Re: NeuroNames [was: slides for the UMLS presentation]

Many thanks for weighing in directly on this discussion, Jack.  I  
should have cc'd you myself on this.

Clearly the presentation you sight discussion the following issue is  
one of great relevance to biomedical semantic web projects:

"Where ontological entities carry information resources that speak to  
the same subject, then those entities are merged into a single  
subject map entity -- a subject proxy -- regardless of conflicts  
between messages conveyed."

Such a capability will be critical to merging the top-down  
(ontological) and bottom-up (SW) approaches to KR.  Terminologies -  
and TMRM - clearly play a critical role in the intervening layers  
uniting these approaches.

Cheers,
Bill


On Jun 7, 2006, at 1:21 PM, Jack Park wrote:

>
> Brief comment regarding the topic mapping work Bill mentions here.
>
> Doug Bowden recently participated in a workshop on "Ontology  
> Federation" here at SRI. We had several speakers from both the  
> topic mapping world, and bioinformatics: Douglas Bowden and Peter  
> Karp, and Steve Newcomb, Patrick Durusau, and myself. Vinay  
> Chaudhri opened the workshop and participated. Richard Fikes spoke  
> from the perspective of the KR community. KR lies, of course, at  
> the roots of the work products we all create.
>
> We are moving away from the XTM topic mapping specification, and  
> into the TMRM [1] topic maps reference model, the product of which  
> we now call "subject maps" to distinguish topic maps from a  
> slightly different paradigm. Subject maps are no longer constrained  
> by a preselected ontology (XTM) and can be implemented using key/ 
> value properties of the author's choice. This permits authors to  
> create subject maps that can mimic any frame-like language chosen,  
> including, I suppose, OWL.
>
> There exists a necessary and important tension between the use  
> cases of traditional KR and those for which the topic mapping  
> paradigm has been created and shown useful. When Bill mentions  
> "more semantic web compliant", I would ask questions derived from  
> two important use cases. The two use cases do not circumscribe the  
> entire field of KR, but they serve as place holders to delimit a  
> useful discussion between ontologists and subject mappers. I will  
> argue that both ontologies and subject maps are valuable, and they  
> can serve users together. The two use cases about which I speak are:
>   1- accurately answering questions according to some authority
>   2- understanding some universe of discourse, even where  
> conflicting world views exist
>
> Use of authoritative ontologies is clearly the domain of question  
> answering. Understanding some universe of discourse is also rightly  
> the domain of ontologies, but here, subject maps offer the  
> opportunity to "federate" disparate world views into a unified  
> framework organized around subjects. Where ontological entities  
> carry information resources that speak to the same subject, then  
> those entities are merged into a single subject map entity -- a  
> subject proxy -- regardless of conflicts between messages conveyed.  
> There are benefits to be derived from such merging operations.  
> Patrick Durusau and I spoke to this topic in a teleconference to  
> the Ontolog community [2], and slides and an mp3 of the talk are  
> available. There will be other papers released soon on these  
> opportunities.
>
> It was in the spirit of this federation opportunity that Doug  
> Bowden and I first spoke. To be "semantic web compliant", it is  
> always possible for our subject map portal to carry plenty of RDF  
> metadata. It remains to be answered whether the goal of such  
> metadata is to accurately answer specific questions, or to just  
> advertise the presence of world views.
>
> Bioinformatics, in all of its many manifestations, I strongly  
> believe, will benefit from collaborations between ontologists and  
> subject mappers.
>
> Jack
> [1] http://www.isotopicmaps.org/tmrm/
> [2] http://ontolog.cim3.net/cgi-bin/wiki.pl?ConferenceCall_2006_04_27
>
> William Bug wrote:
>>
>> Hi All,
>>
>> Sorry - I'd thought I'd already subscribed to this list, but  
>> apparently not - until now.
>>
>> The need for a mereotopologically-sound, neuroanatomical ontology  
>> is quite pressing across the community of neuroscientists involved  
>> in neuroinformatics projects most of which include a neuroimaging  
>> component.  Generally there is only one thing neuroscientists are  
>> interested in when analyzing images at whatever resolution from  
>> the macromolecular (EM) on up to the macroscopic - i.e.,  
>> identifying biologically relevant shapes.  In order for these  
>> shapes to have any meaning in a context where one attempts to pool  
>> data and perform relevant data reduction operations, the shapes  
>> must exist within a shared coordinate space of some sort.  For  
>> instance, if two separate labs are examining the change in the  
>> size of the Substantia Nigra during the course of Parkinsonian  
>> neurodegeneration, in order for them to compare their  
>> observations, they require several data integration/semantic  
>> frameworks:
>>     - a shared neuroanatomical terminology
