To: | "[sio-dev] discussion" <sio-dev@xxxxxxxxxxxxxxxx> |
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From: | Ali Hashemi <ali.hashemi+ontolog@xxxxxxxxxxx> |
Date: | Wed, 7 Apr 2010 11:01:51 -0400 |
Message-id: | <n2h5ab1dc971004070801nd8874503na7a1453fe095ee6a@xxxxxxxxxxxxxx> |
On Tue, Apr 6, 2010 at 6:27 PM, Cameron Ross <cross@xxxxxxxxxxxx> wrote: Dear Cameron, Thanks for the question. I can provide three general use cases, and one concrete example. General Use Case 1) Ontology Design Tool (ODT) Motivation: I am what an ontologist / knowledge engineer would call a "domain specialist" or a "subject matter expert." I have extensive experience in my field and want to formalize my knowledge. I don't have the time nor desire to become an expert in logic, but I want to be able to express my work in a machine readable format that is shareable with others in my field and might possibly ease interface with those in fields peripherally related to mine. Goal: Provide a mechanism for a SME to formalize intuitions. Actors: User + ODT Triggers: Need for formal axioms Pre-requisites: COLORE Solution: Using the inbuilt advantages afforded with a formal language at least as expressive as first order logic, we can communicate with the SME using examples (tarski-models) only, and navigate the repository to find the best set of axioms which correspond to their intuition. Base Course: 1) The user logs into COLORE. (it only works on COLORE atm) 2) The user names the relation(s) she wishes to formalize 3) User provides at least one example of their relation in "action" - essentially a Tarski style model. The model can be represented visually, or inputted as a plain text (see referenced papers for more on this). 4) ODT searches the ontologies in the repository (COLORE) to find "Core-Hierarchies" and bounds in each hierarchy that match the user's intuition. 5) For each Core Hierarchy, ODT presents a Tarski style model in the same representation that the user inputted. 6) The user decides if this example corresponds to their intuition. 7) repeat 5-6 until search space exhausted 8) Present user with axioms for their intuition. For a more detailed explanation of how this works, please see Chapter 4 of my Master's thesis, or for a very brief version, this paper: http://stl.mie.utoronto.ca/publications/design-repository.pdf , or for something in between, wait for an upcoming journal paper. Chapters 1-3 of the thesis discuss the repository and how the media that is logic on the web allows all this to happen. ======================================== 2) Semantic Mapping Tool (SMT) - Same Domain Motivation: I am an organization who has developed an ontology and would like to interface said ontology with one developed by others. I need to determine what / how and where our ontologies overlap. This works for any number of ontologies, not just two. Goal: Given test mapping axioms, determine how two or more ontologies are "similar" and "different." Actors: User + SMT Triggers: Interoperability Pre-requisites: COLORE Solution: Create an image for each target ontology in the repository. Exploit repository structure to determine "similarity" and "difference." Again, this only works on COLORE, and requires at least first order expressivity. Base Course: 1) User logs into COLORE 2) User provides candidate mapping axioms. I.e. the user guesses that A is related to B, but is unsure how and to what extent, wants to see how A is in fact related to B. (This can also be automated...) 3) SMT generates an image of the user's target ontologies in COLORE, given the mapping axioms 4) SMT analyzes images to determined "Similarity" and "Differences" in the target ontologies 5) SMT provides the user with partial interpretations of the ontologies into one another and into COLORE (in some cases, SMT performs automatic abduction). For more on this, see chapter 5 of my Master's thesis or alternatively, wait for an upcoming journal paper. The definition of "Similarity" and "Difference" in the thesis are a bit outdated, you'll have to wait for the journal paper for the most up-to-date definitions. ======================================= 3) Semantic Mapping Tool - Interdisciplinary Discovery / Sharing Motivation: I want to know if knowledge developed in some other domain is useful for me. Can I reuse work done by others in a seemingly disparate field? Is there a way to get around the research silos and specialized jargons that have popped up? i.e. cell diffusivity and permeability being similar to electrical