mood, and enables furthermore,a mechanism to like/rate and feedback these associations
|SubmittedBy=BobFerris
|OntologyPurpose=Providing various general association relation types and a concept for feedback-able personal associations.
|OntologyURI=http://purl.org/ontology/ao/core#
|LongDescription=The Association Ontology combines features of the Similarity Ontology, the Review Ontology and DCMI Metadata Terms. The intend behind this ontology is to provide a mechanism to append (personal) association statements (sim:Association) to something by using the relation sim:association. This step of indirection is neccessary to enable:

* reusable association statements and
* voting, rating and reviewing of association statements in a specific context.

Therefore, the sub class ao:LikeableAssociation was created, which combines the concepts of sim:Association and rev:Review. Simple voting (the "like button") can be realized by using the property ao:likeminded, which creates a relation between an association statement and an individuum (foaf:Agent). Ratings and reviews can be realized by using the features of the Review Ontology, e.g. rev:rating or rev:Feedback.
To address associations of a specific domain, e.g. genre, mood or occasion, new sub properties based on dcterms:subject were created. These are:

* ao:genre: a hook for genres descriptions of all kind,
* ao:mood: a hook for mood descriptions and
* ao:occasion: a hook for occasion descriptions.

They are intendend to be an abstact and general hook into their specific domains (genre, mood, occasion). Furthermore, new, more specific sub properties based on these properties should be created to provide a hook in more specific domains, e.g. mo:genre for music genres/styles (this sub property relation isn't currently the case).
To enable voting, rating and reviewing of a reusable association statements in a specific context, the property ao:included_association was created. By using this relation one can include a reusable association statement into another association statement (preferable based on ao:LikeableAssociation). Please have also a look at the example in this document, which illstrates this use case.
|Justification=The Association Ontology hooks up parts of the Similarity Ontology, the Review Ontology and DCMI Metadata Terms.
|OntologyDomain=Knowledge engineering
}}

{{My references}}

Ontology:Counter Ontology

2011-02-02T23:06:22Z

BobFerris:

{{Ontology
|Name=Counter Ontology
|OntologyAuthor=Yves Raimond, Mats Skillingstad, Bob Ferris
|Description=The Counter Ontology specification provides basic concepts and properties for describing a general counter concept and some important sub counters, e.g. an event counter, on/ for the Semantic Web.
|SubmittedBy=BobFerris
|OntologyPurpose=To describe counters of all kinds and events that are related to a specific counter.
|OntologyURI=http://purl.org/ontology/co/core#
|LongDescription=The Counter Ontology includes a general multiple purpose counter concept. This concept could be uses to associate any concept to a co:Counter instance(s) with the property co:counter or a specific sub property of it. The second property of co:Counter is co:count, which is a simple xsd:integer based datatype property. That means you could use this concept for things like for example play counter, skip counter or website hit counter.
Furthermore, this ontology includes already a predefined property to associate event specific ( event:Event) counter to its related events (co:event_counter,), e.g. a co:ScrobbleEvent to scrobble something. This enables the opportunity to trace back all related events, which are responsible for a specific count. Of course, this is also possible with all other concepts ;)
|Justification=The Counter Ontology is a generalisation of the Playcount Ontology from Yves Raimond.
|OntologyDomain=Knowledge engineering
}}

{{My references}}

Community:References/Ordered List Ontology announcement

2011-02-02T23:05:18Z

BobFerris: New page: {{Reference |Subject=Ontology:Ordered List Ontology |Label=Ordered List Ontology announcement |Description=A blog post about the Ordered List Ontology with examples and graphics. |Type=Ot...

{{Reference
|Subject=Ontology:Ordered List Ontology
|Label=Ordered List Ontology announcement
|Description=A blog post about the Ordered List Ontology with examples and graphics.
|Type=Other
|TypeOther=Weblog post
|URL=http://smiy.org/2010/07/15/the-ordered-list-ontology/
}}

Ontology:Ordered List Ontology

2011-02-02T23:04:03Z

BobFerris: New page: {{Ontology |Name=Ordered List Ontology |OntologyAuthor=Samer A. Abdallah, Bob Ferris |Description=The Ordered List Ontology Specification provides basic concepts and properties for describ...

