Semantic Interoperability Issues, Solutions, Challenges
Semantic Interoperability Issues, Solutions, Challenges

Author: Salvatore F. Pileggi

Publisher: CRC Press

Published: 2022-09-01

Total Pages: 111

ISBN-13: 1000792072

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Semantic technologies are experimenting an increasing popularity in the context of different domains and applications. The understanding of any class of system can be significantly changed under the assumption any system is part of a global ecosystem known as Semantic Web.The Semantic Web would be an evolving extension of current Web model (normally referred as Syntactic Web) that introduces a semantic layer in which semantics, or meaning of information, are formally defined.So, semantics should integrate web-centric standard information infrastructures improving several aspects of interaction among heterogeneous systems. This is because common interoperability models are progressively becoming obsolete if compared with the intrinsic complexity and always more distributed focus that feature modern systems. For example, the basic interoperability model, that assumes the interchange of messages among systems without any interpretation, is simple but effective only in the context of close environments. Also more advanced models, such as the functional interoperability model that integrates basic interoperability model with the ability of intepretating data context under the assumption of a shared schema for data fields accessing, appears not able to provide a full sustainable technologic support for open systems.The Semantic Interoperability model would improve common interoperability models introducing the interpretation of means of data. Semantic interoperability is a concretely applicable interaction model under the assumption of adopting rich data models (commonly called Ontology) composed of concepts within a domain and the relationships among those concepts.In practice, semantic technologies are partially inverting the common view at actor intelligence: intelligence is not implemented (only) by actors but it is implicitly resident in the knowledge model. In other words, schemas contain information and the "code" to interpretate it.

Semantic Interoperability: Issues, Solutions, Challenges
Semantic Interoperability: Issues, Solutions, Challenges

Author: Dr. Salvatore F. Pileggi

Publisher: River Publishers

Published: 2012-03-13

Total Pages: 164

ISBN-13: 8792982824

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Semantic technologies are experimenting an increasing popularity in the context of different domains and applications. The understanding of any class of system can be significantly changed under the assumption any system is part of a global ecosystem known as Semantic Web. The Semantic Web would be an evolving extension of current Web model (normally referred as Syntactic Web) that introduces a semantic layer in which semantics, or meaning of information, are formally defined. So, semantics should integrate web-centric standard information infrastructures improving several aspects of interaction among heterogeneous systems. This is because common interoperability models are progressively becoming obsolete if compared with the intrinsic complexity and always more distributed focus that feature modern systems. For example, the basic interoperability model, that assumes the interchange of messages among systems without any interpretation, is simple but effective only in the context of close environments. Also more advanced models, such as the functional interoperability model that integrates basic interoperability model with the ability of interpreting data context under the assumption of a shared schema for data fields accessing, appears not able to provide a full sustainable technologic support for open systems. The Semantic Interoperability model would improve common interoperability models introducing the interpretation of means of data. Semantic interoperability is a concretely applicable interaction model under the assumption of adopting rich data models (commonly called Ontology) composed of concepts within a domain and the relationships among those concepts. In practice, semantic technologies are partially inverting the common view at actor intelligence: intelligence is not implemented (only) by actors but it is implicitly resident in the knowledge model. In other words, schemas contain information and the “code” to interpret it.

Cases on Semantic Interoperability for Information Systems Integration: Practices and Applications
Cases on Semantic Interoperability for Information Systems Integration: Practices and Applications

Author: Kalfoglou, Yannis

Publisher: IGI Global

Published: 2009-10-31

Total Pages: 376

ISBN-13: 1605668958

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"This book presents the use of semantic interoperability for a variety of applications ranging from manufacturing to tourism, e-commerce, energy Grids' integration, geospatial systems interoperability and automated agents interoperability for web services"--Provided by publisher.

Principles of Health Interoperability
Principles of Health Interoperability

Author: Tim Benson

Publisher: Springer

Published: 2016-06-22

Total Pages: 461

ISBN-13: 3319303708

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This book provides an introduction to health interoperability and the main standards used. Health interoperability delivers health information where and when it is needed. Everybody stands to gain from safer more soundly based decisions and less duplication, delays, waste and errors. The third edition of Principles of Health Interoperability includes a new part on FHIR (Fast Health Interoperability Resources), the most important new health interoperability standard for a generation. FHIR combines the best features of HL7’s v2, v3 and CDA while leveraging the latest web standards and a tight focus on implementability. FHIR can be implemented at a fraction of the price of existing alternatives and is well suited for use in mobile phone apps, cloud communications and EHRs. The book is organised into four parts. The first part covers the principles of health interoperability, why it matters, why it is hard and why models are an important part of the solution. The second part covers clinical terminology and SNOMED CT. The third part covers the main HL7 standards: v2, v3, CDA and IHE XDS. The new fourth part covers FHIR and has been contributed by Grahame Grieve, the original FHIR chief.

