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

[Deana Pennington]

At first glance, this looks good, Ferdinando.  I'll try take a closer 
look at it before the end of the week.  Deana

Ferdinando Villa wrote:
> 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
>
>   


-- 
********

Deana D. Pennington, PhD
Long-term Ecological Research Network Office

UNM Biology Department
MSC03  2020
1 University of New Mexico
Albuquerque, NM  87131-0001

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