Semantic Interoperability Sample Clauses

The Semantic Interoperability clause establishes a framework to ensure that different systems, organizations, or software can exchange and interpret data with consistent meaning. In practice, this clause may require parties to use standardized data formats, shared vocabularies, or agreed-upon ontologies so that information transferred between systems remains accurate and unambiguous. Its core function is to prevent misunderstandings or data misinterpretation, thereby facilitating seamless integration and collaboration across diverse technological environments.
Semantic Interoperability. 2.2.1 The main problems ▇▇▇▇▇▇▇-▇▇▇ et al. write [13]: "Some low-level service-discovery schemes are currently available such as Microsoft's Universal Plug and Play, which fo- cuses on connecting di erent types of devices, and Sun Microsystems's Jini, which aims to connect services. These initiatives, however, attack the prob- lem at a structural or syntactic level and rely heavily on standardization of a predetermined set of functionality descriptions. Standardization can only go so far, because it can not anticipate all possible future needs. The Semantic Web, in contrast, is more exible." Internet and the World Wide Web is increasing the number of information sources, the need of data exchange, the need of integration / interoperability and introducing new problems. The problems can be categorized in informa- tion sources and information exchange. Information sources in Internet introduces problems as follows [52]: the product of many individuals who have di erent domain and inter- est. Di erent domain can use di erent 'vocabulary', the main factor of the di erences of vocabulary is less of control in content and catalog. Furthermore, con icts can be occurred among the web as information sources. Increasing of autonomy will give other problem for integration. There are many kind of autonomy according to ▇▇▇▇ [80] as follows: design autonomy (own data representation, own domain), communi- cation autonomy (communicate to others), execution autonomy (local operation without in uenced by external operation), and association autonomy (share degree of sources). According to ▇▇▇▇▇ [89] there are 2 groups of heterogeneity: information and system heterogeneity. Many types of heterogeneity are due to technolog- ical di erences. Researchers and developers have been working on resolving the heterogeneity for many years. Information heterogeneity has lead to dif- ferent level in interoperability of system, syntactic, structure, and semantic. Table 2.1 present diversity of information system. Syntactic heterogeneity is concerned with di erences in the representation and encoding of data. It also referred to as format, such as: data format heterogeneity. Schemas are de nitions that specify the structure of data and are the result of a database design phase. For example: homonyms, synonyms or di erent attributes in database tables Hakimpour [49] distinguishes two types of heterogeneity: data hetero- geneity and semantic heterogeneity. Data heterogeneity refers to di er...
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Semantic Interoperability. The goal of data or information interoperability is to provide a way to access to data or information in multiple or heterogenous sources. Many researchers and prototypes have been done in the eld of information interoperability. Traditional approach was contributed by researchers from database area, and include ANSI/SPARC architecture, Federated Architecture and Dataware- house architecture. However, it based on point to point translation/convertion or developing global as view (GAV). This approach has problems in hetero- geneity of sources, dynamic of environment, and huge number of sources. Integration and interoperability is the important keys for the modern in- formation systems. However, the information sources are more heterogeneity (syntactic, structure, ad semantic), large number, dynamic of content and lo- cation, autonomy and open. Therefore, information interoperability requires di erence in modeling, representation, and accessing of sources. Researchers and practitioners in the elds of database and information integration have produced a large e ort to facilitate interoperability [96]. The sub-chapter on semantic interoperability consist of three sections. First, we introduce the main problems in information integration or inter- operability, including approach in schema and ontology mapping. Next, we present a classi cation of the approaches in semantic integration or interop- erability. Generic solution of semantic integration and interoperability can be categorized in two models: tightly coupled solution and loosely coupled solution. Main part of sub-chapter is review of implementation semantic web for integration or interoperability of heterogeneous information sources. Se- mantic integration or interoperability is an active area of research in several disciplines. Results of state of the art are comparison of related approaches and as a research foundation.
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Semantic Interoperability. Public data, i.e. all information that public authorities in the EU produce, process or purchase, represent one of the key sources of smart growth. Certain partial results have been achieved at the EU level, creating an implementation framework at the national level32. From the viewpoint of the data domain for the pan-European digital single market architecture, the biggest challenge represents transition to a new paradigm for data storage and management. For this purpose, the key pan-European platform is the “open data” initiative based on the relevant EU Directive33 and the ISA programme34. The open-data issue will also be addressed by the new Connecting Europe Facility (CEF) which, among other things, will support the implementation of the data (Open Data Digital Service Infrastructure), including the pan-European open data portal, in keeping with the steps taken so far35. The SR is among countries with the lowest level of openness in terms of availability of public data, including reference data administered in public administration registers36, which are needed for the exercise of public authority. Lacking quality in the current standard and openness of public data is evident from the level of sophistication of e- Government services37 in Slovakia. The problem is that electronic services require the availability of reference registers, which do not exist, and some basic registers (register of legal entities, natural persons, spatial information) are only in the implementation phase under the Operational Programme “Informatisation of Society” (hereinafter “OPIS”) and their availability is envisaged for 2015. Despite the fact that sufficient amount of data is available to public administration in the SR, administration is unable to use them effectively, in particular due to technical and legal reasons.
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Semantic Interoperability using controlled vocabularies: Due to the project’s user centric design, clear and effective communication among the participating partners is essential. Medical staff tends to use a very specific kind of language that is hardly understandable for patients, especially for less educated users. Therefore, it is important to provide non ambiguous feedback and instructions to avoid unwanted harmful consequences from using the system. Controlled vocabularies have proven as a means for providing standardized communication between medical staff, system developers and users patients. This module assists essentially the Virtual Individual Model.
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Semantic Interoperability. Today there are islands of well-defined semantics for use in e-commerce, such as universal classification schemas (EAN/UCC, UNSPSC …) and standard e-commerce frameworks (RosettaNet, OAGIS, ebXML, xCBL …). But there is no generally available, overall and unified business semantics across existing standards. Similar business concepts are being expressed differently, using different semantic depth, which results in ambiguous and overlapping concepts when considered in an integration scenario. This in turn leads to drastic increase in complexity and cost of integration. This also prevents ad-hoc collaboration scenarios between partners using different e-commerce frameworks. Well-established older standards will linger, so that this aspect of integration will not go away any time soon. The ECIMF project group has identified the need for better and more effective methods for semantic mapping. Some of the most promising methods use upper- level shared ontologies – however, there is no such common unified ontology available at the moment. Readers are encouraged to review Annex 3, where this problem is discussed in depth. Some of the existing projects are working intensively in this area, specifically: • ISO TC/154 Basic Semantic Register: provides a cross-linked reference to key concepts across several existing e-commerce standards. • ECIMF Semantic Mapping Tool: provides a prototype tool to facilitate semantic translation process, with use of shared ontology. • OntoWeb projects: several projects, e.g. on ontology-based integration of content standards (SIG1), and industrial applications of ontologies (SIG4) And other similar projects. However, there is still much to be done before the average e-commerce user begins to benefit from this work. The ECIMF project clearly identifies this issue as a fundamental integration problem, and recommends both further basic research into efficient methods of semantic mapping, and a development of upper-level shared e-commerce ontology for the purpose of such mapping.
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Semantic Interoperability 
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Related to Semantic Interoperability

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