{{Ontology
|Name=Ordered List Ontology
|OntologyAuthor=Samer A. Abdallah, Bob Ferris
|Description=The Ordered List Ontology Specification provides basic concepts and properties for describing ordered lists as semantic graph.
|SubmittedBy=BobFerris
|OntologyPurpose=To get rid of RDF sequences ;) and to enable typed sequences for special purposes, e.g. playlists
|OntologyURI=http://purl.org/ontology/olo/core#
|LongDescription=There is a need to describe typed ordered lists or sequences of information resources. The existing approach in the RDF vocabulary, rdf:Seq, has some drawbacks regarding defining explicitly a range for items of a sequence and to query them efficiently with SPARQL, because every slot of a sequence is related by a separate property of the form rdf:_N, where N is a positive integer number, e.g. rdf:_1 (cf. RDF Vocabulary Description Language 1.0: RDF Schema and RDF Semantics ). That’s why, I co-designed the Ordered List Ontology according to a proposal made by Samer A. Abdallah. This ontology should overcome the drawbacks of the existing ordered list modelling approach by enabling more semantics to describe sequences of information resources.
As one can see in graphic 'olo:OrderedList concept as graph with relations', the Ordered List Ontology consists of two concepts - olo:OrderedList and olo:Slot. That means an ordered list is a composite of all slots, which are part of this ordered list (related by the property olo:slot). Although, the Ordered List Ontology is OWL based, the ontology also provides "backward" compatibility to the RDFS world.
The initial and primary access method to single slots in an ordered list should be olo:index, because this property represents the fixed index of a slot in an ordered list. Thereby, the property olo:length relates to the length of an ordered list, the number of included slots. The secondary access method is its (currently) optional iterator olo:next as shortcut to the next slot in the list. The items, which are arranged in an ordered list, are associated by the property olo:item to a slot.
On the basis of the ordered list concept defined in the Ordered List Ontology one can define more specific ordered list definitions, e.g. for media playlist (see the Play Back Ontology) or ranked recommendations (see the Recommendation Ontology).
|Justification=To get rid of RDF sequences ;)
|OntologyDomain=Knowledge engineering
}}

{{My references}}

Community:References/Cognitive Characteristics Ontology annoucement

2011-02-02T22:59:52Z

BobFerris:

{{Reference
|Subject=Ontology:Cognitive Characteristics Ontology
|Label=Cognitive Characteristics Ontology annoucement
|Description=A blog post about the Cognitive Characteristics Ontology with examples and graphics.
|Type=Other
|TypeOther=Weblog post
|URL=http://smiy.org/2010/10/19/the-cognitive-characteristics-ontology/
}}

Community:References/Counter Ontology announcement

2011-02-02T22:59:09Z

BobFerris:

{{Reference
|Subject=Ontology:Counter Ontology
|Label=Counter Ontology announcement
|Description=A blog post about the Counter Ontology with examples and graphics.
|Type=Other
|TypeOther=Weblog post
|URL=http://smiy.org/2010/07/26/the-counter-ontology/
}}

Community:References/Counter Ontology announcement

2011-02-02T22:58:49Z

BobFerris: New page: {{Reference |Subject=Ontology:Counter Ontology |Label=Counter Ontology announcement |Description=A blog post about the Counter Ontology with examples and graphics. |Type=Other |TypeOther=...

Ontology:Counter Ontology

2011-02-02T22:57:30Z

BobFerris: New page: {{Ontology |Name=Counter Ontology |OntologyAuthor=Yves Raimond, Mats Skillingstad, Bob Ferris |Description=The Counter Ontology specification provides basic concepts and properties for des...

{{Ontology
|Name=Counter Ontology
|OntologyAuthor=Yves Raimond, Mats Skillingstad, Bob Ferris
|Description=The Counter Ontology specification provides basic concepts and properties for describing a general counter concept and some important sub counters, e.g. an event counter, on/ for the Semantic Web.
|SubmittedBy=BobFerris
|OntologyPurpose=To describe counters of all kinds and events that are related to a specific counter.
|OntologyURI=http://purl.org/ontology/co/core#
|LongDescription=The Counter Ontology includes a general multiple purpose counter concept. This concept could be uses to associate any concept to a co:Counter instance(s) with the property co:counter or a specific sub property of it. The second property of co:Counter is co:count, which is a simple xsd:integer based datatype property. That means you could use this concept for things like for example play counter, skip counter or website hit counter.
Furthermore, this ontology includes already a predefined property to associate event specific ( event:Event) counter to its related events (co:event_counter,), e.g. a co:ScrobbleEvent to scrobble something. This enables the opportunity to trace back all related events, which are responsible for a specific count. Of course, this is also possible with all other concepts ;)
|Justification=The Counter Ontology is a generalisation of the Playcount Ontology from Yves Raimond.
}}

