Semantic Web Technologies
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6.2 Semantic Desktop
Semantic Desktop is a common term for concepts relating to improving the user
interface and data processing abilities of a machine so that data can be more easily
exchanged between various programs or functions, including data that could not be
handled automatically by a computer once. It also incorporates some ideas about
being able to instantly exchange knowledge between different individuals. Existing
Semantic Desktops are still accused of being too complicated to use or not scaling
well. Authors presented new prototype concerned with semantic desktop inspired
by NEPOMUK (social semantic desktop),which exploits the contextual information
and can dynamically reorganize itself [16].
6.3 Geospatial Semantic Web
A concept of placing geospatial information at the heart of the Semantic Web to
enable extraction of knowledge and incorporation of knowledge is termed as Geospatial Semantic Web. To define geographical incidences, it uses popular science terms,
semantic gazetteers and geospatial ontologies. Geospatial data semantics, next generation cyber networks, standardized geo domain vocabulary and geographic information extraction are primary fields of interest for the Geospatial Semantic Web. In addition, recent methodologies that promote semantic interoperability without reducing
heterogeneity must be taken into account [17]. Geospatial Semantic Web provides a
number of uses. One prominent application is from the domain of cultural heritage.
Nowadays, modern and evolving digital cultural heritage repositories are growing.
Such repositories, utilizing geospatial semantic web technologies, aim to resolve the
difficulties of maintaining and retaining scattered and poorly linked cultural heritage
documents that do not have structured search interfaces [18].
6.4 Semantic Web in Agriculture
While Agriculture and its related industry have a number of significant semantic
resources and standards of data interchange, the application based on semantic web
technologies in agriculture is underused. The adoption of semantic web technologies in the agricultural domain is dependent on available semantic resources in agricultural field. For example, AGROVOC is the major and most detailed semantic
resource comprising 35,000 concepts and 40,000 terms about agriculture, and also
about food, nutrition, fisheries, forestry and the environment. The key areas of agriculture where semantic web technologies were applied are classified mainly into:
knowledge-based systems, remote sensing, decision support, and expert systems.
Knowledge-based systems are applications which cause information to be stored in
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6.2 Semantic Desktop
Semantic Desktop is a common term for concepts relating to improving the user
interface and data processing abilities of a machine so that data can be more easily
exchanged between various programs or functions, including data that could not be
handled automatically by a computer once. It also incorporates some ideas about
being able to instantly exchange knowledge between different individuals. Existing
Semantic Desktops are still accused of being too complicated to use or not scaling
well. Authors presented new prototype concerned with semantic desktop inspired
by NEPOMUK (social semantic desktop),which exploits the contextual information
and can dynamically reorganize itself [16].
6.3 Geospatial Semantic Web
A concept of placing geospatial information at the heart of the Semantic Web to
enable extraction of knowledge and incorporation of knowledge is termed as Geospatial Semantic Web. To define geographical incidences, it uses popular science terms,
semantic gazetteers and geospatial ontologies. Geospatial data semantics, next generation cyber networks, standardized geo domain vocabulary and geographic information extraction are primary fields of interest for the Geospatial Semantic Web. In addition, recent methodologies that promote semantic interoperability without reducing
heterogeneity must be taken into account [17]. Geospatial Semantic Web provides a
number of uses. One prominent application is from the domain of cultural heritage.
Nowadays, modern and evolving digital cultural heritage repositories are growing.
Such repositories, utilizing geospatial semantic web technologies, aim to resolve the
difficulties of maintaining and retaining scattered and poorly linked cultural heritage
documents that do not have structured search interfaces [18].
6.4 Semantic Web in Agriculture
While Agriculture and its related industry have a number of significant semantic
resources and standards of data interchange, the application based on semantic web
technologies in agriculture is underused. The adoption of semantic web technologies in the agricultural domain is dependent on available semantic resources in agricultural field. For example, AGROVOC is the major and most detailed semantic
resource comprising 35,000 concepts and 40,000 terms about agriculture, and also
about food, nutrition, fisheries, forestry and the environment. The key areas of agriculture where semantic web technologies were applied are classified mainly into:
knowledge-based systems, remote sensing, decision support, and expert systems.
Knowledge-based systems are applications which cause information to be stored in