>>     - a shared coordinate space (to place the shapes from their  
>> images in a comparable coordinate framework)
>>     - a shared, well-founded anatomical ontology which  
>> encapsulates mereotopological knowledge about shapes in - at least  
>> - 3D space.
>> Other knowledge resources can be helpful in supplementing this  
>> array of tools, but, generally, these are the absolute minimum.
>>
>> [NOTE: the Wikipedia has a moderately clear definition of  
>> mereotopology (http://en.wikipedia.org/wiki/Mereotopology).   
>> Basically, it combines a formal, ontological theory of shapes and  
>> boundaries (mereology) with the mathematics of topology with the  
>> goal of providing a computational formalism to support applying  
>> logical operations to objects in space.  As has been pointed out  
>> by others, a great deal of the work in this field of applied  
>> biomedical mereotopology derives from related work in the GIS  
>> field.  Use of mereotopology by geographers has been going on for  
>> quite some time and is much more advanced.  Work from GIS can be  
>> adapted for use in the biomedical domain, but it must be done with  
>> great care, as many of the assumptions behind the way researchers  
>> represent space and manner of information being represented can  
>> differ significantly across these disciplines.]
>>
>> The same is true as you scale this problem up to field-wide  
>> projects such as BIRN or The NeuroCommons.
>>
>> As several have mentioned in this thread, there are already  
>> existing resources that can begin to fill this need.
>>
>> 1) NeuroNames
>> Kei, Olivier, Peter Mork, and others have already given sufficient  
>> references on NeuroNames in this thread, so that others can dig in  
>> deeper to the specifics if they like.
>>
>> Having worked with Doug Bowden, Mark Dubach, and their colleagues  
>> over the last year or so in an advisory capacity on the specific  
>> issue of use of NeuroNames for semantically-based, neuroanatomical  
>> data set integration, I can add a few important qualifying points:
>>     a) Doug et al. have been working on the extremely difficult  
>> task of unifying neuroanatomical terminologies across mammalian  
>> species for 20 years now.  Embedded in Neuronames & Braininfo,  
>> there is a wealth of hard won empirical knowledge related to how  
>> one achieves this end.  I think it would be ill-advised to try to  
>> duplicate their effort, as the myriad scientific problems related  
>> to this effort would surely present themselves again and only need  
>> to be worked out once one.
>>     b) Doug et al. are extremely collegial and quite receptive to  
>> feedback and collaboration - within the bounds of their limited  
>> resources.
>>     c) NeuroNames is a terminological resource - not a well- 
>> founded, spatial ontology of brain anatomy capable of supporting  
>> mereotopological reasoning.  As with most research-based  
>> terminologies, there are many semantically-based relations  
>> embedded in the NeuroNames graphs, but as the primary goal of NN  
>> is to disambiguate and integrate across the neuroanatomical  
>> lexicon, the embedded semantic information can often lead to a  
>> logical dead end.  For instance, many neuroanatomical terms  
>> critical to specifying location in the rodent brain have been  
>> placed in the NN category "ancillary terms," as they don't fit  
>> into the core hierarchy in an unambiguous way.  This can make use  
>> of NN for annotating mouse brain gene & protein expression  
>> patterns (e.g., GENSAT, the Allen Brain Atlas, various BIRN  
>> projects) extremely problematic.
>>     d) The NN primary structures (http:// 
>> braininfo.rprc.washington.edu/indexabout.html) provide the closest  
>> thing to an ontology in NN.  As Peter Mork pointed out, there has  
>> been an effort in the past to unite this core NN hierarchy with  
>> the FMA, which does provide a mereotopologically sound framework  
>> for anatomy.  Barry Smith (formal ontologist who has worked for  
>> over a decade on problems in biomedical ontology - most  
>> especially, though hardly exclusively, in the area of  
>> mereotopological reasoning) and his colleagues have worked closely  
>> with the Cornelius Rosse and his colleagues at the FMA project to  
>> create in association with the work started in the FMA a  
>> foundational ontology for biomedicine (the Ontology of Biological  
>> Reality) that is becoming increasingly important to all of the  
>> ontologies being monitored by NCBO and incorporated into the OBO  
>> site and the emerging OBO Foundary (http://obofoundry.org/).
>>     e) Doug and his colleagues have worked closely with Jack Park  
>> (a consulting scientist to SRI's AI Center - http:// 
>> www.ai.sri.com/) to represent NN as a TopicMap (XTM).  As many on  
>> this list may know, there has been a moderate amount of effort to  
>> integrate and/or reconcile XTM with RDF here at the W3C (search on  
>> "TopicMaps" at the main RDF page - http://www.w3.org/RDF/).  I'm  
>> not certain how this effort will ultimately make NN more "semantic  
>> web" compliant, but the bottom line is a great deal of effort has  
>> already been expended to express NN in a semantically well- 
>> grounded formalism.
