By Zulugrel - 11.02.2020
Ontology network meaning
Share this item with your network: In general, ontology (pronounced ahn-TAH-luh-djee) is the study or concern about what kinds of things exist - what entities. The ontologies on the Web range from large taxonomies categorizing Web sites (such A bottom-up development process starts with the definition of the most.
Ontology network meaning topic is currently receiving special attention not only from an active community of ontology network meaning from many areas of informatics, but also from the industry, which is providing increasing budgets and investments to develop this technology ontology network meaning to enhance its applicability in business settings.
In computer science terms, an ontology comprises a set of definitions of concepts, properties, relations, constraints, axioms, processes and ontology network meaning that describe a certain domain or universe of discourse.
By providing this body of definitions about a domain, an ontology enables applications ontology network meaning software agents to use the precise, clear, formal semantics to process the information described by the ontology and to use this information in intelligent applications.
Many areas of computer-based applications are now taking advantage of ontologies: knowledge management, electronic commerce, tutoring and geographic systems, e-government, among many other application areas.
Ontology research and practice has recently received a very strong boost from the idea of the Semantic Web, popularized by Tim Bernes-Leethe key inventor of the today's World Wide Web.
Berners-Lee defines the Semantic Web here a Web in which the software will "understand" and process data from the pages, according to the context of this data .
Ontologies constitute the backbone of the Semantic Web, as they are responsible for providing this context. A Web page then cars btcc 2019 touring an ontology about the domain that this page refers to, and a software agent that handles the page can use the precise semantics of these definitions to process the information.
While ontology researchers have made many advances in recent years, many key challenges still must be addressed, including topics such as ontology interoperability and diversity, engineering methodologies, Semantic Web standard and practices, and other challenging issues.
Given the huge variety of readers of this Special Issue, which span from undergraduate students to senior researchers and IT practitioners, this extended editorial aims at providing the readers a brief description of the field, giving a flavor of ontologies' rich history and application possibilities, as well as the interesting research that is taking place and its challenges to overcome.
The end of the editorial brings an outline of the articles of this Special Issue, which by no means reflect all the research topics and applications of the field in growth, but rather sketch a portrait of part of the ontology research that is taking place in Brazil now.
Since new applications and opportunities are flourishing, we hope that this Special Issue and this text motivate the readers, and especially those from the Brazilian research and industrial community, to join the large group of researchers who devote their efforts to the development of ontology technology.
His definition focuses on the point that ontologies are declarative structures "explicit" and must depict update windows electrum from a certain domain or universe of discourse "conceptualization".
An interesting point in that definition is its abstraction: this web page does not commit unnecessarily to any way in which the specification is actually carried out.
This definition, however, does not make explicit, some of the key features and benefits of ontologies, which were already present in KSE's work and in the field as a whole: applicability of ontologies in deductive systems, in agent communication and their role in standardizing knowledge.
In order to comprise these features, Gruber's ontology network meaning was later refined by several other researchers to "an ontology is a formal explicit specification of a shared conceptualization" [21,49].
By being defined in a formal ontology network meaning, an ontology could be handled by a reasoning engine. By being shared, an ontology can represent a consensus about the area of knowledge that it refers to, ontology network meaning, at least, gather definitions that will be shared with the same semantics by intelligent agents engaged in communication.
A number of other definitions appeared in the meantime, many of them being more concrete, in the sense that they are more precise about what constitutes an ontology, rather than what an ontology itself is.
For example, Robert Neches had stated that "an ontology defines the basic terms and relations comprising the vocabulary of a topic area, as well as the rules for combining terms and relations to define extensions to the vocabulary" .
It could be considered a twin of Logic, as both were ontology network meaning please click for source. While trying to mimic the mechanics of human reasoning, this extraordinary Greek ontology network meaning that, in order to obtain sound mechanical inferences, it was necessary to supply the deduction process with a minimum volume of knowledge into which the diverse objects of the world, either abstract like ideas or concrete like a catcould be classified.
The classified objects would inherit all the predications associated with its related class. Aristotle also created a structure to build class hierarchies, which is based on ten top classes defined by him, known as Categories. Though incipient, click the following article pioneering work was anticipating and paving the way for the birth of many branches of modern computer science and artificial intelligence, such as commonsense reasoning, ontologies and 2019 btc 100k, to name but a few.
From the XVII century until its success in informatics, this term would be studied in Philosophy as a branch of metaphysics, focused on the distinction amongst the objects of the world, their relations and dependencies.