{{My references}}

Community:References/Cognitive Characteristics Ontology annoucement

2011-02-02T22:52:32Z

BobFerris: New page: {{Reference |Subject=Ontology:Cognitive Characteristics Ontology |Label=Cognitive Characteristics Ontology annoucement |Description=A blog post about the Cognitive Characteristics Ontology...

{{Reference
|Subject=Ontology:Cognitive Characteristics Ontology
|Label=Cognitive Characteristics Ontology annoucement
|Description=A blog post about the Cognitive Characteristics Ontology with examples and graphics.
|Type=Other
|TypeOther= Weblog post
|URL=http://smiy.wordpress.com/2010/10/19/the-cognitive-characteristics-ontology/
}}

Community:References/Recommendation Ontology announcement

2011-02-02T22:48:44Z

BobFerris: New page: {{Reference |Subject=Ontology:Recommendation Ontology |Label=Recommendation Ontology announcement |Description=A blog post about the Recommendation Ontology with examples and graphics. |Ty...

{{Reference
|Subject=Ontology:Recommendation Ontology
|Label=Recommendation Ontology announcement
|Description=A blog post about the Recommendation Ontology with examples and graphics.
|Type=Other
|TypeOther=Weblog post
|URL=http://smiy.org/2010/08/07/the-recommendation-ontology/
}}

Ontology:Recommendation Ontology

2011-02-02T22:44:08Z

BobFerris: New page: {{Ontology |Name=Recommendation Ontology |OntologyAuthor=Bob Ferris, Kurt Jacobson |Description=The Recommendation Ontology specification provides basic concepts and properties for describ...

{{Ontology
|Name=Recommendation Ontology
|OntologyAuthor=Bob Ferris, Kurt Jacobson
|Description=The Recommendation Ontology specification provides basic concepts and properties for describing recommendations on/ for the Semantic Web.
|SubmittedBy=BobFerris
|OntologyPurpose=For describing recommendations of all kinds.
|OntologyURI=http://purl.org/ontology/rec/core#
|LongDescription=The Recommendation Ontology is an ontology for modeling high level recommendations on/ for the Semantic Web. Thereby, the ontology hook up parts of the Similarity Ontology, DCMI Metadata Terms, the Association Ontology and the Ordered List Ontology.
The core of the Recommendation Ontology is the rec:Recommendation concept. A rec:Recommendation instance can consist of

* an item or agent relation (rec:Recommendation or its inverse property rec:for) to associate the resource, for which the recommendation was made
* an recommender relation (rec:recommender or its inverse property rec:recommends) to associate the instance, which provided or calculated the recommendation, e.g. an is:InfoService instance
* recommendation object relations (rec:recommendation_object or its inverse property rec:recommended_in) to associate appropriated objects to the recommendation subject
* recommendation audience relations (rec:recommendation_audience to associate groups or stereotypes, which are probably appropriated as target group for this recommendation.

Since rec:Recommendation is a sub class of ao:LikeableAssociation, it is also possible to like (ao:likeminded), rate (rev:rating) or give a feedback (rev:Feedback) to a recommendation. Furthermore, one can also relate detailed association (sim:Association) or similarity statements (sim:Similarity) to a recommendation by using the property ao:included_association.
As an extension of rec:Recommendation, we built the rec:RankedRecommendation concept to enable also ordered (ranked) recommendations at a high level. rec:RankedRecommendation is not only a sub class of rec:Recommendation. Furthermore, it is also a sub class of olo:OrderedList, which enables all features of an ordered list also to this concept. Following this design, a rec:ranked_recommendation is not only a sub property of rec:recommendation_object, but also a sub property of olo:slot. That means the recommendation objects are now related by using the property olo:item.
|Justification=The Recommendation Ontology hooks up parts of the Similarity Ontology, the DCMI Metadata Terms, the Association Ontology and the Ordered List Ontology.
|OntologyDomain=Recommendation,
|Scenario=Federated Recommendations
}}

{{My references}}

Ontology:Cognitive Characteristics Ontology

2011-02-02T22:39:16Z

BobFerris: New page: {{Ontology |Name=Cognitive Characteristics Ontology |OntologyAuthor=Dan Brickley, Libby Miller, Toby Inkster, Yi Zeng, Yan Wang, Danica Damljanovic, Zhisheng Huang, Sheila Kinsella, John B...

