Vocabularies & Ontologies: similarities & differences, definitions & structures

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Vocabularies & Ontologies: similarities & differences, definitions & structures
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Recording of a presentation given by Simon Cox (CSIRO) and Nick Car (Geoscience Australia) at the June 2017 AVSIG meeting. Nick and Simon gave an overview of ontologies and vocabularies, using five examples on the vocabulary/ontology spectrum.
Ontology Different (Kate Ryan album) Ontology Continuum hypothesis Similarity (geometry) Bit Data structure Data structure Similarity (geometry)
Web page Spectrum (functional analysis) Slide rule Presentation of a group Implementation Group action Link (knot theory) Code Similarity (geometry) Bit Theory Demoscene Revision control Ontology Different (Kate Ryan album) Spectrum (functional analysis)
Source code Email Functional (mathematics) Demon Information Wage labour Electronic mailing list Set (mathematics) Content (media) Disk read-and-write head Process (computing) Term (mathematics) Gamma function Dublin Core Position operator
Presentation of a group Link (knot theory) View (database) Web page Set (mathematics) Numbering scheme Virtual machine Uniform resource locator Hierarchy Revision control Dublin Core Data structure Descriptive statistics
Principal ideal Standard deviation Greatest element Presentation of a group Latin square Multiplication sign 1 (number) Sheaf (mathematics) Turtle graphics Mereology Semantics (computer science) Formal language Data model Object (grammar) Ontology Core dump Error message Social class Physical system Link (knot theory) Touchscreen View (database) Temporal logic Web page Moment (mathematics) Electronic mailing list Menu (computing) Bit Term (mathematics) Numbering scheme Element (mathematics) Virtual machine Hand fan Category of being Curvature Right angle Quicksort Ranking Data structure Geometry Web page Slide rule Asynchronous Transfer Mode Implementation Inheritance (object-oriented programming) Service (economics) Link (knot theory) Real number Virtual machine Maxima and minima Content (media) Number Time domain Revision control Frequency Centralizer and normalizer Latent heat Root Information model Network topology Term (mathematics) Representation (politics) Boundary value problem Model-driven engineering Codierung <Programmierung> Data structure Gamma function Normal (geometry) Computing platform Condition number Domain name Addition Execution unit Standard deviation Scaling (geometry) Information Interface (computing) Core dump Semantics (computer science) Advanced Boolean Expression Language Word Integrated development environment Ontology Logic Network topology Normed vector space Revision control Social class
Slide rule Execution unit Link (knot theory) View (database) Linked data Interior (topology) 1 (number) Moisture Content (media) Term (mathematics) Slosh dynamics Category of being Duality (mathematics) Digital photography Network topology Personal digital assistant Normed vector space Process (computing) Data structure
Execution unit Link (knot theory) Information Visual system Moisture Maxima and minima Moisture Knot Uniform resource locator IRIS-T Synchronization Boundary value problem Gamma function Matrix (mathematics)
Link (knot theory) View (database) Linked data Point (geometry) Sampling (statistics) Code Bit Electronic mailing list Sample (statistics) Ontology Different (Kate Ryan album) Ontology Data structure
Online help Point (geometry) Code Similarity (geometry) Electronic mailing list Word Sample (statistics) Ontology Different (Kate Ryan album) Term (mathematics) Ontology Cuboid Data structure Default (computer science)
Information management Texture mapping Code Transport Layer Security Point (geometry) Electronic mailing list Sampling (statistics) Code Electronic mailing list Sample (statistics) Ontology Term (mathematics) Ontology Computer worm Data structure
Email Source code User interface Programmable read-only memory Interior (topology) Sampling (statistics) Code Core dump Dynamic random-access memory Content (media) Demoscene Negative Binomialverteilung Duality (mathematics) Hardy space Sample (statistics) Ontology Oval Ontology Revision control Abstraction Social class
Installation art Code Programmable read-only memory Analogy Electronic mailing list Student's t-test Content (media) Type theory Ontology Gamma function Normal (geometry) Abstraction Social class Physical system Data type Theory of relativity View (database) Point (geometry) Moment (mathematics) Sampling (statistics) Electronic mailing list Code Mass Library catalog Similarity (geometry) Sample (statistics) Ontology IRIS-T Social class Data structure Vacuum
Web page Email Code View (database) Electronic mailing list Turtle graphics Metadata Ontology Core dump Social class Data type View (database) Building Point (geometry) Sampling (statistics) Electronic mailing list Code Menu (computing) Landing page Similarity (geometry) Type theory Category of being Word Error message Sample (statistics) Ontology Personal digital assistant Data structure
Point (geometry) Link (knot theory) Code Euler angles Multiplication sign View (database) Denial-of-service attack Electronic mailing list Product (business) Data model Term (mathematics) Ontology Core dump Finitary relation Social class Metropolitan area network World Wide Web Consortium View (database) Building Point (geometry) Electronic mailing list Sampling (statistics) Code Line (geometry) Instance (computer science) Type theory Data management Data model Sample (statistics) Ontology Mixed reality POKE Social class Data structure
so this talk was prompted by not asked and I say we research is another's popping it ask what's the difference between a vocab Rhian or ontology and so there's a bit of a pun going on there in the title here but vocabularies ontology z' and similarities and differences definitions and structures so there's a continuum here I'm going to talk about that the mini agenda just that Simon
