Ontologies - Science topic

While data based AI is the dominant approach applied in AI, Symbolic AI keep being applied widely.

What do you think are the current existing trends in the Symbolic AI?

I'm currently using R to analyze some metabolomics data, and I'm using the hmdbQuery package to download HMDB entries for each metabolite in my dataset. I'm having some trouble working with the ontology data, though. For example, I would like to ask, "what are all the metabolites (which are in my dataset) which have the Lipid Transport annotation?" This is relatively straightforward with the Gene Ontology database, but with HMDB, I'm not sure how best to deal with the tree structure of the ontology data. Right now, I'm working on writing some elaborate code to dig into each branch of the tree, for each metabolite, and extract and store this information it in a table, but it doesn't seem very elegant. Have any of you dealt with this before?

I believe that it is common knowledge that mathematics and its applications cannot directly prove Causality. What are the bases of the problem of incompatibility of physical causality with mathematics and its applications in the sciences and in philosophy?

The main but very general explanation could be that mathematics and mathematical explanations are not directly about the world, but are applicable to the world to a great extent.

Hence, mathematical explanations can at the most only show the general ways of movement of the processes and not demonstrate whether the ways of the cosmos are by causation, what the internal constitution of every part of it is, etc. Even when some very minute physical process is mathematized, the results are general, and not specific of the details of the internal constitution of that process.

No science and philosophy can start without admitting that the cosmos exists. If it exists, it is not nothing, not vacuum. Non-vacuous existence means that the existents are non-vacuously extended. This means that they have parts. Every part has parts too, ad libitum, because each part is extended and non-infinitesimal. Hence, each part is relatively discrete, not mathematically discrete.

None of the parts of any physical existent is an infinitesimal. They can be near-infinitesimal. This character of existents is Extension, a Category directly implied by the To Be of Reality-in-total.

Similarly, any extended being’s parts -- however near-infinitesimal -- are active, moving. This implies that every part has so (finite) impact on some others, not on infinite others. This character of existents is Change.

No other implication of To Be is so primary as these two (Extension-Change) and directly derivable from To Be. Hence, they are exhaustive of To Be.

Existence in Extension-Change is what we call Causality. If anything is existent, it is causal – hence Universal Causality is the trans-scientific and physical-ontological Law of all existents.

By the very concept of finite Extension-Change-wise existence, it becomes clear that no finite space-time is absolutely dense with existents. Hence, existents cannot be mathematically continuous. Since there is continuous (but finite and not discrete) change (transfer of impact), no existent can be mathematically absolutely continuous or discrete in its parts or in connection with others.

Can logic show the necessity of all existents as being causal? We have already discussed how, ontologically, the very concept of To Be implies Extension-Change and thus also Universal Causality.

WHAT ABOUT THE ABILITY OR NOT OF LOGIC TO CONCLUDE TO UNIVERSAL CAUSALITY?

In my argument above and elsewhere showing Extension-Change as the very exhaustive meaning of To Be, I have used mostly only the first principles of ordinary logic, namely, Identity, Non-contradiction, and Excluded Middle, and then argued that Extension-Change-wise existence is nothing but Universal Causality, if everything existing is non-vacuous in existence.

For example, does everything exist or not? If yes, let us call it non-vacuous existence. Hence, Extension as the first major implication of To Be. Non-vacuous means extended, because if not extended, the existent is vacuous. If extended, everything has parts.

The point of addition now has been Change, which makes the description physical. It is, so to say, from experience. Thereafter I move to the meaning of Change basically as motion or impact.

Naturally, everything in Extension must effect impacts. Everything has further parts. Hence, by implication from Change, everything causes changes by impacts. Thus, we conclude that Extension-Change-wise existence is Universal Causality. It is thus natural to claim that this is a pre-scientific Law of Existence.

In such foundational questions like To Be and its implications, we need to use the first principles of logic, because these are the foundational notions of all science and no other derivative logical procedure comes in as handy. In short, logic with its fundamental principles can help derive Universal Causality. Thus, Causality is more primary to experience than the primitive notions of mathematics.

Extension-Change, Universal Causality derived by their amalgamation, are the most fundamental Metaphysical, Physical-ontological, Categories. Since these are the direction exhaustive implications of To Be, all philosophy and science are based on these.

Bibliography

(1) Gravitational Coalescence Paradox and Cosmogenetic Causality in Quantum Astrophysical Cosmology, 647 pp., Berlin, 2018.

(2) Physics without Metaphysics? Categories of Second Generation Scientific Ontology, 386 pp., Frankfurt, 2015.