>>     f) Though - as Don points out - neuroanatomical  
>> representations are likely to significantly evolve over the coming  
>> decades, as the number of large scale gene & protein expression  
>> characterization studies focussed on the brain continue to  
>> accumulate.  Having said that, the "conventional" view of  
>> neuroanatomy will likely remain relevant for a long while to come,  
>> not only because it has been used to characterize findings in the  
>> literature for the last 125+ years, but also because it did derive  
>> from a wealth of empirical observation which is likely to remain  
>> valid in many domains of neuroanatomical study.  I would also  
>> modify Don's well informed comment regarding the derivation of  
>> "conventional" views of neuroanatomy.  To a large extent they are  
>> related to functional studies of the brain - as well as lesion  
>> based studies of functional deficits dating back to the 19th  
>> century (think "Broca's Area"), but they are also very much based  
>> on a study of the morphology of the brain - both the external  
>> surface morphology (sulci, gyri, and lobes), as well as  
>> histological examination of internal structures.  Many of these  
>> studies of structure in space are likely to stay with us for some  
>> time to come (and are well-founded in reality), though as Tim  
>> Clark & Don have pointed out in this thread, nomenclature is still  
>> a very significant problem even in this very "old" field.
>>     g) licensing of NN - Doug et al. formerly had a completely  
>> open policy to distributing NN.  The only a reason a license was  
>> instituted was at some point about 5 years back another group  
>> sucked down the entirety of NN, reworked a lot of what was there -  
>> probably with very practical goals directed toward making NN more  
>> "correct" and effective in their problem domain - then  
>> "republished" their product as "NeuroNames".  This lead to a great  
>> deal of confusion.  The fact they chose to do this on sly also  
>> meant the work they did was not necessarily compatible with the  
>> work done by Doug et al..  In order to avoid this happening again,  
>> it was decided a license would be established to discourage this  
>> sort of behavior.  As anyone who has developed a terminology and/ 
>> or ontology, it is absolutely essential there remain a single  
>> curating authority, if the value of the resource is to remain in  
>> tact.  The "vetting" performed by the central authority - as is  
>> extensively done by the curators of the Gene Ontology, for  
>> instance - is absolutely essential to the guaranteeing the  
>> integrity of the knowledge resource.  This is not a "closed" or  
>> proprietary process, just a highly controlled one.  Unfortunately,  
>> Doug Bowden's resources are MUCH MUCH smaller than those available  
>> to the curators/developers of GO, so the NN curation effort  
>> necessarily moves at a slower pace.
>>
>> 2) Working with the Neuroscience community
>> As Kei, Don, and others have stated, it would be unwise to proceed  
>> in creating an "open source" neuroanatomical ontology without  
>> interacting with the researchers who've already put a lot of  
>> effort into this problem over the past decade or so.  With this in  
>> mind, I have several suggestions:
>>     a) The 5 ways of knowing neuroanatomy:
>>         This is a pitch I've been making which I think helps to  
>> sum up the current ways various sub-fields have attempted to  
>> identify/label/collate brain morphology
>>         i) Terminlogies - e.g., NN, BrainLex
>>         ii) Ontologies - e.g., Neuro-FMA (the project Peter Mork  
>> referred to)
>>         iii) Literature Informatics (CocoMac, BrainMap,  
>> NeuroScholar, BAMS, ArrowSmith, etc.).
>>             These are very mature projects.  Some include their  
>> own mereotopological reasoning systems (e.g., CocoMac and  
>> BrainMap) in order to be able to pool and compare the relatedness  
>> of structures and connectivity across different studies in the  
>> literature.  The goal in this category is to perform large-scale  
>> semantic mining of the literature to confirm/refute current  
>> knowledge and uncover new correlations - very much along the lines  
>> of what The NeuroCommons Project expects to achieve via use of  
>> semantic web technologies.  Some researchers in this category are  
>> actually participating in The NeuroCommons Project (i.e., Gully  
>> Burns, who developed NeuroScholar).
>>         iv) voxel/pixel analysis:
>>             This approach applies computer vision algorithms to  
>> automatically - or semi-automatically - identify 2D & 3D shapes in  
>> digital anatomical images.  This field is also extremely mature,  
>> though there are many significant caveats to exactly how much of  
>> this work can be effectively automated.
>>         v) parameterized models:
>>             Often these are derived from - or used to drive - the  
>> voxel/pixel based analysis described in 'iv' - though the spatial  
>> modeling is definitely a distinct approach from the pure voxel/ 
>> pixel approach.
>>
>> None of studies you'd fit into these categories exclusively focus  
>> on their technique/tool alone without some aspect of the other  
>> "ways of knowing neuroanatomy" playing a role in what they do.   