will introduce a bit of theory about vocabularies and Matala T's and their similarities and differences and then we're just going to step through five implementations of vocabularies you've seen it UT they're very impressive I'm too thin we're going to go through five that are on that spectrum and then we'll just conclude in the minute or so so I'm related to you and Nick and I were preparing this this morning so it's not necessarily going to be that slick anyway um yeah it's great that we've just had the presentation that we just saw we're probably going to be looking a little bit more behind the scenes here and yeah so I'm seeing slide two great just to motivate it first we'll take a look at a simple vocabulary there's two approximately similar versions of the well of almost the same thing here if you'd select that first link thanks Nick I are we going can people see the web pages on us showing probably off no idea so I know we're going to be laughing I think I'm showing I don't know do I look back to the browser and we're just not
going to have to see things in presentation to it that will work okay yeah I don't have any transitions so it
it's okay yes yes yeah so if you just scroll up to the doctor so we see the headers there this is a a list of
so-called agent roles the list this list I think comes from the dublin core list so if you scroll down now you see that there's a you know a whole set of kinds of functions that a person or a job position might have in respect to some information resource so you know all those those terms on the left would make sense if you just scroll up just just so we can see the headings here what we're looking at here is a Scott a very flat discussed vocabulary where each of the items you could click through but you won't find much on those as just basically got a label and a
definition or description with with no hierarchy here at all and thanks less looks like the dublin core set the other link that we had back in the presentation there is a related set
which comes from the geographic metadata standard you'll see almost all the same
words there may be a few more in there funder and mediator and and these things as well but again this is just a flat list principal investigator there's a cool one right so this comes from a more scientific domain so this is just this is formatted just in scores as we heard from the previous if you go back again nick to the presentation as we heard from the previous that that's the one i wanted to see the the previous presentations cos gives you a basic hierarchical vocabulary structure the in the left here this is literally the definition of Scott's concept as it comes in the scoffs standard in the RDF representation of that on the right you see a sort of a pseudo UML picture of the clasts ghost concept and all the properties that might be from that and a note for those people who are already familiar with emphasis and vocabulary standards and scoffs is not a full implementation but is certainly inspired by or the intention is to provide an RDF compatible implementation of the well known ISO thesaurus vocabulary standards have noted there that 2 7 double 8 and 5 9 6 4 which everyone kind of knows and loves or this is vaguely aware of race has relatively recently been replaced by 2 5 9 6 4 so a scoffs cons that's the definition of scoffs concept actually flip through to number 6 first actually Nick so here's an example from a vocabulary which I've been managing working on for a number of years now got papers written about was published through the syslog service which we developed at CSI our own path Perth and there you see in all its glory the definition of something called the Cambrian which is May those of you from the natural environmental sciences would be aware that that's something important in geology it's a time period which started 542 million years ago and ended 488 million years ago so you know well well before any of us were aware but it's it's very much a central part of historical geology you can describe the Cambrian using Scots and that's an attempt at doing it there and you see there's quite a lot of relationships there narrower broader broader transitive that's the the next step out it's this particular one is taken from a resource which is the International stratigraphic chart from 2016 also we've got lots and lots of labels for that in different languages and including some non Latin language languages which you can see down at the bottom there ok so flip back to number 5 please Nick we've worked on the gory details of what a Geo chronologic era is which is the Cambrian is one of those and you can design a much more semantically rich information model for that which is shown pictorially on the right there and on the left if that's the the turtle encoding of the RDF implementation of that as an hour class and you see that in bolded in the middle there I've said we got to say that a geologic run logic error is a scoffs concept it's a subclass of that all geo chronologic errors are also scoffs concepts but we've also got a whole bunch of additional geology specific properties added in there and if you flip down to number seven now Nick so that same individual Cambrian which before I showed just as a scoffs concept when you add in the additional of additional properties which come from geology like the rank of this thing that it's got a beginning and end which comes from temporal topology basically and that it that that it is an interval and contains other ones and this it's end is coincident with the end of something smaller and it's beginning is constant at the beginning of something smaller and it nests inside all those things that's all those bolded properties that are on the right-hand side so that the beauty of this technology platform the IDF platform is that if you only want to think of it in terms of scores you can do that which is what I showed on that slide six but if you want to all the additional semantics that you get when you really head into doing it as a full-on geo chronologic gyro which is also as you see there a proper interval from the time ontology then those can be added in without without getting in the way of viewing it just as a simple concept and in the past I've published these through vocabulary services with the idea that when viewed purely as vocabulary fodder if you like you can use any info use you can query it using all of the scoffs properties but it if you are a geologist and you know more about what this concept really means then you can query it or view the information about it using the richer properties and in the previous presentation we saw flipping within the pool party environment I well actually no as in your interface wasn't it or maybe it was pool party looking at it through the Scot interface but then she said you had all the additional clinical properties associated with the drug what it was what what what what what it was designed what conditions it was designed to treat which would obviously go way beyond the semantics that you just have in the simple knowledge organizational system