(3) Causal Ubiquity in Quantum Physics: A Superluminal and Local-Causal Physical Ontology, 361 pp., Frankfurt, 2014.

(4) Essential Cosmology and Philosophy for All: Gravitational Coalescence Cosmology, 92 pp., KDP Amazon, 2022, 2nd Edition.

(5) Essenzielle Kosmologie und Philosophie für alle: Gravitational-Koaleszenz-Kosmologie, 104 pp., KDP Amazon, 2022, 1st Edition.

Relatively Easily = define 1st, 2nd, 3rd order reasoning ~ keeping context "GENERAL"

for Example, JAS MyWay 1st order Reasoning of Words =

A = About

B = Because

C = Christ

D = Devil

E = Energy

F = Family

G = God

H = Home

I = Indio

J = Just

K = Kill

L = Love

M = Marry

N = Nothing

O = Open

P = People

Q = Queen

R = Real

S = Safe

T = Time

U = Universe

V = Victory

W = Women

X = Xes

Y = Yes

Z = Zoo

This tells you a great deal about my 1st order (public) "cognitive-reasoning", "personality", and "senses". The Second Order is "personal", and the third order is "private". By adding together Semantic Ontologies, a formal Ontology is created, for example... PlayNAC

how these terms used in research methods?

I totally can imagine what a huge potential semantic technologies such as knowledge graphs, ontologies, SPARQL search and automated reasoning might have in different fields of science and engineering. However, apart from biology and medicine (which I have only very little insight on) they seem to be rarely used (e.g. compared to machine learning methods).

Of course it is likely that I am simply unaware of very useful applications of semantic technologies, therefor this question.

More precisely, I am interested in short descriptions which concrete knowldegebase/tool is used and which problem it helps to solve or which question it helps to answer.

QM stands for quantum mechanics, CS for computer science, CC for cellphones/computers, and Mathematics seems to have somehow missed all three.

Now is the time to catch up. We have come to a stand off. Students are ending up neurologically sick -- feeling math-averse (neurophobia and math trauma).

It is not a matter of selection. Only group/rote work [1] seems to infuse Mathematics, as taught today, even in highly-qualified students. Paradoxically, one finds that the more intellectually qualified, the more averse!

And yet current Mathematics still tries to "instruct" it to the students, and other disciplines, in the US and the world.

This failure has been denied [1], and the “fault” has been put on the victims -- the students. Paradigm shifts are needed: first, QM.

According to QM, only integer numbers should be necessary to build all one can see in nature. Otherwise, all of Physics would be contradicted. This would also contradict all of CS and all of CC. Computers, for example, only work with integers, and are error-free.

Since this contradiction is not even imaginable, QM is ontologically correct. Therefore, all sciences must reflect it, according to a "holographic principle" (HP) in nature, including Mathematics.

The HP is often referred to as "the micro as in the macro" or vice-versa.

These two words macro and micro are commonly viewed as antonyms, meaning that they are the opposite of each other. Macro means on a large scale. Micro means on a very small scale. Both are important, though often complementary, views of nature. The view from the macro, while taking into account the micro, is called "universality" in Physics.

The QM main principle was given by Niels Bohr as, "all states at once". This needs to be understood as different from the following possibilities:

In opening the "black box" of QM as viewed by Bohr, QM does not represent Natur (defined by the philosopher Kant), but Wirklichkeit (ditto). It is not how nature is, but seems to work. A story.

A known analogy is the Plato's Cave". The shadows one can see on the wall are Wirklichkeit, and the open reality outside is Natur. After watching Wirklichkeit for some time, people can make an idea what Natur looks like, even though imprisoned in the Cave.

QM is, ontologically, how one can describe Wirklichkeit -- which is the subject of Physics. Natur may not have QM behavior, and continuity may exist in Natur.

Mathematics is not concerned with Wirklichkeit only, but can include Natur. Although, as no one can see Natur, one is led to treat any "pure" Mathematics as a speculation.

Albeit, Mathematics must agree with Physics in the realm of Wirklichkeit.

This does not happen today, and creates a clash. The inconsistency is seen as an opening. What IS mathematics?

Today's calculus teaching can be seen as relying on outdated ideas, going back before QM, computer science (CS), and cellphones/computers (CC) were discovered. Three major paradigm shifts seem to have been missed.

But these three paradigm shifts represent how science is done, in our seemingly endless task in going from Wirklichkeit to Natur.

