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The semantic spectrum, sometimes referred to as the ontology spectrum, the smart data continuum, or semantic precision, is a series of increasingly precise or rather semantically expressive definitions for data elements in knowledge representations, especially for machine use.
At the low end of the spectrum is a simple binding of a single word or phrase and its definition. At the high end is a full ontology that specifies relationships between data elements using precise URIs for relationships and properties.
With increased specificity comes increased precision and the ability to use tools to automatically integrate systems but also increased cost to build and maintain a metadata registry.
Some steps in the semantic spectrum include the following:
The following is a list of questions that may arise in determining semantic precision.
Many organizations today are building a metadata registry to store their data definitions and to perform metadata publishing. The question of where they are on the semantic spectrum frequently arises. To determine where your systems are, some of the following questions are frequently useful.
Today, much of the World Wide Web is stored as Hypertext Markup Language. Search engines are severely hampered by their inability to understand the meaning of published web pages. These limitations have led to the advent of the Semantic web movement.
In the past, many organizations that created custom database application used isolated teams of developers that did not formally publish their data definitions. These teams frequently used internal data definitions that were incompatible with other computer systems. This made Enterprise Application Integration and Data warehousing extremely difficult and costly. Many organizations today require that teams consult a centralized data registry before new applications are created.
The job title of an individual that is responsible for coordinating an organization's data is a Data architect.
The first reference to this term was at the 1999 AAAI Ontologies Panel. The panel was organized by Chris Welty, who at the prodding of Fritz Lehmann and in collaboration with the panelists (Fritz, Mike Uschold, Mike Gruninger, and Deborah McGuinness) came up with a "spectrum" of kinds of information systems that were, at the time, referred to as ontologies. The "ontology spectrum" picture appeared in print in the introduction to Formal Ontology and Information Systems: Proceedings of the 2001 Conference. The ontology spectrum was also featured in a talk at the Semantics for the Web meeting in 2000 at Dagstuhl by Deborah McGuinness. McGuinness produced a paper describing the points on that spectrum that appeared in the book that emerged (much later) from that workshop called "Spinning the Semantic Web." Later, Leo Obrst extended the spectrum into two dimensions (which technically is not really a spectrum anymore) and added a lot more detail, which was included in his book, The Semantic Web: A Guide to the Future of XML, Web Services, and Knowledge Management.
The concept of the Semantic precision in business systems was popularized by Dave McComb in his book Semantics in Business Systems: The Savvy Managers Guide published in 2003 where he frequently uses the term Semantic Precision.
This discussion centered around a 10 level partition that included the following levels (listed in the order of increasing semantic precision):
Note that there was formerly a special emphasis on the adding of formal is-a relationships to the spectrum which has been dropped.
The company Cerebra has also popularized this concept by describing the data formats that exist within an enterprise in their ability to store semantically precise metadata. Their list includes:
What these concepts share in common is the ability to store information with increasing precision to facilitate intelligent agents.
This article has multiple issues. Please help
improve it or discuss these issues on the
talk page. (
Learn how and when to remove these template messages)
|
The semantic spectrum, sometimes referred to as the ontology spectrum, the smart data continuum, or semantic precision, is a series of increasingly precise or rather semantically expressive definitions for data elements in knowledge representations, especially for machine use.
At the low end of the spectrum is a simple binding of a single word or phrase and its definition. At the high end is a full ontology that specifies relationships between data elements using precise URIs for relationships and properties.
With increased specificity comes increased precision and the ability to use tools to automatically integrate systems but also increased cost to build and maintain a metadata registry.
Some steps in the semantic spectrum include the following:
The following is a list of questions that may arise in determining semantic precision.
Many organizations today are building a metadata registry to store their data definitions and to perform metadata publishing. The question of where they are on the semantic spectrum frequently arises. To determine where your systems are, some of the following questions are frequently useful.
Today, much of the World Wide Web is stored as Hypertext Markup Language. Search engines are severely hampered by their inability to understand the meaning of published web pages. These limitations have led to the advent of the Semantic web movement.
In the past, many organizations that created custom database application used isolated teams of developers that did not formally publish their data definitions. These teams frequently used internal data definitions that were incompatible with other computer systems. This made Enterprise Application Integration and Data warehousing extremely difficult and costly. Many organizations today require that teams consult a centralized data registry before new applications are created.
The job title of an individual that is responsible for coordinating an organization's data is a Data architect.
The first reference to this term was at the 1999 AAAI Ontologies Panel. The panel was organized by Chris Welty, who at the prodding of Fritz Lehmann and in collaboration with the panelists (Fritz, Mike Uschold, Mike Gruninger, and Deborah McGuinness) came up with a "spectrum" of kinds of information systems that were, at the time, referred to as ontologies. The "ontology spectrum" picture appeared in print in the introduction to Formal Ontology and Information Systems: Proceedings of the 2001 Conference. The ontology spectrum was also featured in a talk at the Semantics for the Web meeting in 2000 at Dagstuhl by Deborah McGuinness. McGuinness produced a paper describing the points on that spectrum that appeared in the book that emerged (much later) from that workshop called "Spinning the Semantic Web." Later, Leo Obrst extended the spectrum into two dimensions (which technically is not really a spectrum anymore) and added a lot more detail, which was included in his book, The Semantic Web: A Guide to the Future of XML, Web Services, and Knowledge Management.
The concept of the Semantic precision in business systems was popularized by Dave McComb in his book Semantics in Business Systems: The Savvy Managers Guide published in 2003 where he frequently uses the term Semantic Precision.
This discussion centered around a 10 level partition that included the following levels (listed in the order of increasing semantic precision):
Note that there was formerly a special emphasis on the adding of formal is-a relationships to the spectrum which has been dropped.
The company Cerebra has also popularized this concept by describing the data formats that exist within an enterprise in their ability to store semantically precise metadata. Their list includes:
What these concepts share in common is the ability to store information with increasing precision to facilitate intelligent agents.