resistivity... Essentially, I want to discover 'conceptual or structural metaphors' that connect disparate domains to one another. Goal: Support interdisciplinary knowledge sharing. Actors: User + SMT Triggers: Interoperability Pre-requisites: COLORE Solution: The exact same as Use Case 2, except the target ontologies are from different domains. Again this exploits a basic advantage that the medium of logic affords us :P Base Course: see above use case 2. ====================================== 4) Concrete Use Case - Reseed Reseed is a non-profit organization seeking to transform how people relate to space, land and food. There are three vectors to this organization: (1) Community Intervention by Example (i.e. actual urban farming) (2) Education and Knowledge Sharing (relevant to ontolog - the technology side of collecting, collating and sharing gained wisdom) (3) Effect Policy Change in Government and Business Very brief overview -- food security is becoming an increasingly important issue; we often fight against nature instead of learning how to best work with it; people in urban environments often don't have a connection to the land they live on, nor are they connected to the provenance of the food they eat. To address this, reseed wants to incorporate permaculture principles ( http://en.wikipedia.org/wiki/Permaculture ), to bring farming into urban environments. Take a moment and ask why every house has green front lawn? It is a relic from Edwardian England (or before, I forget). A green lawn demonstrated that one was wealthy enough to set aside land for no purpose but to be green and short.... In this day and age, our widespread adoption of lawns seems a bit absurd, especially in light of the resources they divert, consume and larger looming environmental considerations... In effect, in Ontario at least, a green lawn is a forest in its infancy. It is why weeds love it, as they are nature's way of trying to increase the biomass density en route to re-establishing a forest, and ultimately, it is why they present an ecological and economic drain... But I'm beginning to digress. Basically, the relevant (to ontolog) technology integration strategy of reseed includes developing an online knowledge resource for people to share their experiences of urban farming, and for new comers to learn the basic principles and apply them to their local context. For example, wisdom from the Amerindians that almost disappeared with their genocide a few hundred years ago, suggested that Corn, Beans, Squash and a few other plants should be grown together. The corn grows quickly and provides a base for the beans to sprout, while the squash, broccoli etc. provide protection to the roots of these plants from hard rain and larger creatures. All three together help mitigate the need for leaving land fallow... Anyway, capturing and sharing this knowledge is valuable. Not only that, but being able to take as input certain contextual (i.e. local) variables regarding climate: i.e rainfall, temperature, humidity etc. allows our system to suggest a number of plants and farming strategies for someone looking to apply the collectively learned wisdom to their local contexts. So to make this more concrete for OOR, Reseed is looking to explore all plant, farming, seed ontologies from the perspective of supporting local farming initiatives. This means: 1) Being able to do a search on related ontologies 2) Be able to browse them to determine if they address our needs. 3) Be able to extract, reuse and/or extend axioms if relevant 4) Create pointers to and from said ontologies 5) Develop a new ontology to support the rest of our technology integration So it is a combination of the above use cases, plus some located on the ontolog wiki. There's a bit more to the reseed use of ontologies, but this email is already long enough and I think it gives a pretty good impression of a use case. Best, Ali -- Founding Director, www.reseed.ca Social Technologies Adviser, www.pinkarmy.org (•`'·.¸(`'·.¸(•)¸.·'´)¸.·'´•) .,., _________________________________________________________________ Msg Archives: http://ontolog.cim3.net/forum/sio-dev/ Join Community: http://ontolog.cim3.net/cgi-bin/wiki.pl?WikiHomePage#nid1J Subscribe/Config: http://ontolog.cim3.net/mailman/listinfo/sio-dev/ Unsubscribe: mailto:sio-dev-leave@xxxxxxxxxxxxxxxx Community Shared Files: http://ontolog.cim3.net/file/work/SIO/ Community Wiki: http://ontolog.cim3.net/cgi-bin/wiki.pl?SharingIntegratingOntologies (01) |
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