One recognizes then, that science does not behave continuously, but by jumps -- that break from the past, and open a new future -- in going from Wirklichkeit to Natur, and back -- does the envisioned Wirklichkeit reproduce the actual Wirklichkeit?

This has been called a "paradigm shift" (PS) by T. S. Kuhn in Structure of Scientific Revolutions [2].

David Hilbert [3], at the turn of the XX century, proposed twenty-three problems intended to guide research in the dawning century, claims otherwise, that “History teaches the continuity of the development of science.”

Michael Harris [4], a mathematician, writes that he, "would still be glad to lift the veil, but we no longer believe in continuity. And we may no longer be sure that it’s enough to lift a veil to make our goals clear to ourselves, much less to outsiders."

The outdated ideas currently in Mathematics date back to the time of Newton, Leibnitz, and Cauchy, before the 3 PSs mentioned. They include (aka Fictions, or incorrect models): microscopic continuity, infinitesimals, hyper-reals, Cauchy epsilon-deltas, and Cauchy accumulation points.

Even in 4-year universities one finds classes, such as at Caltech, MIT, CSU, and abroad, teaching Fictions today [1].

This failure can be denied [1], and the “fault” can be put on the victims -- the students. But, there is no feeling of inferiority. PS [2] combats this, American style -- by innovation.

A technical innovation can reduce this gap by a PS [2] -- already heralded and error-free, as one can see in the history of sciences (contradicting David Hilbert [3]).

This reduces risk by following an experimental model that works, even though no one has explained it mathematically, without Fictions.

By jump-starting to QM one has a solution, which we mark as a first paradigm shift.

Where Fictions interfere with known Physics, they must be mercilessly deprecated -- although, and yet, current Mathematics still tries to "instruct" it to the students, in the US and the world.

The other paradigm shifts, stand for computer science (CS), and cellphones/computers (CC).

We now introduce a coherent, holographic principle (HP), a universe, and understanding yet to be discovered, as two new paradigm shifts -- and gain a cosmic perspective: who is the Creator of all this marvelous scheme?

This final PS leads to a comment. One does not need to learn anything, confirms https://www.researchgate.net/profile/Robert-Fuchs

One just has to observe.

Mathematics seems, thus, to be discovered — as a hologram and coherent with other sciences, and not, somehow, invented by mere humans.

What is your qualified opinion?

REFERENCES

[1] https://edsource.org/2022/high-calculus-failure-rates-thwart-students-across-csu/664771

[2] T. S. Kuhn, Structure of Scientific Revolutions, 1962.

[3] David Hilbert, Paris International Congress of Mathematicians (ICM), 1900.

[4 I] Michael Harris, “Mathematics Without Apologies”, Princeton University Press, ISBN 978-0-691-1-17583-6, 2017.

This is a work in progress attempt to crystallise the 3 main ontologies, schools, mindsets and underlying theology, metaphysics if you will, among the "3 Wise Men" (Goodman - UK, Reimann - German, and Jacobson - US) from CoCo. Each of CoCo's founding fathers' learning technologies reflect their nationalities, and by extension, their national universities' concerns and agendas for the learner.

By tracing the underlying "self" of their respective technological formulations, one could delineate their contrasting (sometimes overlapping, ontologies, schools) mindsets and govern-mentalities embedded in their respective learning technologies.

In Goodman's works, there's a preoccupation with space and architecture, notably the need to recolonise monotonous routine driven places. There's a strong streak of Marxist geography found in the works of David Harvey that focuses on redistributing justice and power via spatial arrangements such as design driven planning and regeneration. Through the spatial (re-)arrangement of the learning environment, (To be continued!).

Image Source: https://medium.com/@jeff.appel/the-question-concerning-technology-by-martin-heidegger-1954-22c03bcdeb20

Dear All,

I have created a mind map of a literature review on How Ontology, Epistemology And Axiology Relate To Develop New Knowledge Through Research Methodology And Research Design.

The summary is at :

I want critical comments on my thoughts.

The outline of the finding is as follows and you can follow the above link for a more clear image.

Thank you

Please refer following links of ideas and make critics;

· I found that any research needs to add new knowledge

· That knowledge is resulted from answering a question/s or/and finding a solution/s

· Each problem or solution has its ontology, epistemology, and axiology

· The ontology, epistemology and axiology collectively form a research philosophy while those influence developing research questions or hypotheses or a mix of both regarding the problem or solution.

· As the research philosophy and questions/hypothesis origin from the same sources to both should be conceptually related to each other.

