By Jeffrey T. Pollock
- New Paradigm for contemplating software integration and B2B difficulties
- Heightens the significance of conveying which means among structures
- Addresses move within the EAI area towards extra information dealing with services
- Offers an answer for the multitude of managers disconnected with the newest applied sciences
- Leverages the technical advances made in advanced info integration over 15 years
- Shifts the focal point from expertise ideas to info options
- Relies seriously at the use of sensible examples, suggestions, definitions, and soapbox excerpts through the major physique of textual content
Chapter 1 Semantic Interoperability offers IT that means (pages 3–22):
Chapter 2 details Infrastructure concerns and difficulties (pages 23–38):
Chapter three Promise of Frictionless info (pages 39–65):
Chapter four Foundations in info Semantics (pages 69–98):
Chapter five Semantic clash answer styles (pages 99–125):
Chapter 6 Metadata Archetypes (pages 127–144):
Chapter 7 Ontology layout styles (pages 145–194):
Chapter eight Multimodal Interoperability structure (pages 195–221):
Chapter nine Infrastructure and E?Business styles (pages 223–255):
Chapter 10 power Case reports (pages 259–304):
Chapter eleven Adoption recommendations (pages 305–331):
Chapter 12 Tomorrow's Adaptive and Dynamic platforms (pages 333–346):
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Additional resources for Adaptive Information: Improving Business through Semantic Interoperability, Grid Computing, and Enterprise Integration
However, it is grounded in long-established concepts of information theory and enterprise software practices. It will become the next 15-year overnight success in the information technology industry. The discipline of data semantics has broad and far-reaching applications in a number of software solutions. From work on the Semantic Web to emerging database structures, the concepts underlying the use of semantics in digital systems are having an immense impact on businesses industry wide. Definition: Semantic Interoperability Semantic interoperability is a dynamic enterprise capability derived from the application of special software technologies (such as reasoners, inference engines, ontologies, and models) that infer, relate, interpret, and classify the implicit meanings of digital content without human involvement—which in turn drive adaptive business processes, enterprise knowledge, business rules, and software application interoperability.
One way to meet this challenge is collaborative IT systems, which can enable businesses to change processes and procedures on the fly—thereby further differentiating themselves against their competitors. These differentiating factors can be leveraged to drive customer loyalty. By making a business’s outward-facing demand-based systems more collaborative, corporate leaders can ensure that their customers always have the best service, information, and insight possible. Finally, innovators across industry will leverage collaborative technology to drive market expansion—growing the opportunity with new services and offerings that can expand their customer base.
Sometimes they might include graphical tools, perhaps with some drag-and-drop functions, to assist with writing that code—but the final result is always some type of custom script or compiled object to accomplish an integration task. Each company’s folklore, culture, fuzzy process, and data combine to create the single most challenging barrier to IT evolution. The “H” Factor Humans themselves are the single largest bottleneck to adaptive IT systems. Humans must be involved in the finest of details because of the hands-on nature of resolving data and process meanings.
Adaptive Information: Improving Business through Semantic Interoperability, Grid Computing, and Enterprise Integration by Jeffrey T. Pollock