[seek-kr-sms] Ideas for discussion: shared development of ontologies

Sergey Krivov Serguei.Krivov at uvm.edu
Thu Jan 11 07:51:07 PST 2007


Interesting, I do not remember if I ever came across of Topic Maps and I
feel like I am just learning this idea. Here is a paper that I found to be
an easy and quick introduction to the subject:
http://ausweb.scu.edu.au/aw02/papers/refereed/fitch2/paper.html
It explains TM and RDF together. There  are seems already "standard"
approaches to RDF <->TM conversion:
http://www.w3.org/2002/06/09-RDF-topic-maps/

What is more relevant to Ferdinando's proposal is that there are already
some takes on Owlification of TM:
http://xml.coverpages.org/CreganTMs-OWL200505.pdf
In fact this paper describes a proposed ISO standard of TM semantics in OWL.
(Of course, we need something opposite to the process of Owlfication of TM,
we need something for TMization of OWL files.  If TM have clear semantics
this should be possible.) Superficially the mentioned ontology  looks very
close to Ferdinando's prototype, save for the operational components of the
prototype, which are of course most important.

Sergey

*******************************************************
Sergey Krivov, Research Assistant Professor, 
Computer Science Department,
Fellow of Gund Institute for Ecological Economics,
University of Vermont,
617 Main St. Burlington VT,
05405



> -----Original Message-----
> From: seek-kr-sms-bounces at ecoinformatics.org [mailto:seek-kr-sms-
> bounces at ecoinformatics.org] On Behalf Of Ferdinando Villa
> Sent: Wednesday, January 10, 2007 1:01 PM
> To: 'Deana Pennington'; 'Josh Madin'; 'Shawn Bowers'
> Cc: seek-kr-sms at ecoinformatics.org
> Subject: [seek-kr-sms] Ideas for discussion: shared development of
> ontologies
> 
> Hey all,
> 
> continuing the discussion of last week on approaches to enable
> collaborative
> ontology development, Banff paper and all. Here are a few thoughts from
> last
> week's explorations - hope you can make sense of them. I'm prototyping
> some
> of these things for Thinkcap (see below). Obviously we want something
> simple
> for the first cut we've been discussing, but it's good to agree on a
> consistent strategy before. See what you think and please send feedback!
> If
> you have urgent points please share before end of the week - I'll be
> traveling 1/14 to 1/27.
> 
> Cheers ferdinando
> 
> ---
> 
> * Considerations on choice of "substrate" data structure for shared
> knowledge development:
> 
> Ontologies are "distilled", minimal statements whose success depends on
> lack
> of redundancy and very exact logics. Such crystalline structures are a
> very
> suboptimal substrate for group discussion.
> 
> Concept maps are just at the other end: very flexible, free association,
> therefore good for collaborative brainstorming with appropriate
> interfaces;
> but lack of "direction" make conceptual drift a risk and there is no
> built-in mechanism for either ensuring that topics are appropriately
> handled
> and to ease the merging of the discussion back into the ontology.
> 
> Topic maps (TM: http://www.topicmaps.org) have several advantages:
> 
>    1. a little more structured than concept maps: topics, associations and
> occurrences, with roles and scopes. Not much, very intuitive, but quite
> powerful. Good info also at www.ontopia.com.
>    2. relatively formal and with an ISO standard, but much simpler and
> without the logical constraints of OWL; supported by several tools and
> APIs
> (can be loaded in cmaptools, JAVA interfaces available, serializers into
> XML
> and text languages, permanent storage engines available).
>    3. have a notion of type for topics, associations and roles of topics
> in
> associations, allowing to constrain the pathways of the discussion into
> useful tracks.
> 
> * Proposal:
> 
>    1. define an ontology of association roles and types that is optimal to
> guide generation and analysis of TM that represent formal knowledge
> domains.
>    2. identify a pathway to define an initial topic map from a conceptual
> space defined as OWL (can cross ontology boundaries within knowledge base
> and define arbitrary boundary concepts). This can happen using profiles
> that
> map relationships and restrictions into topics and associations, with
> relative documentation. The structure of the ontology can be relaxed and
> documented selectively (only documented and relevant
> concepts/relationships
> become part of the TM). The only constraint is that all topic are
> associated
> to exactly one formal concept.
>    3. define a search/edit/add process over the TM and not over the
> ontology. New topics associated by users must use the association types
> and
> roles predefined in the ontology that informs the TM process.
>    4. Topics can be added by users to represent restricted or generalized
> versions of concepts, documentation including URLs, documents, papers,
> examples (see below). The core TM ontology informs a wizard to make adding
> topics and associations intuitive and meaningful.
>    5. Define a process to preprocess the collaboratively edited concept
> maps
> and collect direction of the discusssion into likely changes to the
> ontology, to inform an administrative interface. Facts about the desired
> direction of the conceptualization in the community are collected as RDF
> during editing, using listeners for topics and associations.
> Reasoner-mediated process classifies these facts and prepares a set of
> suggestions and key points for the administrators' attention. Analysis of
> topics and editing process also constantly redefines weights of concepts
> in
> search engine.
>    6. The TM is stored permanently on server and becomes the reference for
> the community process. All text searches (thinkcap-like) are done on the
> topic map and related addressable resources, not on the ontology any more;
> results always point to an OWL class as well as the related topics.
> 
> * Example taxonomy of association roles that can be used by system and
> users
> to inform association interface and OWL <-> TM translation (very
> preliminary, to be discussed):
> 
> AssociationRole
>     AnnotationRole
>         Comment
>         Criticism
>         DocumentationResource
>         Example
>         Explanation
>         SourceIdentification
>     ConceptualRole
>         Generalization
>         Restriction
>             CanBe
>             IsAlso
>             MustBe
>     ContainmentRole
>         PartOf
>     ContextualizationRole
>         DisciplinaryLocation
>         SpatialLocation
>         TemporalLocation
>     IncarnationRole
>         InstanceOf
>     OntologyModificationRole
>         LinearConceptOperation
>             AddConcept
>             MergeConcepts
>             ModifyConcept
>         RestructuringOperation
> 
> * Action points:
> 
>    1. define TM ontology for translating OWL <-> TM and to guide the
> shared
> collaboration (prototype available
> http://www.integratedmodelling.org/ks/topicmaps/tm.owl).
>    2. define initial process to translate a bounded portion of a concept
> space (ontology or other, using boundary concepts) into TM using TM
> ontology
> and optional translation profile (XML). Being prototyped in Thinklab as we
> speak.
>    3. define strategy for indexing and browsing of TM in similar way as
> ThinkCap does now; TM substitutes the current direct indexing of ontology.
> Each topic always links to a concept.
>    4. define UI to enable collaborative editing of TM. Relatively major,
> but
> can start small - two screen panes, find or create one topic in each,
> association wizard uses TM ontology to guide associations.
> 
> 
> --
> Ferdinando Villa, Associate Research Professor, Ecoinformatics
> Ecoinformatics Collaboratory, Gund Inst. for Ecol. Economics and Dept. of
> Botany
> University of Vermont           http://ecoinformatics.uvm.edu
> 
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