· Then research design is formulated to answer those research questions or hypotheses or a mix of both

· same time the research methodology is underpinning the particular research’s ontology, epistemology, axiology and philosophy continues

· Then research design and research methodology both make the selection of approach in theory development. As well, research design and research methodology make and formulate the rest of the steps in the research.

· After that, the steps are clear. However, the selections of methodological choices, strategies, data collection techniques and analysis techniques are interrelated decisions.

· Finally, all these activities resulted in new knowledge

Hello ReseachGate Community,

I would like to know what are the different techniques to maintain the semantic aspect of the knowledge representation (apart from ontologies).

Best regards,

As it is well known, Linked Opend Data (LOD) and computational ontologies have great success in the fields of Life Sciences (Biology, Medicine, etc). See e.g. the big LS-cluster at <https://lod-cloud.net/>.

However, I wonder why mathematics are – in comparison – covered only sparsely by ontologies or LOD.

Indicators (to the best of my current knowledge):

Probably there is some (machine-processable) formalization of mathematical knowledge but it seems almost disconnected from the "semantic web" and LOD-bubble.

Questions:

Is it because of the concept of "confirmation bias" discussed in scientific studies in social psychology, do studies focus on confirmation rather than falsification?

Is that why journal editors or reviewers tend to reject work that falsifies other studies?

What do you think about that?

My ontology is about medicine(Diseases based on ICD-10,Specialties etc). I have used annotation property rdfs:label but due to the number of concepts it's time consuming process. Is there a way by coding or using some tool to make this process faster? I think that this domain is internationalized not culturally-influenced If I'm not mistaken.

I need the different ways to represent knowledge in enterprises other than ontologies , thanks.

Pattern-Based Security Requirements Specification Using Ontologies and

Boilerplates

Olawande Daramola 1, 2

How to install Jena on your PC, in order to visualise Ontologies?

15. Archaeologies of Identity

Organisers: Gail Higginbottom, Cecilia Dal Zovo, Felipe Criado-Boado

Instituto de Ciencias del Patrimonio (Incipit)

Consejo Superior de Investigaciones Científicas Direction (CSIC)

We invite you to participate in our session. This session wishes to address approaches and interpretations that determine in what ways megaliths & earthworks first became phenomena in particular regions and/or why they didn´t. Connected to this is whether or not people saw themselves as affiliated groups. Indeed, we also want to know why some regions chose one of these phenomenon and not the other within the same temporal span, or gave one precedence over the other. The building of megalithic monuments is a worldwide, time-transcending phenomenon, hundreds of thousands were erected across the World, with some places like the Korean Peninsula holding about 30,000 dolmens. The fact that they still exist in situ, highlights their past and continued relevance in the Cultural Landscape today; it also highlights their on-going collective identities. A similar story is attached to earthworks like mounds, ditches, embankments and pathways and their combinations. Megaliths & earthworks are clearly a dominant form for creating a materiality of social & spiritual engagement across the World. Is it possible that similar material practices mean shared worlds in some regions, and how might we differentiate between this and co-vergent evolution? As these monuments continued to develop through time, it is possible that so too did their meaning(s). Or is this rationale only an assumption, and indeed rather misguided? With such deliberations, this session, then, also wishes to see evidence that might answer this for us, too, or indeed provide evidence for the stability of a cultural practices, meaning and identity through time. Perhaps there is macro and micro evidence that displays stability but the micro reveals the forms of change within local communities. We are seeking works that present ideas related to these themes and which seek to answer questions such as these, or indeed, by default, have done so.

Keywords: Megaliths, Earthworks, Cultural Landscapes, Social engagement, Shared Worlds

CONTACT Email addresses: gail.higginbottom@incipit.csic.es; cecilia.dalzovo@incipit.csic.es

Observing trends in publications related to ontologies and ontology Engineering, they look like most of them, if not all, are application oriented.Even more, when analyzing relatively recent history of this field, one can realize that, for example, during the first decade of the XXI Century, there was an intensive process of looking for new methodologies, and after creation of NeON Methodology, I feel, roughly speaking, nothing more has happened.

Other examples, from the development tools. Several years ago there were several tools competing for the roll of most used editor. Today looks like almost every thing is developed using Protégé. Regarding ontology languages there is a similar "state-of-affairs", even we try to open a debate around that topic last year: https://www.researchgate.net/post/What_are_the_current_trends_in_ontology_languages

What do you think? Hopefully I am wrong...

Ontologies are one of the main current formalism for modelling real world. But there are always reasons for that choice, among them, domain properties and characteristics.

