When the Top list was started, more than a decade ago, the fiber-to-the-home industry was new. The list included nearly every broadband-related company that was even thinking about fiber, some that planned to start thinking about it soon, and some that specialized in other broadband technologies entirely.
Introduction "Tell me what wines I should buy to serve with each course of the following menu. And, by the way, I don't like Sauternes. Similarly, consider actually assigning a software agent the task of making a coherent set of travel arrangements.
For more use cases see the OWL requirements document. To support this sort of computation, it is necessary to go beyond keywords and specify the meaning of the resources described on the Web. This additional layer of interpretation captures the semantics of the data.
Ontology is a term borrowed from philosophy that refers to the science of describing the kinds of entities in the world and how they are related. An OWL ontology may include descriptions of classes, properties and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.
These entailments may be based on a single document or multiple distributed documents that have been combined using defined OWL mechanisms. The Document Roadmap section of the Overview [Overview]1. An ontology differs from an XML schema in that it is a knowledge representation, not a message format.
Most industry based Web standards consist of a combination of message formats and protocol specifications. These formats have been given an operational semantics, such as, "Upon receipt of this PurchaseOrder message, transfer Amount dollars from AccountFrom to AccountTo and ship Product.
For example, we won't in general have a mechanism to conclude that because the Product is a type of Chardonnay it must also be a white wine. One advantage of OWL ontologies will be the availability of tools that can reason about them.
Tools will provide generic support that is not specific to the particular subject domain, which would be the case if one were to build a system to reason about a specific industry-standard XML schema.
Building a sound and useful reasoning system is not a simple effort.
Constructing an ontology is much more tractable. It is our expectation that many groups will embark on ontology construction. They will benefit from third party tools based on the formal properties of the OWL language, tools that will deliver an assortment of capabilities that most organizations would be hard pressed to duplicate.
The Species of OWL The OWL language provides three increasingly expressive sublanguages designed for use by specific communities of implementers and users.
OWL Lite supports those users primarily needing a classification hierarchy and simple constraint features.
For example, while OWL Lite supports cardinality constraints, it only permits cardinality values of 0 or 1. It should be simpler to provide tool support for OWL Lite than its more expressive relatives, and provide a quick migration path for thesauri and other taxonomies. OWL DL supports those users who want the maximum expressiveness without losing computational completeness all entailments are guaranteed to be computed and decidability all computations will finish in finite time of reasoning systems.
OWL DL includes all OWL language constructs with restrictions such as type separation a class can not also be an individual or property, a property can not also be an individual or class.
OWL DL is so named due to its correspondence with description logics [Description Logics]a field of research that has studied a particular decidable fragment of first order logic. OWL DL was designed to support the existing Description Logic business segment and has desirable computational properties for reasoning systems.
OWL Full is meant for users who want maximum expressiveness and the syntactic freedom of RDF with no computational guarantees. For example, in OWL Full a class can be treated simultaneously as a collection of individuals and as an individual in its own right.
DatatypeProperty can be marked as an owl: It is unlikely that any reasoning software will be able to support every feature of OWL Full.
Each of these sublanguages is an extension of its simpler predecessor, both in what can be legally expressed and in what can be validly concluded. The following set of relations hold. Their inverses do not. Ontology developers adopting OWL should consider which species best suits their needs.
Reasoners for OWL Lite will have desirable computational properties. Reasoners for OWL DL, while dealing with a decidable sublanguage, will be subject to higher worst-case complexity.
For more information about this issue see the OWL semantics document. Structure of the Document In order to provide a consistent set of examples throughout the guide, we have created a wine and food ontology. Some of our discussion will focus on OWL Full capabilities and is so marked.
The wine and food ontology is a significant modification of an element of the DAML ontology library with a long history. All of the examples presented in this document are taken from the ontologies contained in wine.
This effort aims to make Web resources more readily accessible to automated processes by adding information about the resources that describe or provide Web content.Encourage students to refer to the following while they are working: model informational essay, Informative Writing Checklist, Informational Texts anchor chart, their planning graphic organizer, Academic Word Wall, and Domain-Specific Word Wall.
Below are links to the free, downloadable Word Doc and PDF versions of the latest edition () of the Guidelines for the Use of Fishes in Research.. Both the Word and PDF versions contain useful internal and external hyperlinks. Providing educators and students access to the highest quality practices and resources in reading and language arts instruction.
These first three standards are anchor standards. They are expounded on in all grade levels covered by the Common Core State Standards (K). Here are all of the grade level specific standards related to author’s purpose. Job Skills’ Programs and Services are funded by the Government of Canada, the Ontario Government, municipal governments, United Way Toronto & York Region and the Ontario Trillium Foundation.
Individual grade-specific standards can be identified by their strand, grade, and number (or number and letter, where applicable), so that RI, for example, stands for Reading, Informational Text, grade 4, standard 3 and Wa stands for Writing, grade 5, .