>> However, it is clear much fundamental work in this area primarily  
>> focuses on one technique over the others.
>>
>> Having said that, when the neuroscience community makes use of  
>> this work to examine a specific biological problem, they will  
>> often draw significant tools and resources from more than one of  
>> these domains.
>>
>>     b) NCBO/NCOR sponsored meeting focused on mereotopology in  
>> neuroanatomy:
>>         Barry Smith is working to bring together researchers  
>> working in the 5 domains described above.  There is a very  
>> pressing need in large-scale, field-wide neuroinformatics projects  
>> such as what is being done in the BIRN project to have these 5  
>> domains converge and work more cooperatively.  Right now, a lot of  
>> manual effort has to be put out to bring them together.  This is  
>> something BIRN has been pursuing.  In the last 6 months, we have  
>> received a great deal of support and guidance on this effort from  
>> NCBO.  Daniel Rubin interacts directly with the BIRN Ontology Task  
>> Force, and the work Barry Smith has been doing with FMA, OBO,  
>> FuGO, and PATO have very much begun to create a much more well- 
>> founded and computable path toward performing large-scale  
>> annotation of neuroimaging data.
>>         This meeting is on the NCBO/NCOR slate for 2007, but in  
>> the interim I hope to see more effort invested in the coming year  
>> across the 5 communities listed above  toward the goal of  
>> integrating across these "ways of knowing" now that the need has  
>> been recognized.
>>            3) Microarrays:
>>     Just as Don, Kei, Alan R., and others have pointed out, high- 
>> throughput assays - microarrays, BAC-based IHC, in situ studies  
>> using the Gene Paint technology employed by the Allen Institute of  
>> Brain Science to construct the Allen Brain Atlas of gene  
>> expression in the brain - are going to transform our understanding  
>> of neuroanatomy over the coming decades.  This is just a given.   
>> There is a pressing need to derive a means to integrate spatially- 
>> mapped studies of gene & protein expression into a neuroimaging  
>> setting. The spatial resolution may be very coarse - e.g., "whole  
>> brain" - but they still provide sufficient spatial information to  
>> be usable in the context of a neuroanatomical coordinate system.
>>     We are working in the BIRN project to create a means for  
>> researchers to integrate these distinct approaches to studying the  
>> brain.  As Alan R. pointed out, FuGO is working to put description  
>> of microarray experiments on a solid, formal footing, and I would  
>> expect one aspect of that will be to represent microarray data in  
>> RDF/OWL.  This is not a trivial problem, given as much of the  
>> available data is merely MIAME-compliant - MIAME not even being a  
>> data format, but just a collection of minimal data requirements.   
>> One need only look at the great complexity of the data submission  
>> process at the NCBI GEO site to get an appreciation for how  
>> difficult this problem can be.  A great deal of effort is being  
>> invested in the microarray field to come up with a better means  
>> handle this issue, and the FuGO effort will be a critical  
>> clearinghouse for this work.  The important thing to remember when  
>> it comes to field-wide data pooling and re-analysis, it may  
>> sometimes be necessary to get right back to the microarray primary  
>> image files so as to reapply different criterial  when performing  
>> the statistical tests and reductions on pooled data.  Given this  
>> requirement - one we also see in the neuroimaging domain - I  
>> believe it is very important to proceed in a well-reasoned manner  
>> when seeking to integrate across microarray datasets using  
>> semantic web technologies.  Alan R. and myself - possibly others  
>> too - on this list are on the FuGO Coordinators Committee, so  
>> hopefully we can help to keep those lines of communication open.
>>
>> Sorry to go on so, but this is a topic on which I've labored quite  
>> intensively over the past year.  There is a lot being done on this  
>> issue, and I think all efforts will get much further more quickly  
>> - and in a way that will carry more street cred with practicing  
>> neuroscientists - if we all try to work together.
>>
>> Cheers,
>> Bill
>>
>> Bill Bug
>> Senior Analyst/Ontological Engineer
>>
>> Laboratory for Bioimaging  & Anatomical Informatics
>> www.neuroterrain.org
>> Department of Neurobiology & Anatomy
>> Drexel University College of Medicine
>> 2900 Queen Lane
>> Philadelphia, PA    19129
>> 215 991 8430 (ph)
>> 610 457 0443 (mobile)
>> 215 843 9367 (fax)
>>
>>
>> Please Note: I now have a new email - William.Bug@DrexelMed.edu
>
>
>

Bill Bug
Senior Analyst/Ontological Engineer

Laboratory for Bioimaging  & Anatomical Informatics
www.neuroterrain.org
Department of Neurobiology & Anatomy
Drexel University College of Medicine
2900 Queen Lane
Philadelphia, PA    19129
215 991 8430 (ph)
610 457 0443 (mobile)
215 843 9367 (fax)


Please Note: I now have a new email - William.Bug@DrexelMed.edu







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Received on Thursday, 8 June 2006 04:37:37 UTC