HI everyone,

I am trying to find Ontologies for user modelling and for disabilities, so far I have had little success finding ontology search engines. The only one I managed to locate is https://www.ebi.ac.uk/ols/index which doesn't have the kinds of Ontologies I am looking for. Any pointers will be appreciated.

Thank you.

HI,

I would like to start a discussion about how to apply new technologies to Quran and Hadith. In fact, a lot of information exist in the holy Quran and a lot of these information has been explained through Hadith. A lot of website has been developed give some of these information according to users. Therefore, a lot of data has been generated and they increase day after day.

However, some of these information can be wrong. I have two main questions:

1- what technologies has been used for Quran and Hadith and for what purposes?

2- There are researchers work in this filed and use DataScience (IA, Semantic technologies, Knowledge representation , machine learning and deep learning, etc.)

If you have propositions for a collaborative work you're welcome.

Hind

IFLA's FRBR, Library of congress RDA are thought to be inspired from semantic web philosophies. Is FRBR and RDA are futuristic enough for the future challenges of Web.

Since 2000, beginning with Mizoguchi and Bourdeau seminal publication "Using Ontological Engineering to Overcome Common AI-ED Problems", and other researchers publications, ontologies and semantic web have been applied to Education, mainly in virtual learning environment. Have those applications reached the expected results? What is your opinion?

Where the ontology basically resides in the machine learning techniques spectrum?

Or any places i could look for existing ontologies which are publicly available?

Thank you for all the support!

Within social science research methodology, pragmatism, as I understand it, emphasizes choosing methods based on those most well suited to answer a question without a priori epistemological and ontological stances. However, I am unclear as to how this might play out…

Take for example the topic of poverty. Various questions can be asked about poverty.

(Q1) What is the most effective way of reducing poverty in our city?

(Q2) How do the poor exit poverty on their own terms?

Both questions may best be answered by different sets of methods. Suppose research is completed and published on both questions. Within political discourse answers to Q1 are used to justify a policy of relocating the poor outside of city limits. Q2 is used to justify a policy of providing no strings attached cash transfers. This results in the revelation that we’ve failed to consider what questions should be asked. Thus, axiology is brought into play. However, this is also where I struggle to understand pragmatism.

To justify one’s research question as more important than another’s must a pragmatist must take an axiological stance?

In doing so are they taking the ontological and epistemological view that there is indeed a singular correct set of values?

Alternatively, would the pragmatist not believe their question is any better than another, suggesting multiple equally valid sets of values?

Perhaps I’ve misinterpreted something or my reasoning is flawed but guidance would be much appreciated. Thank you.

My questions came from reading the following articles:

Morgan, D. L. (2007). Paradigms lost and pragmatism regained: Methodological implications of combining qualitative and quantitative methods. Journal of mixed methods research, 1(1), 48-76. doi:10.1177/2F2345678906292462

Biddle, C., & Schafft, K. A. (2015). Axiology and anomaly in the practice of mixed methods work: Pragmatism, valuation, and the transformative paradigm. Journal of Mixed Methods Research, 9(4), 320-334. doi:10.1177/2F1558689814533157

I'm working with ontologies in owl format. According the W3C guide the properties are classified in DatatypeProperty and ObjectProperty. In addition, the properties can be functional, symmetric and transitive. In a bibliography I found three classifications: DatatypePropertys, ObjectPropertys (which could be symmetric or transitive) and FunctionalPropertys. I need to know if any of these classifications (functional, symmetric, transitive) is independent of the ObjectPropertys or they are classifications for the ObjectPropertys.

I am working on ontologies and decision making. I am confused at relating decision tree concepts and ontology files. I request any of you to please suggest an explanation regarding the same.

During the last two decades, ontologies has been one of the main formalisms, applied in domain modeling, and currently one can find ontological representations in almost every field of knowledge.

Consequently, I am looking for a book, which can support teaching in a first course on ontologies, their foundations, development and applications, to college undergraduate students.

I am looking for a way to use otologies with graph database.

Dear all

We are looking for ontologies that have been designed and developed for describing user interface components, UI adaptation. Does anyone know any of the existing User interface adaptation ontologies? Any limitations in these ontologies?

Best Regards

Dear all

We are looking for ontologies that have been designed and developed for describing museum artifacts and objects. Does anyone know any of the existing museum ontologies? Any limitations in these ontologies?

Best Regards

We are developing applications in the area of semantic web of things and I´d like to know more about the use of ontologies in this area.

