Philippe, Sam et Al : Seeking clarification ..
Is it true to say : the real distinction between an Archetype and an Ontology is that - the role of an Archetype (item) is to provide contextual constraints the role of an Ontology (item) is to provide conceptual constraints an Ontology (item) concept can be applied as an Archetype (item) constraint an Ontology item must have object oriented properties e.g. it is composed an Archetype item must have data (info) properties e.g. it has a type a Set of Archetype items (whether or not linked to a template) may have info properties that are the equivalent of a particular Ontology (but not explicitly asserted) carl <quote who="Philippe AMELINE"> > Hi Sam, > > The structured langage is not a direct mapping from natural langage. It > is a tree of concepts ordered from generic to specific. > > Example (sorry if I don't use the proper medical terms in english) : > > polyp > -- location > ---- left colon > -- size > ---- 3 mm > -- aspect > ---- pedonculated > > This tree means that you have found a "pedonculated polyp whose size is > 3 mm in the left colon" > polyp, location, left colon, size, mm, aspect, pedonculated are concepts > taken from the ontology > > If you want to make a natural langage sentence out of the tree, you will > have to put it in a grammatical generator if order to put all its parts > at the right place in a sentence. > > Building a generic model for this polyp description tree is absolutely > the same work as making an Archetype in openEHR, except that you > directly build the Archetype with "semantical concepts" instead of > abstract information mapped to terminologies. > You can keep some mappings if you want to put automatic classification > at work (for example, this polyp can be classified in ICD) but this > mapping is no longer a semantisation concept. > > The ontology is a genuine component, and each time you put one of its > term in a tree, you automatically get a bunch of inherited properties, > for translation purposes, for example. > > Cheers, > > Philippe > > Sam Heard wrote: > >> Philippe >> >> Thank you for this...very informative and I am starting to see how we >> are converging with your work. >> >> I believe that the 'structured terminology' - fils guide down from the >> archetype nodes - is an important part - SNOMED are trying to address >> it generically (ie without archetypes) - I doubt this is possible in >> one language - and it is certainly not in other languages. >> >> From my experience with health one, French is particularly suited to >> the approach that you are taking as qualifying terms (such as >> adjectives) tend to follow their nouns and the subject, verb, object >> structure is usual in sentence. I know that moving to English - where >> qualifiers precede, that such an approach has to be more sophisticated >> - and in other languages it is far more complex. >> >> What is called for is getting to grips with some key archetypes for >> interoperability - from a range of stakeholders - and then really >> having a close look at where more complex terminology is sought. One >> place I have no doubt it is required is in anatomy....how you describe >> the location of a lesion or mass. Another is the characteristics of a >> mass or lesion..... >> >> The high level 'smarts' you are talking about are impressive - and I >> do not know about this end of things. >> >> Cheers, Sam >> >>> Hi Thomas, >>> >>> The very word we are talking about here is Knowledge management. >>> Archetype and ontology are some (very strategic) components, but are >>> not the "whole thing". >>> >>> From my point of view, Knowledge management is a superset of (at >>> least) 2 concepts : artificial intelligence (AI) and smart data >>> management. >>> An example of smart data management is the ability, when you expect a >>> document of 'A' type and that a document of 'B' type arrives, to >>> check if 'A' -is a-> 'B' or 'B'-contains->'A', in order to close the >>> goal "get a A". >>> >>> So, Knowledge management doesn't only mean expert systems or smart >>> agents, but a system that is globally aware of what it manages. >>> >>> In Odyssee, the ontology is the very kernel of the systems, since it >>> is the langage used to tell the patient health journey, but also to >>> represent the internal knowledge. >>> The AI components are structured around a Blackboard (we started from >>> Stanford's BBK, now largely adapted) that federates smart agents. >>> The smart data management components are everywhere else, for example >>> in the data model and interfaces management. >>> >>> This (somewhat long) introduction to tell that, in the way we use it, >>> Archetypes are data model elements and Fils guides are interface >>> elements of the smart data management category. >>> >>> A Fil guide is a multi-purpose information element aimed at answering >>> the question "what can I do now ?" for something/someone that is >>> somewhere in a tree (multi-purpose isn't it ;o)). >>> So a Fil guide is made of two parts : a path (in the form >>> colonoscopy/description/polyp or colonsocopy/*/polyp or */polyp) and >>> a content (currently in the form of a list of ontology concepts that >>> can allow to bring the description one step further, but it can be >>> anything else - say an html page or a function pointer). >>> >>> When you describe something in the medical field, if there is a >>> genuine "gold standard" description, you have to use a deterministic >>> approach, since the user has to be compliant to the standard. This >>> description becomes part of the information system reference model >>> through an Archetype. And the instanciated data remember the mold >>> (Archetype) they come from. >>> But in most cases, there is just a fuzzy expertise, and you can just >>> say something like "being where you are, an expert would keep on the >>> description that way" : it is tipically what a Fil guide will do. You >>> have many Fils guides in a big bag, and when the user is somewhere, >>> you find the more relevant Fil guide (if any) : more relevant means >>> the one whose path is the semantically closest from user actual >>> current path. But the Fils guides are just oppostunistic description >>> support in a non deterministic domain. So the data don't remember the >>> Fil guide they come from. >>> >>> This (too) long description to explain that Fils guides neither >>> belong to the reference model, nor to the ontology, but are interface >>> components in a knowledge management system. >>> >>> Currently, we have nearly 3500 Fils guides, but most of them are used >>> for our report management system and should be replaced with >>> archetypes. >>> >>> By the way, the Fil guide engine, that decides which Fil guide to >>> throw, can also decide to throw an Arcehtype if the user has entered >>> a part of domain where a deterministic description should occur. And >>> you also can go beyond the leaves of an Archetype using Fils guides >>> (or just using the ontology by hand). >>> >>> I hope that all this is understandable ;o) >>> >>> Philippe AMELINE >>> >>> >>>>> Hi, >>>>> >>>>> >>>>> I just forgot to tell you that our ontology has "only" 50 000 terms >>>>> (it means less than 50 000 concepts, since a concept can be >>>>> represented by several terms). As you may have understood, the >>>>> ontology contains only "basic concepts", since complex concepts are >>>>> expressed through a small tree. >>>>> 50 000 is more than a standard medical dictionary (say a dictionary >>>>> + anatomical terms + drugs international standard names), so it >>>>> really represent the words used in the medical domain. >>>> >>>> >>>> to clarify a bit: in Philippe's system, there are 50,000 concepts in >>>> a compositional terminology, as well as the "fils guides" (guide >>>> paths) whch are little structured post-coordination rules defining >>>> legal ways to put the 50,000 concepts together in coordinated tree >>>> structures. This combination of a small, clean lexicon, and the fils >>>> guides are what makes Philippe's approach to terminology so >>>> exciting, in my view. Philippe - one question I have never asked - >>>> how many fils guides do you have currently? >>>> >>>> - thomas -- Carl Mattocks co-Chair OASIS (ISO/TS 15000) ebXMLRegistry Semantic Content SC co-Chair OASIS Business Centric Methodology TC CEO CHECKMi v/f (usa) 908 322 8715 www.CHECKMi.com Semantically Smart Compendiums (AOL) IM CarlCHECKMi - If you have any questions about using this list, please send a message to d.lloyd at openehr.org