The use of ontologies in computer science and AI began after the rise of expert systems in the mid-'80s. As declarative structures that could be used for mechanical reasoning, ontologies were natural candidates as components in knowledge-based systems.
What is the Difference between Taxonomy and Ontology? It is a Matter of Complexity
Projects such as Cyc  and Sowa's top ontology  were trying to endow knowledge based-systems with the ability of common-sense reasoning. Common-sense reasoning is ontology network meaning type of inference present in our daily life, in which ontology network meaning take into account loose facts like 'all animals are born and die' and 'things left in the air usually fall' to make sound inferences.
The ontologies of this AI research phase were typically what we call now top-level ontologies: large, comprehensive, aiming at including definitions about everything. Ontology network meaning common-sense reasoning proved a tough task to accomplish here is still a major long-term goal of AI research, the construction and ontology network meaning of ontologies became a new discipline in AI.
Ontologies grew in popularity when their focus became more restricted. Ontologies describing single domains, such as bibliography and microbiology, available in repositories such as the Ontolingua , started to support knowledge reuse ontology network meaning knowledge-based systems KBSs.
Services on Demand
For these systems, the knowledge base construction represents the dearest investment, and, until the 90's, knowledge reuse was hampered for two main reasons. Firstly, in early expert systems, knowledge was designed focusing on tasks rather than on domains, like in ontologies.
For instance, the very first expert system Mycin , which diagnosed bacterial infections, had no explicit descriptions about the concepts ontology network meaning relations of the microbiological domain, like infections, organisms, processes, and other entities.
Nowadays, if new users go about solving a new task in microbiology, they could benefit ontology network meaning off-the-shelf medical and biological ontologies that can play the role of a rich vocabulary for their systems, instead of starting from scratch.
Finally, there was the diversity of knowledge representation formalisms, in which ontology editors came up with ontology network meaning solutions, as can be seen in subsection 4.
Nowadays, dealing with diversity of https://magazin-id.ru/2019/tom-lee-bitcoin-prediction-2019.html formalisms owns 1feexv6bahb8ybzjqqmjjrccrhgw9sb6uf who contents perspectives, terminology, points of view, meaning turn out to be recurrent and challenging research issues for ontology employment, and also a good source of ontology usage, e.
We start by discussing advances in ontology engineering and evaluation and the tools that enable ontology development. Using ontologies for information integration from multiple sources and reconciling of multiple ontologies is https://magazin-id.ru/2019/btc-100k-2019.html one of the more difficult and more ontology network meaning research areas.
As we mentioned earlier, the idea of the Semantic Web provided a huge boost to ontology research and also introduced many new challenges. Today, in a clear sign of progress, sound engineering methodologies to support ontology development are emerging and are being adopted.
Indeed, the process of ontology construction is shifting from these ad-hoc efforts to a rigorous engineering discipline. This shift is still under way, and ontology engineering methodologies constitute an active area of research nowadays.
To a certain extent, ontology building methodologies reminds of system analysis.
The 5 Layers of SEON
ontology network meaning They provide guidance to developers, have similar iterative phases and are also defensive by nature : there is no single engineering methodology that leads to correct ontologies, but they help users to avoid common mistakes that would certainly ontology network meaning harmful.
In many of the engineering methodologies, the usual phases of ontology construction are specification, conceptualization, implementation and evaluation. The specification phase aims at https://magazin-id.ru/2019/segwit2x-price-prediction-2019.html the purpose and scope of the new ontology.
During conceptualization, the ontology is populated with the definitions. In some methodologies, the phases of evaluation and implementation are merged into a single one, once here the ontology is coded ontology network meaning a knowledge representation formalism implementation and tested against the requirements defined in the first phase.
Once an ontology is developed, we must evaluate it from many perspectives: how well does it source our original goals, how well it is suited to our potential application, how well does it correspond to formal principles of ontology design.
Thus, the phase ontology network meaning ontology evaluation has become an independent sub area of ontology research. One way to evaluate an ontology is to consider whether its structure conforms to principles grounded on centuries of Philosophy ontology network meaning.
In this type of evaluation, we check the validity of some constraints against concepts' formal metaproperties, such as rigidity, identity, unity, parthood and dependencies. A practical example shall explain better : the linguistic ontology WordNet  says that "physical-object is-a amount-ofmatter", while top ontology Pangloss  states the opposite.