My friend and colleague from Turin, Maurizio Ferraris, launched a kind of new theory, he called "Nuovo Realismo", or Neo-realism, in the path of Searle, but against his notion of collective intentionality in social ontology. Anyhow I haven't been able to grasp the bulk of the matter. Can someone of you explain me the Pitch of Ferraris Theory of Social Ontology ? Thanks

Ontological types of Competitive Advantage. 

Dear all,

I computed Gene ontology semantic similarity as follows

I took the genes from two different co-expression networks from gene expression dataset. For example

Module 1 : 30 genes

Module 2: 20 genes

Once I had them in hand I used gene ontology software and annotate the genes using biological process category. Later I obtained GO IDs and used GOSEMSIM R package to compute similarities ranges from 0 to 1. This is the data from experiment. Now I want to test GO similarity significance as follows.

I want to check the following : What is the chance of getting the significant GO similarity from two random gene sets of the same sizes?

 I am not getting the way how to do it? specifically how to select the random gene sets of same sizes and calculate the P-values?

Can any body please let me know the exact procedures to do this ?

Thanks, Sai

I have found some suggestions in terms of explanation - that phenomena involving the emergent properties can't be explained using only a relatively lower order vocabulary. But what is a typical ontological "diagnosis" of emergence? Any good readinhg suggestions and answers are greatly appreciated.

My research includes developing an ontology specially designed to be used in jurisprudence information retrieval by a semantic search engine.

I would like to know what metodology is advised to perform such a task.

what are the best references for learning IoT ontologies and how they could be used for auto-discovery of  Smart Things (SThs) integration in the IoT network. and how to building a frame work that use them for searching in the IoT.

Thanks in advance,

Given a customer review R comprising of sentences {s_1, s_2, ..., s_k};

each sentence s_i has a set of features X_i = {x_1, x_{2, ....,} x_n}ⁱ ;

We fit a binary classifier which takes {X_1, X_{2, ....,} X_k} as input and gives sentiment polarity labels {Y_1......Y_k} as output.

There are ambiguous sentences which the classifier is not able to correctly classify. To improve this, we assume that there should be a flow of sentiment within a review, which is broken only under specific conditions.

E.g., a consumer may feel very positive about a laptop, except some of its aspects. So, sentence-after-sentence they say positive things (flow) but then one sentence is negative (flow-violation), marked by either a contrast term like 'but', 'however' etc. or by a strong negative term or both.

One way to check this flow or flow-violation is to use an auto-regression like model.

So, we predict Y values using the classifier. Then, we make corrections for a Y_i using weighted sum of previous predicted labels and current value of Yi. The estimation of weights is a different problem.

However, I want to directly use a sequence of features X_i, X_i-1, X_i-2... in a classifier so it can learn the dependence on previous sentences itself. The problem is that this approach becomes computationally complex due to feature size. Also, manually tuning a auto-regression like function gives better result.

What are other methods that address a problem like flow or flow-violation of sentiment across a series of sentences?

Hello.I have a training dataset in which it has discrete class label but i want result in testing dataset class label as continuous value.So is it possible by using any Prediction algorithm?.Thankyou

If the high degree nodes are sequentially removed from the network, the network quickly fragments into disconnected components. Will similar fragmentation be observed if the nodes with high social capital are removed?

For example Club web dataset for Open Information Extraction 

is bridge rules a good answer to it or evolving MCS are good approach.

Ontologies are recognized as a mean of knowledge modeling and representation in the Semantic Web. Moreover, they have been the subject of several works on the visualization of their content. My question concerns the way in which it would be possible to evaluate a data visualization system in general, and in particular ontology visualization system.

I need to design my case experiments to address both a simple ontology and a complex ontology. How can I quantify ontologies in terms of the number of classes, entities, etc?

When using domain-specific ontologies for describing business collaboration, the used concepts (or more precisely, the value of the concept) may have different contextual interpretations according to the local business context (e.g. for the concept "Price" there is many contextual dimensions : Currency, VAT, Date, etc.)

I am going to classify patents from two different perspective: 1) how much they address a specific pre-determined technological attributes, and 2)how much they address pre-determined market need. That means I am going to do the classification two times and then figure out those patents address the two attributes. I am going to use two ontologies to model the concept of each of the 'technological attributes' and 'market needs'. Also, I am going to use all keywords semantically address those keywords which are determined in the ontologies. I am going to use a lexicon database like WordNet.