{{Ontology
|Name=Cognitive Characteristics Ontology
|OntologyAuthor=Dan Brickley, Libby Miller, Toby Inkster, Yi Zeng, Yan Wang, Danica Damljanovic, Zhisheng Huang, Sheila Kinsella, John Breslin, Bob Ferris
|Description=The Cognitive Characteristics Ontology specification provides a vocabulary for describing cognitive pattern within contexts, their temporal dynamics and their origins, on/ for the Semantic Web.
|SubmittedBy=BobFerris
|OntologyPurpose=Description of personal cognitive pattern in a simple and extended way.
|OntologyURI=http://purl.org/ontology/cco/core#
|LongDescription=The Cognitive Characteristics Ontology includes two opportunities to model cognitive patterns. The first one is the representation of cognitive characteristics by using the semantic relation cco:cognitive_characteristic or better its more specialised sub properties (see graphic cco:cognitive_characteristic property as graph with relations) to associate the topics of the cognitive patterns to the users. The second opportunity is the property-oriented context reification of cco:cognitive_characteristic, cco:CognitiveCharacteristic, which is a general multiple purpose cognitive characteristic concept to describe cognitive patterns more in detail for a specific user or user group.
As one can see in graphic cco:CognitiveCharacteristic concept as graph with relations, the specialised sub properties of cco:cognitive_characteristic, the cognitive patterns, currently are

* interest (cco:interest), that means, a certain area of interest or preference, which is equivalent to foaf:topic_interest,
* compentence (cco:competence), that means, the compentence to (be able to) do or know something or
* setting (cco:setting), often regarding a specific environment, e.g. an application.

One can also refine the semantic relation of a competence association by using the sub properties of cco:competence, which are currently:

* cco:skill: the ability or skill to (be able to) do something, e.g. to walk, to play the piano or to work in a team
* cco:expertise: the knowledge or expertise in a certain domain or a specific topic, e.g. football, programming languages or music
* cco:belief: an uncertain relation for competence representation, that means beliefs, persuasions or opinions, which can also be misconceptions

One can see the second opportunity to model cognitive patterns, cco:CognitiveCharacteristic in graphic cco:CognitiveCharacteristic concept as simplified graph with relations. This concept can be used to associate any foaf:Agent instance to (a) cco:CognitiveCharacteristic instance(s) with help of the properties cco:habit and cco:agent. The topics of a cco:CognitiveCharacteristic instance are related to it by using the property cco:topic, so that a property chain of cco:habit and cco:topic will also direct to topics of a cognitive pattern of an user or user group. That means, a statement that is modelled with the simple semantic relation approach based on cco:cognitive_characteristic can also be represented by an instance of cco:CognitiveCharacteristic, which has a cco:agent or cco:habit, a cco:topic and a cco:characteristic relation. The last property in this row is used to associate the applied cognitive pattern relation (sub properties of cco:cognitive_characteristic).
Different statistics can be made on cognitive characteristics. These are currently:

* cco:overall_weight, which reflects the overall interest in a topic and should be different from the actual weight (associated by the property wo:weight) of a cognitive characteristic
* cco:longest_duration, which is the longest continuous interval of attention for a cognitive pattern, e.g. for an interest, if it appears in the following years: 1990, 1991, 1995, 1996, 1997, 1998, 2001, then the longest duration is 4 years
* cco:ultimative_duration, which is the overall duration of attention for a cognitive pattern, e.g. for an interest, if it appears in the following years: 1990, 1991, 1995, 1996, 1997, 1998, 2001, then the longest duration is 7 years