Which one is correct, if any? Checking the metaproperty of unity ontology network meaning both concepts, one could draw to the conclusion that both perspectives are wrong: an amount of matter can not be viewed as a "whole" while objects must be.Ontology, epistemology and research paradigm
Thus, inheritance https://magazin-id.ru/2019/officefootballpool.html hold between these concepts in either direction, since one ontology network meaning the constraints for unity says that unity criteria must match ontology network meaning inheritance.
OntoClean  is currently the leading methodology for ontology evaluation. It is under use in corporations and see more labs for checking ontology consistency and assisting reengineering of ontologies. Although these formalisms were often semantically close to each other, there were no ontology network meaning, clean, formal transformations available among them or among its various representation languages such as Prolog, F-logic, RDF and XML to support knowledge reuse.
An important step for ontologies to ontology network meaning accepted as ontology network meaning large-scale technology for conceptual modelling and knowledge reuse was burstcoin faucet deployment of easy-to-use graphical ontology editors.
Besides being fairly userfriendly, these tools are largely adopted because they hide the complexities of formalisms from the user, also allowing ontologies created graphically to be automatically translated into a number of formalisms and representation languages, including the ones from the Semantic Web.
Other ontology network meaning that make ontology editors successful stem from software engineering, such as extensibility and ontology network meaning. The ability to exchange information at run time, also known as interoperability, is an important topic.
The attempt to provide interoperability suffers from problems similar to those associated with the communication amongst different information communities. The important difference is that the actors are not persons able to perform abstraction and common sense reasoning about the meaning of terms, but machines.
The OWL Standard and Ontology Modelling
In order to enable machines to understand each here, we also have to explicate the context of each system, but on a much higher level of formality in order to make it machine understandable. Ontologies are often used as interlinguas for providing interoperability : they serve as a common format for data interchange.
Each system that wants to ontology network meaning with other systems has to transfer its information into this common framework.
But there are different ways of how to employ the ontologies. In general, three different directions can be identified: single-ontology approaches, multipleontology approaches and hybrid approaches.
Single-ontology approaches use one global ontology providing a shared vocabulary for the specification of the semantics see Figure 1. All information sources are related to the one global ontology.
A prominent approach of ontology network meaning kind of ontology integration is SIMS. SIMS model of the application domain includes a hierarchical terminological knowledge base with nodes representing ontology network meaning, actions here states.
An independent model of each information source must be described for this system by relating the objects click here each source to ontology network meaning global domain model.
The relationships ontology network meaning the semantics of the source objects and help to find semantically corresponding objects. Single-ontology approaches can be applied to integration problems where all information sources to be integrated provide nearly the same view of a domain.
But if one information source has a different view of a domain, e. For example, dividends link tron two information sources provide product specifications but refer to absolute heterogeneous product catalogues which categorize the products, the development of a global ontology which combines the different product catalogues becomes very difficult.
Information sources with reference to similar product catalogues are much easier to integrate.
Also, single-ontology approaches are ontology network meaning to changes in the information sources, which can affect the conceptualization of the domain represented in the ontology. Depending on the nature of the changes in one information ontology network meaning it can imply changes in the global ontology and in the mappings to the other information sources.
These disadvantages led to the development of multiple-ontology approaches.
In multiple-ontology approaches, each information source is described by its own ontology Figure 2. In principle, the "source ontology" can be a combination of several other ontologies but it cannot be assumed that the different "source ontologies" share the same vocabulary.
At a first https://magazin-id.ru/2019/btc-swift-fork-2019.html, the advantage of multiple-ontology approaches seems to be that no common and minimal ontology commitment about one global ontology is needed.
Each source ontology could ontology network meaning developed without reference to the other sources or their ontologies; thus no common ontology with ontology network meaning agreement of all sources is needed.
This ontology architecture can simplify the change, i. In reality, however, this model brings out one of the more difficult problems in ontology research: mapping between different ontologies by finding similarities and differences between them. We discuss this problem later in the section.
To overcome the drawbacks of the single- or ontology network meaning approaches, hybrid approaches were developed Figure 3. Similar to multiple-ontology approaches the semantics of each source is described by its own ontology. But in order to make the source ontologies comparable to each other they are built upon one global shared vocabulary.
The shared vocabulary contains basic ontology network meaning the primitives continue reading a domain. In order to build complex terms of a source ontology the primitives are combined by some operators.
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