Ontologies are playing important role for interoperability in IoT that we can see there are several exist ontologies for IoT but I am just wondering whether it is possible to extend ontology for IoT with trust concept. 

Does anyone has ideas about it? 

Thanks so much. 

how can i align 2 ontologies in protege.

Someone knows some ontologies that have more than 100 SWRL rules?  I would like to run tests on these ontologies in Ph.D.

I only know this ontology:

I'm interested in finding ontologies in the domain of sustainable territories

I need:

1- A set of natural language (NL) rules or a legal text made of NL sentences

2- The formal requirements extracted from these NL rules (or from the legal document)

3- Related resources (e.g terminologies, ontologies) required for the transformaltion NL -> formal expression

For instance, I've found work on ontology matching and ontology mapping but the application is to ontologies at the same level, i.e. a book in an ecommerce catalogue and a book in a library catalogue.

As an example of different levels of description consider the domain health with domain lung cancer. (ill)Heath and Cancer both describe the same underlying phenomena (tumours) but at different levels of description. The health level is a summary or outcome level, the cancer level is an event or process level.

Maybe it would help to think of cancer process as nested within health outcomes.

Description I'm developing an OWL application that uses a reasoner. The classification takes too much time (more than 4 minutes) as I'm treating a relatively large ontology. I don't want to waste this time each time I run the application. The alternate is to save the reasoner inferred model and use the stored inferred one instead of running the reasoner each time.

Let's consider the following ontology:

Example

:A rdf:type owl:Class .

:A1 rdf:type owl:Class ;

rdfs:subClassOf :A .

:A2 rdf:type owl:Class ;

rdfs:subClassOf :A1 .

which asserts that A2 subClassOf A1 subClassOf A.

Problem When I use Protege 5 with some reasoner (e.g Pellet or even Hermit), start the reasoner and save the inferred model with all the available inference options. When I open the inferred model, I see that it doesn't state that A2 is a subclass of A. It only states that it's a subclass of A1. see below what it contains about A2:

A2 rdf:type owl:Class ;

rdfs:subClassOf :A1 .

I want all the implicit knowledge to become explicit. This work by Protege doesn't give me what I want (i.e. don't assert that A2 is also a subclass of A)? What is the problem? Any alternatives?

Remark: Saving the inferred model using some other tool (i.e. Jena or OWLAPI) will solve my problem as well, however, calling their methods to save the inferred model behaves the same way as Protege.

I am proposing a mixed methods approach, and my sub-questions require different approaches. Hence, in the first phase of my study, I have a relativist ontological approach, and in the next phase, my ontology is realist. Is that alright? Does this change need to be justified?

I am trying to develop a semantic search engine that use ontology based query expansion i.e. user entered query keywords are matched to ontology classes and new related concepts will be fetched from ontology. The new information is added to user query to provide better results when we do searching.

I tried to develop some small ontology and tried query expansion approach. My problem is how to cover a whole domain in ontology(like science, arts, engineering, biology etc.)and do semantic search to show utility of approach. Are there any good ontology that can cover a whole domain that i can use with user query for query expansion.

I have to test a novel approach for querying RDF data and also the impact of the triple store on my proposition. So first I tested it on Jena TDB, OntoDB and now I want to test it on RDF-3X but I have no idea for beginning with RDF-3X.

Anybody know if exists some variant of OWL language, specially designed for the spatial domain ontologies. Similar to GeoSPARQL regarding SPARQL.

Greetings.

.

Wonder, what are the applications of ontology matching. How knowledge matched / mapped / aligned with between pairs of ontology can be used. How we can justify the use of both types of knowledge i.e. knowledge which is being found common in both ontology and knowledge which is uncommon between pair of onotology.

Hope I am clear and concise enough to put the Question here....

I'm about to start a new research over this subject. 

I'd appreciate your help if you have some information to share with me.

Thanks in advance;

Eduardo

Hi,

I have a set of ontologies related to Cultural Heritage domain created by technical experts and a textual corpus written by archaeological experts. My problem is that the ontologies need to be filled by archaeological knowledge (that I don't know big things), so I'll use the archaeological texts to try to extract the information needed.

I need your recommendations about methods of information extraction.      

And for ontologies, is there any heuristics to fill an Ontology automatically? (I have the T-Box and I have to generate the A-Box)  

Thank you for your interest,

Best regards.

But do not know if the version I downloaded contains only the Ontology Sumo or other manufacturer's components like Dbpedia, FOAF and other Ontologies that are in sumo.

I am searching for a plug in for Protege to find out the number of class relations and object properties for an existing ontology. Is there any?