or scarce so we're really in the work that we're doing is trying to preserve the anchor back discuss while also providing the using the possibilities that you get from from vocabularies sorry from from owl and ontology and of course those those concepts I showed in slide five the definition of geologic era itself would need to be published in some kind of register of ontology definitions and that could a list of things like chronologic era and stratigraphic section and gee chronologic boundary themselves would form a richer kind of vocabulary of vocabulary of those geologic time terms so pass over to you now Nick and you can flip through those examples alright just before I do that I'll just mention that it's course itself for those who are unfamiliar these are actually an ontology just happen to be an ontology about folk and root so no one will start up on the screen for a moment things that are formalized in ontology x' can be formalized spots and other ontology because scots itself is one of those sorts of ontology so I'm going to skip over a couple of slides a little bit short on time but I'll just talk to them very quickly so one of the first examples of the first example here is the global agricultural schema core and that's just a very big flat scoffs vocabulary so it's got a lot of terms in there it's delivered with a tool that's similar to there's a different tool to the pool party tool that we saw before and it's definitely needed both Gabriel and so it's vocab real ontology there the next one and so of course people can click on these links in my time in your CD interface that's provided it does have machine readable version that had HTML web pages and so on but it's it's definitely in vocab real and now to logic time scale Simon's actually talked about that so we'll skip on over but just reminder that it's both the vocabulary and plus has got a couple extra fan tickets another similar one is a and observed property located at Simon's also worked on and I will click on this one because it's going to if I do it right show us
so slightly different tool so this is the things Daily Register which someone actually did show before and like both the pool party tool and others it's got various bullying I hope you get around vocabularies and so on and now in this
case this so Cadbury is a vocab
replastered has some other properties and I have to look the slide to remind myself what they are and yes so we could look at and their photos oil moisture
ones we're doing here yes so so here we
go just the information about deep soil
moisture and there are some other things
like features of interest that are related to the turbulent clean knots cause things okay now this next example
example for port is the one I think best highlights vocabulary and ontology differences because it's actually both we've got two things there so the first thing I will show you is a vocabulary that is used to classify physical
samples and that's the vocabulary bit so
you can see in the name here it's got the word box for vocabulary and then separate for that we have an ontology as well and I'll talk about the similarities and differences looking at the vocabulary the circuitry
is got terms by blast the blasters are
method for extracting samples and it's got a whole bunch of other terms in here do is irrelevant to samples maybe you want to use them for and identifying samples dredge texture sample getting thing and this is just a list and it's derived from an XML code list so in the normal way of doing business you can define a code list and then you can take
that code to that linked data and scoffs and now you've got a scoffs vocabulary so that's the code list now the ontology very different beast your ontology is
the active model around in some interests to samples and I'm using an ontology viewing tool here to to
actually turn the ontology into HTML and
text and it tells you about the classes of things that you might want to know
about in relation to this sample or just samples generally and so it's like the ontology sets moments just mentioned and there's some pictures somewhere or other in the documentation that will show us what graphically what the classes of interest we think of interests around a sample are so what click look Betty students that the ontology actor uses
the code list I'm going to show an example from a a live system here which is GA support catalog so what this is
doing is it's it's just a landing page for metadata about a sample and I'm now going to click on the RDF or turtle view of this now I'm wondering if this is going to actually be visible it just as a landmark Nick yeah I know I said I changed that I put it'll go to your downloads page and I can do it manually I got TTL oops text yeah yeah I think this book of course it downloads still hopefully yeah it's going to put together still ok I can't show you folks but I can describe it you can see here this this sampling feature so that's a property oh that's a better class that's related to the sample and it has to determine for holds that's anthology property there's no nothing's cost about that that's a special thing you have to know about samples and ontology and subscribe at the Sun Apple type it's got the word core here and cause the URI and that URI actually links to term within this code list so here we have the ontology
specify some relationship in this case the relationship of sample type and then
that's usually a term from the code list
to actually instantiate that so here we have it on top of you using a poke a buried a probe and available for use to describe samples and the from a management point of view the updates I feels very different mix 15 ontology to be updated very rarely whereas the Kobus we would expect to be attitude quite frequently so the last one I'm not going to demonstrate I'm just going to mention example five this is the probe ontology so it's a core w3c ontology for describing provenance and it is not at all at all a vocabulary and it is a data model and there are no individuals or instances of things that you can refer to directly in product so if you look at the product documentation line you'll see types of you'll see classes that you can you use and so there's a class called entity and you can describe your data items as an entity and link it to people which probably describes an ages that there's no sense in which is a unless been three tools that you could refer to so it's right at the other end of pure ontology not vocabulary okay we've definitely learned our time but that's it so I will stop sharing and hand back to Kim