A semantic mapper is tool or service that aids in the transformation of data elements from one namespace into another namespace. A semantic mapper is an essential component of a semantic broker and one tool that is enabled by the Semantic Web technologies.
Essentially the problems arising in semantic mapping are the same as in data mapping for data integration purposes, with the difference that here the semantic relationships are made explicit through the use of semantic nets or ontologies which play the role of data dictionaries in data mapping.
A semantic mapper must have access to three data sets:
A semantic mapper processes on a list of data elements in the source namespace. The semantic mapper will successively translate the data elements from the source namespace to the destination namespace. The mapping does not necessarily need to be a one-to-one mapping. Some data elements may map to several data elements in the destination.
Some semantic mappers are static in that they will do a one-time data transforms. Others will generate an executable program to repeatedly perform this transform. The output of this program may be any transformation system such as XSLT, a Java program or a program in some other procedural language.
In computer science and information science, an ontology encompasses a representation, formal naming and definition of the categories, properties and relations between the concepts, data and entities that substantiate one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of concepts and categories that represent the subject.
The Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontologies. Ontologies are a formal way to describe taxonomies and classification networks, essentially defining the structure of knowledge for various domains: the nouns representing classes of objects and the verbs representing relations between the objects.
In computing and data management, data mapping is the process of creating data element mappings between two distinct data models. Data mapping is used as a first step for a wide variety of data integration tasks, including:
The semantic spectrum is a series of increasingly precise or rather semantically expressive definitions for data elements in knowledge representations, especially for machine use.
SPARQL is an RDF query language—that is, a semantic query language for databases—able to retrieve and manipulate data stored in Resource Description Framework (RDF) format. It was made a standard by the RDF Data Access Working Group (DAWG) of the World Wide Web Consortium, and is recognized as one of the key technologies of the semantic web. On 15 January 2008, SPARQL 1.0 was acknowledged by W3C as an official recommendation, and SPARQL 1.1 in March, 2013.
Semantic translation is the process of using semantic information to aid in the translation of data in one representation or data model to another representation or data model. Semantic translation takes advantage of semantics that associate meaning with individual data elements in one dictionary to create an equivalent meaning in a second system.
In information science, an upper ontology is an ontology which consists of very general terms that are common across all domains. An important function of an upper ontology is to support broad semantic interoperability among a large number of domain-specific ontologies by providing a common starting point for the formulation of definitions. Terms in the domain ontology are ranked under the terms in the upper ontology, e.g., the upper ontology classes are superclasses or supersets of all the classes in the domain ontologies.
In metadata, a vocabulary-based transformation (VBT) is a transformation aided by the use of a semantic equivalence statements within a controlled vocabulary.
In computer metadata, semantic equivalence is a declaration that two data elements from different vocabularies contain data that has similar meaning. There are three types of semantic equivalence statements:
Metadata publishing is the process of making metadata data elements available to external users, both people and machines using a formal review process and a commitment to change control processes.
In metadata a synonym ring or synset, is a group of data elements that are considered semantically equivalent for the purposes of information retrieval. These data elements are frequently found in different metadata registries. Although a group of terms can be considered equivalent, metadata registries store the synonyms at a central location called the preferred data element.
Semantic integration is the process of interrelating information from diverse sources, for example calendars and to do lists, email archives, presence information, documents of all sorts, contacts, search results, and advertising and marketing relevance derived from them. In this regard, semantics focuses on the organization of and action upon information by acting as an intermediary between heterogeneous data sources, which may conflict not only by structure but also context or value.
Ontology alignment, or ontology matching, is the process of determining correspondences between concepts in ontologies. A set of correspondences is also called an alignment. The phrase takes on a slightly different meaning, in computer science, cognitive science or philosophy.
Simple Knowledge Organization System (SKOS) is a W3C recommendation designed for representation of thesauri, classification schemes, taxonomies, subject-heading systems, or any other type of structured controlled vocabulary. SKOS is part of the Semantic Web family of standards built upon RDF and RDFS, and its main objective is to enable easy publication and use of such vocabularies as linked data.
BioMOBY is a registry of web services used in bioinformatics. It allows interoperability between biological data hosts and analytical services by annotating services with terms taken from standard ontologies. BioMOBY is released under the Artistic License.
Semantic interoperability is the ability of computer systems to exchange data with unambiguous, shared meaning. Semantic interoperability is a requirement to enable machine computable logic, inferencing, knowledge discovery, and data federation between information systems.
The terms schema matching and mapping are often used interchangeably for a database process. For this article, we differentiate the two as follows: Schema matching is the process of identifying that two objects are semantically related while mapping refers to the transformations between the objects. For example, in the two schemas DB1.Student and DB2.Grad-Student ; possible matches would be: DB1.Student ≈ DB2.Grad-Student; DB1.SSN = DB2.ID etc. and possible transformations or mappings would be: DB1.Marks to DB2.Grades.
OneSource is an evolving data analysis tool used internally by the Air Combat Command (ACC) Vocabulary Services Team, and made available to general data management community. It is used by the greater US Department of Defense (DoD) and NATO community for controlled vocabulary management and exploration. It provides its users with a consistent view of syntactical, lexical, and semantic data vocabularies through a community-driven web environment. It was created with the intention of directly supporting the DoD Net-centric Data Strategy of visible, understandable, and accessible data assets.
Knowledge extraction is the creation of knowledge from structured and unstructured sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing. Although it is methodically similar to information extraction (NLP) and ETL, the main criteria is that the extraction result goes beyond the creation of structured information or the transformation into a relational schema. It requires either the reuse of existing formal knowledge or the generation of a schema based on the source data.
The Open Semantic Framework (OSF) is an integrated software stack using semantic technologies for knowledge management. It has a layered architecture that combines existing open source software with additional open source components developed specifically to provide a complete Web application framework. OSF is made available under the Apache 2 license.