The Cartesian view of avowals proposes that the inherent subjectivity of the linguistic act not only establishes its validity but also posits the speaker as the ontological source of the representation. Thus, this view grants an unchallengeable authority to self-ascriptions of mental states. In Speaking My Mind: Expression and Self-Knowledge, Dorit Bar-On argued for a neo-expressivist approach that separates the semantics of avowals from their epistemology. Is it not the case, however, that the conative nature of an avowal as a speech act allows for the expression of feeling, self-knowledge, etc., without actually involving any claim that the avowal is veridical?  If one utters, “I am tired,” could the utterance function as an indirect speech act to persuade a response in the hearer? In such an instance, would the avowal, contrary to the Cartesian view, be truth-apt and challengeable?

Is there any domain ontologies (in owl format) which capture the educational concepts in the JAVA programming course or c++ ?

what is the best ontology editor for the beginner?

such as Protege, OntoEdit; or is there any other visual ontology editor?

In his Treatise, Hume refers to "a progress of the sentiments" (Book III, Sec. II). As I understand this, he takes it that we may develop a bona fide commitment to justice such that it can supplement or even contravene the private interests that originally gave rise to it (i.e., justice being a product of artifice). I take him to be making an ontological claim here rather than a historical one, particularly as he appears to regard our “suppos’d state of nature” as "mere philosophical fiction". Is there an alternate interpretation?

I am dealing with ontologies and I need patient ontology as soon as possible

I mean: in a state of exception all legal categories collapse, and at the end of day the same act can deserve a medal or be deemed high treason. In this way it represents, according to me, a pure political world, where the law is suspended. 

From my viewpoint the law is to a large extent an ontology, a weaponed ontology, establishing the things composing the stuff of the world : goods, persons, properties, absolute rights, agreements, deeds, covenants, contracts, and so on.

Then it seems to me that a pure political state has no ontology, and as such is completely shapeless, and it works only through decision and mobilisation. 

This would also be practically important in the US constitutional law, since the Supreme Court maintains that a "political question" can not be justiciable.

As such the nature of the political seems to lie outside the law in a realm of pure ontological ambiguity where all things get confused, precisely at the opposite of a world governed by the rule of law, which needs, first of all, a fixed social ontology to establish its own domain.

Is such a sharp opposition between the legal and the political, in ontological terms, sustainable or not ? And where it can bring us to?

I have information annotated with concepts from ontologies, all stored into RDF store. To conduct a semantic-based search using concepts hierarchies, I use SPARQL queries. I noticed that more the query is becoming complicated more it takes more time to be executed. Is there any solutions to index and optimize ontologies-based search.

Regards.

Dear All

could you help me in finding some existence rule bases? No idea about its implementing. I am working with ontologies in protege and I need some knowledge bases to deal with it. if the implementing is important please lead me for some appropriate ones.

If there is not such rule bases could you help me how to create them? (creating them is not focus just want to test ideas)

ps. better if the knowledge bases  are in medical domain

Please I need help on how to go about classifying documents using WEKA. I am doing classification of dissertations of my department. The assignment is to do an Ontology-based classification of 250 dissertations against Gartner's Hype cycle. The aim is to determine which field of IT each dissertation falls into.

Thanks

As above.

I'm interested in any resources that can support the following 3 tasks:

1) cross-lingual information seeking (e.g., query formulation support, searching, browsing, retrieving, or evaluating search results in either work or leisure contexts);

2) bilingual cataloguing (e.g, entering electronic catalogue data, performing subject analysis, classification or indexing);

3) translation support for either of the above.

Specifically, I'm looking for concrete examples of bilingual thesauri; bilingual corpora; alligned or parallel corpora; machine-readable dictionaries; databanks, taxomonies, ontologies or other authoritative lists of terminology; and perhaps, translation aids or links to useful site that contain any of the above.

If you've ever used or seen such resources and could comment on how authoritative, useful, and/or helpful you found them to be, could you please post your suggestions, pointers to research, and/or links. Much obliged! VR

Few people would go further to highlight indigenous ontology within scholarship. Can anyone share their definition of indigenous ontology and its application within academic studies?

I am Working on Protege Tool for constructing ontologies. I can say that is semi-automatic. Can you suggest the ways to do it automatically?

I already know that there exist several ontologies for describing e.g., comments like http://www.openannotation.org/spec/core/core.html, or SIOC, but I could not find an ontology that covers all kinds of social data activities of one object(including tags, ratings, shares, comment,...).