Besides these statistics, one can also associate a concrete activity (by using the property cco:activity), to differentiate e.g. between football playing (topic = football; activity = playing) and football watching (topic = football; activity = watching), and further statistical items (by using the property cco:statistical_item) to a cognitive pattern description, which is itself also a sub class of scovo:Item.
It is also important, to be able to describe dynamics of a cognitive characteristic. In the Cognitive Characteristics Ontology they can be described with help of the cco:CharacteristicDynamics concept, which is a sub class of wo:Weight, and can be related to a cco:CognitiveCharacteristic instance by using the property cco:characteristic_dynamics. Thereby, one can relate

* concrete appear times (time instants or intervals, by using the property cco:appear_time), when a cognitive pattern gets attention by someone, or
* an evidence description (by using the property cco:evidence), where this characteristic or dynamics was derived from.

to a cco:CognitiveCharacteristic or cco:characteristic_dynamics instance.
Due to the two modelling opportunities of cognitive pattern in the Cognotive Characteristics Ontology, there is a need for formal semantics to associate statements with a shortcut relation and instances of the reification class that belonging together or to infer such knowledge with a reasoning engine. The Property Reification Vocabulary fulfil these requirements.
|Justification=The Cognitive Characteristics Ontology is built on top of the Weighted Interests Vocabulary v0.5 and should probably substitute this ontology in the near future. That means all concepts and properties are imported from this ontology. Some of them are also redefined and renamed to broaden their meaning. Furthermore, the Cognitive Characteristics Ontology is inspired by the Unified User Context Model, the General User Model Ontology, the User Modelling for Information Retrieval Language and all their fundamental sources, and finally, the discussions on the FOAF developers mailing list.
The Weighted Interests Vocabulary v0.5 is an union of the Weighted Interest Vocabulary, the E-foaf:interest Vocabulary and the Interest Mining Ontology. That means, all interest related ontologies are now merged under one hood and some concepts are proper modeled now. The design of this interest ontology is also strongly influenced by the outcome of the User (weighted) Interests Ontology working group from Hypios VoCamp Paris 2010.
|OntologyDomain=Personalization
|Scenario=User Profiling
}}

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Community:Recommendation

2011-02-02T22:26:50Z

BobFerris:

{{Domain Template
|Name=Recommendation
|Description=Recommendation is the subject of recommender systems (see [http://en.wikipedia.org/wiki/Recommender_system Recommender system @ Wikipedia])
}}
{{List of ontologies of this domain}}
{{Additional information header}}
Recommendation is the subject of recommender systems, which "form or work from a specific type of information filtering system technique that attempts to recommend information items (movies, TV program/show/episode, video on demand, [http://ontologydesignpatterns.org/wiki/Community:Music music], books, news, images, web pages, scientific literature such as research papers etc.) that are likely to be of interest to the user.

Typically, a recommender system compares a [http://ontologydesignpatterns.org/wiki/Community:Personalization user profile] to some reference characteristics, and seeks to predict the 'rating' that a user would give to an item they had not yet considered. These characteristics may be from the information item (the content-based approach) or the user's social environment (the collaborative filtering approach)." (see [http://en.wikipedia.org/wiki/Recommender_system Recommender System @ Wikipedia]).
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Community:Recommendation

2011-02-02T22:25:48Z

BobFerris:

{{Domain Template
|Name=Recommendation
|Description=Recommendation is the subject of recommender systems (see [http://en.wikipedia.org/wiki/Recommender_system Recommender system @ Wikipedia])
}}
{{List of ontologies of this domain}}
{{Additional information header}}
Recommendation is the subject of recommender systems, which "form or work from a specific type of information filtering system technique that attempts to recommend information items (movies, TV program/show/episode, video on demand, music[1], books, news, images, web pages, scientific literature such as research papers etc.) that are likely to be of interest to the user.

Typically, a recommender system compares a [http://ontologydesignpatterns.org/wiki/Community:Personalization user profile] to some reference characteristics, and seeks to predict the 'rating' that a user would give to an item they had not yet considered. These characteristics may be from the information item (the content-based approach) or the user's social environment (the collaborative filtering approach)." (see [http://en.wikipedia.org/wiki/Recommender_system Recommender System @ Wikipedia]).
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Community:Personalization

2011-02-02T22:24:41Z

BobFerris:

{{Domain Template
|Name=Personalization
|Description="Personalization involves using technology to accommodate the differences between individuals. Once confined mainly to the Web, it is increasingly becoming a factor in education, health care (i.e. personalized medicine), television, and in both "business to business" and "business to consumer" settings."(see [http://en.wikipedia.org/wiki/Personalization Personalization @ Wikipedia])
}}
{{List of ontologies of this domain}}
{{Additional information header}}
Personalization utilizes user profiles.