Interoperating Geographic Information Systems
Interoperating Geographic Information Systems

Author: Michael Goodchild

Publisher: Springer Science & Business Media

Published: 1999-02-28

Total Pages: 544

ISBN-13: 9780792384366

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Geographic information systems have developed rapidly in the past decade, and are now a major class of software, with applications that include infrastructure maintenance, resource management, agriculture, Earth science, and planning. But a lack of standards has led to a general inability for one GIS to interoperate with another. It is difficult for one GIS to share data with another, or for people trained on one system to adapt easily to the commands and user interface of another. Failure to interoperate is a problem at many levels, ranging from the purely technical to the semantic and the institutional. Interoperating Geographic Information Systems is about efforts to improve the ability of GISs to interoperate, and has been assembled through a collaboration between academic researchers and the software vendor community under the auspices of the US National Center for Geographic Information and Analysis and the Open GIS Consortium Inc. It includes chapters on the basic principles and the various conceptual frameworks that the research community has developed to think about the problem. Other chapters review a wide range of applications and the experiences of the authors in trying to achieve interoperability at a practical level. Interoperability opens enormous potential for new ways of using GIS and new mechanisms for exchanging data, and these are covered in chapters on information marketplaces, with special reference to geographic information. Institutional arrangements are also likely to be profoundly affected by the trend towards interoperable systems, and nowhere is the impact of interoperability more likely to cause fundamental change than in education, as educators address the needs of a new generation of GIS users with access to a new generation of tools. The book concludes with a series of chapters on education and institutional change. Interoperating Geographic Information Systems is suitable as a secondary text for graduate level courses in computer science, geography, spatial databases, and interoperability and as a reference for researchers and practitioners in industry, commerce and government.

Dynamics in Logistics
Dynamics in Logistics

Author: Michael Freitag

Publisher: Springer Nature

Published: 2021-12-02

Total Pages: 322

ISBN-13: 303088662X

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This open access book highlights the interdisciplinary aspects of logistics research. Featuring empirical, methodological, and practice-oriented articles, it addresses the modelling, planning, optimization and control of processes. Chiefly focusing on supply chains, logistics networks, production systems, and systems and facilities for material flows, the respective contributions combine research on classical supply chain management, digitalized business processes, production engineering, electrical engineering, computer science and mathematical optimization. To celebrate 25 years of interdisciplinary and collaborative research conducted at the Bremen Research Cluster for Dynamics in Logistics (LogDynamics), in this book hand-picked experts currently or formerly affiliated with the Cluster provide retrospectives, present cutting-edge research, and outline future research directions.

Registries for Evaluating Patient Outcomes
Registries for Evaluating Patient Outcomes

Author: Agency for Healthcare Research and Quality/AHRQ

Publisher: Government Printing Office

Published: 2014-04-01

Total Pages: 385

ISBN-13: 1587634333

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This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.

Machine Learning for Healthcare Applications
Machine Learning for Healthcare Applications

Author: Sachi Nandan Mohanty

Publisher: John Wiley & Sons

Published: 2021-04-13

Total Pages: 418

ISBN-13: 1119791812

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When considering the idea of using machine learning in healthcare, it is a Herculean task to present the entire gamut of information in the field of intelligent systems. It is, therefore the objective of this book to keep the presentation narrow and intensive. This approach is distinct from others in that it presents detailed computer simulations for all models presented with explanations of the program code. It includes unique and distinctive chapters on disease diagnosis, telemedicine, medical imaging, smart health monitoring, social media healthcare, and machine learning for COVID-19. These chapters help develop a clear understanding of the working of an algorithm while strengthening logical thinking. In this environment, answering a single question may require accessing several data sources and calling on sophisticated analysis tools. While data integration is a dynamic research area in the database community, the specific needs of research have led to the development of numerous middleware systems that provide seamless data access in a result-driven environment. Since this book is intended to be useful to a wide audience, students, researchers and scientists from both academia and industry may all benefit from this material. It contains a comprehensive description of issues for healthcare data management and an overview of existing systems, making it appropriate for introductory and instructional purposes. Prerequisites are minimal; the readers are expected to have basic knowledge of machine learning. This book is divided into 22 real-time innovative chapters which provide a variety of application examples in different domains. These chapters illustrate why traditional approaches often fail to meet customers’ needs. The presented approaches provide a comprehensive overview of current technology. Each of these chapters, which are written by the main inventors of the presented systems, specifies requirements and provides a description of both the chosen approach and its implementation. Because of the self-contained nature of these chapters, they may be read in any order. Each of the chapters use various technical terms which involve expertise in machine learning and computer science.

Management Strategies for Sustainability, New Knowledge Innovation, and Personalized Products and Services
Management Strategies for Sustainability, New Knowledge Innovation, and Personalized Products and Services

Author: Pejic-Bach, Mirjana

Publisher: IGI Global

Published: 2022-01-14

Total Pages: 365

ISBN-13: 1799877957

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In today’s changing business environment, managers and employees need essential capabilities such as innovativeness to successfully reach organizational goals. In this digitalized era, it is obvious that undigitized firms and organizations will not survive changing demands unless they can quickly adapt and form new business strategies. The upcoming era necessitates a digital transformation in all institutions from government to the non-profit sector. In such a change-oriented and complex business era, both entrepreneurs and leaders must keep up with the latest developments around them. Management Strategies for Sustainability, New Knowledge Innovation, and Personalized Products and Services discusses the emerging topics of digital transformation, new knowledge innovation, sustainability, and personalized products and services and provides a theoretical infrastructure to share the latest empirical research findings within management, knowledge creation, sustainability practices, artificial intelligence, and digital business functions and strategies. Covering a wide range of topics such as Industry 4.0 and user satisfaction, it is ideal for industry professionals, practitioners, consultants, educators, scholars, researchers, academicians, and students.