"A user profile (userprofile, or simply profile when used in-context) is a collection of personal data associated to a specific user. A profile refers therefore to the explicit digital representation of a person's identity. A user profile can also be considered as the computer representation of a user model.

A profile can be used to store the description of the characteristics of person. This information can be exploited by systems taking into account the persons' characteristics and preferences. For instance profiles can be used by adaptive hypermedia systems that personalise the human computer interaction.

Profiling is the process that refers to construction of a profile via the extraction from a set of data.

User profiles can be found on operating systems, computer programs, [http://ontologydesignpatterns.org/wiki/Community:Recommendation recommender systems], or dynamic websites (such as online social networking sites or bulletin boards)." (see [http://en.wikipedia.org/wiki/User_profile User Profile @ Wikipedia])

See also [http://en.wikipedia.org/wiki/Personalization Personalization @ Wikipedia]
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Community:Personalization

2011-02-02T22:23:49Z

BobFerris:

{{Domain Template
|Name=Personalization
|Description="Personalization involves using technology to accommodate the differences between individuals. Once confined mainly to the Web, it is increasingly becoming a factor in education, health care (i.e. personalized medicine), television, and in both "business to business" and "business to consumer" settings."(see [http://en.wikipedia.org/wiki/Personalization Personalization @ Wikipedia])
}}
{{List of ontologies of this domain}}
{{Additional information header}}
Personalization utilizes user profiles.

"A user profile (userprofile, or simply profile when used in-context) is a collection of personal data associated to a specific user. A profile refers therefore to the explicit digital representation of a person's identity. A user profile can also be considered as the computer representation of a user model.

A profile can be used to store the description of the characteristics of person. This information can be exploited by systems taking into account the persons' characteristics and preferences. For instance profiles can be used by adaptive hypermedia systems that personalise the human computer interaction.

Profiling is the process that refers to construction of a profile via the extraction from a set of data.

User profiles can be found on operating systems, computer programs, recommender systems, or dynamic websites (such as online social networking sites or bulletin boards)." (see [http://en.wikipedia.org/wiki/User_profile User Profile @ Wikipedia])

See also [http://en.wikipedia.org/wiki/Personalization Personalization @ Wikipedia]
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Community:Recommendation

2011-02-02T22:21:39Z

BobFerris: New page: {{Domain Template |Name=Recommendation |Description=Recommendation is the subject of recommender systems (see [http://en.wikipedia.org/wiki/Recommender_system Recommender system @ Wikipedi...

{{Domain Template
|Name=Recommendation
|Description=Recommendation is the subject of recommender systems (see [http://en.wikipedia.org/wiki/Recommender_system Recommender system @ Wikipedia])
}}
{{List of ontologies of this domain}}
{{Additional information header}}
Recommendation is the subject of recommender systems, which "form or work from a specific type of information filtering system technique that attempts to recommend information items (movies, TV program/show/episode, video on demand, music[1], books, news, images, web pages, scientific literature such as research papers etc.) that are likely to be of interest to the user.

Typically, a recommender system compares a user profile to some reference characteristics, and seeks to predict the 'rating' that a user would give to an item they had not yet considered. These characteristics may be from the information item (the content-based approach) or the user's social environment (the collaborative filtering approach)." (see [http://en.wikipedia.org/wiki/Recommender_system Recommender System @ Wikipedia]).
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{{Domain toolbar}}

Community:Personalization

2011-02-02T22:17:05Z

BobFerris: New page: {{Domain Template |Name=Personalization |Description="Personalization involves using technology to accommodate the differences between individuals. Once confined mainly to the Web, it is i...

User:BobFerris

2011-02-02T22:15:21Z

BobFerris:

{{User Template
|FirstName=Bob
|LastName=Ferris
|Gender=Male
|Picture=bferris_100x100.png
|HomePage=http://smiy.org/
|Organization=SMI
|OrganizationType=Non Governmental Organization and Association
|Country=Germany (DE)
}}
{{Account Request Template
|Motivation=I co-developed various helpful Semantic Web ontologies and vocabularies, see

http://purl.org/ontology/olo/core#
http://purl.org/ontology/co/core#
http://purl.org/ontology/ao/core#
http://purl.org/ontology/pbo/core#
http://purl.org/ontology/rec/core#
http://purl.org/ontology/is/core#
http://purl.org/ontology/wo/core#
http://purl.org/ontology/cco/core#
http://purl.org/ontology/prv/core#
|PossibleMainContribution=To help other users to solve modeling problems
|DomainsOfInterest=philosophical engineering, knowledge engineering, music, personalization, recommendation
|ExpertOfDomains=ontology engineering, music
|HowDidIKnowAbout=surfing the web
}}
believe in music to survive

Community:Knowledge engineering

2011-02-02T22:14:06Z

BobFerris:

{{Domain Template
|Name=Knowledge Engineering
|Description=Knowledge Engineering is an engineering discipline that involves integrating knowledge into computer systems in order to solve complex problems normally requiring a high level of human expertise (see [http://en.wikipedia.org/wiki/Knowledge_engineering Knowledge Engineering @ Wikipedia]).
}}
{{List of ontologies of this domain}}
{{Additional information header}}
See also [http://en.wikipedia.org/wiki/Knowledge_engineering Knowledge Engineering @ Wikipedia])
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Community:Knowledge engineering

2011-02-02T22:13:22Z

BobFerris: New page: {{Domain Template |Name=Knowledge Engineering |Description=Knowledge Engineering is an engineering discipline that involves integrating knowledge into computer systems in order to solve co...

{{Domain Template
|Name=Knowledge Engineering
|Description=Knowledge Engineering is an engineering discipline that involves integrating knowledge into computer systems in order to solve complex problems normally requiring a high level of human expertise (see http://en.wikipedia.org/wiki/Knowledge_engineering).
}}
{{List of ontologies of this domain}}
{{Additional information header}}
See also [http://en.wikipedia.org/wiki/Knowledge_engineering Knowledge Engineering @ Wikipedia])
{{My references}}
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Community:Philosophical engineering

2011-02-02T22:09:59Z

BobFerris: New page: {{Domain Template |Name=Philosophical Engineering |Description=I guess that Tim Berners-Lee introduced this term back in 2006, or? See also http://www.impactlab.net/2006/03/25/interview-wi...

{{Domain Template
|Name=Philosophical Engineering
|Description=I guess that Tim Berners-Lee introduced this term back in 2006, or? See also http://www.impactlab.net/2006/03/25/interview-with-tim-berners-lee/
}}
{{List of ontologies of this domain}}
{{Additional information header}}
"This is where Web engineering, physics, Web science and philosophical engineering meet. Physics was actually called experimental philosophy at Oxford.

The Web is now philosophical engineering. Physics and the Web are both about the relationship between the small and the large.

In physics, to take the behaviour of gases as an example, you visualize them as billiard balls, model the rules they follow and then transpose that to a larger scale to account for the effects of temperature and pressure - so physicists analyze systems. Web scientists, however, can create the systems.

So we could say we want the Web to reflect a vision of the world where everything is done democratically, where we have an informed electorate and accountable officials. To do that we get computers to talk with each other in such a way as to promote that ideal." (see http://www.impactlab.net/2006/03/25/interview-with-tim-berners-lee/)
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User:BobFerris

2011-02-02T21:56:41Z

BobFerris:

{{User Template
|FirstName=Bob
|LastName=Ferris
|Gender=Male
|Picture=bferris_100x100.png
|HomePage=http://smiy.org/
|Organization=SMI
|OrganizationType=Non Governmental Organization and Association
|Country=Germany (DE)
}}
{{Account Request Template
|Motivation=I co-developed various helpful Semantic Web ontologies and vocabularies, see

http://purl.org/ontology/olo/core#
http://purl.org/ontology/co/core#
http://purl.org/ontology/ao/core#
http://purl.org/ontology/pbo/core#
http://purl.org/ontology/rec/core#
http://purl.org/ontology/is/core#
http://purl.org/ontology/wo/core#
http://purl.org/ontology/cco/core#
http://purl.org/ontology/prv/core#
|PossibleMainContribution=To help other users to solve modeling problems
|DomainsOfInterest=philosophical engineering, knowledge engineering
|ExpertOfDomains=ontology engineering
|HowDidIKnowAbout=surfing the web
}}
believe in music to survive