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Semantic technologies are often well hidden, see how they work!

Linked DataLinked Data is a sub-topic of the Semantic Web. The term Linked Data is used to describe a method of exposing, sharing, and connecting data via dereferenceable URIs on the Web. based approaches are focussed on the extraction of meaningful pieces of information from Big Data in a given context. Advantage for the customer: the constantly growing amount of information resulting in Big Data becomes both searchable and reasonably usable. Linked Data is an efficient way to process Big data within a networked environment reflecting its dynamic behaviour. Examples: The World Wide Web or most enterprise intranets. Linked Data is based on standards and has been developed for more than 10 years rather than being an undefined accumulation of technologies.
Following a comprehensive requirements analysis and an assessment of various possible solutions, linked data technologies turn out to build the basis for the solution in the following cases (examples): multilingual environment, hetero­ge­neous data sources should be integrated, a lot of unstructured information is used, quantity of data is constantly growing in parallel to changes of its structure and semantics. To build a basis for knowledge graphs built upon linked data technologies most often a controlled vocabulariesControlled vocabularies provide a way to organize knowledge for subsequent retrieval. They are used in subject indexing schemes, subject headings, thesauri and taxonomies. Controlled vocabulary schemes mandate the use of predefined, authorised terms that have been preselected by the designer of ... based on SKOSSimple Knowledge Organization System (SKOS) is a family of formal languages designed for representation of thesauri, classification schemes, taxonomies, subject-heading systems, or any other type of structured controlled vocabulary. SKOS is built upon RDF and RDFS, and its main objective is to ... have to be developed. This is the ‘backbone’ for a further extended version of your enterprise knowledge graphA knowledge graph is a graph of related concepts and resources most often derived from various sources which are distributed across the web or the intranet. which also contains legacy data and data from sources like DBpediaDBpedia is a project aiming to extract structured information from the information created as part of the Wikipedia project. This structured information is then made available on the World Wide Web. DBpedia allows users to query relationships and properties associated with Wikipedia resources, ..., GeonamesGeoNames is a geographical data base available and accessible through various Web services, under a Creative Commons attribution license. or Freebase, all nicely aligned to your enterprise thesauri. In parallel to this, the specification and implementation of your smart applications which make use of your knowledge graph has to be realized. A linked data project is usually comprised of a number of such iterations. Read more.
Basically spoken, semantic technologies help to make applications smarter. Semantic technologies have positive impacts on different levels of software applications: Firstly, they help to build smarter end-user interfaces (users don’t have to deal with the logics behind an application anymore, users can use their own language instead of the provider’s language). Secondly, semantic technologies help to create content with higher quality in less time (prevention of re-inventing the wheel, higher consistency of metadataMetadata is loosely defined as data about data. Metadata is a concept that applies mainly to electronically archived or presented data and is used to describe the a) definition, b) structure and c) administration of data files with all contents in context to ease the use of the captured and ... leads to higher quality of content, improved information retrieval, personalization). Thirdly, information becomes better integrable by using linked data and semantic technologies which causes options to drastically save costs of content production on the one side, and to generate new tools for decision makers. You can find more details on this question in our management briefing.
All industries which deal with a lot of information and data which constantly evolves and which can be put into varying contexts (so called ‘knowledge intensive industries’). Typically industries like finance, pharma, media industry, IT or also government deal with multi-faceted aspects of certain business objects which have to be linked or enriched by additional metadata. Take a look at our references.
First of all, compared to the time your organization or your clients will save by using systems based on a thesaurus, the time for creating it should usually be much less. Depending on some preconditions (availability of fragments to create a seed-thesaurus like glossariesA glossary, also known as an idioticon, vocabulary, or clavis, is an alphabetical list of terms in a particular domain of knowledge with the definitions for those terms. Traditionally, a glossary appears at the end of a book and includes terms within that book which are either newly introduced, ..., simple entity-lists or taxonomiesTaxonomy is the practice and science of classification. The word finds its roots in the Greek τάξις, taxis (meaning 'order' or 'arrangement') and νόμος, nomos (meaning 'law' or 'science'). Taxonomy uses taxonomic units, known as taxa. In addition, the word is also used as a count noun: ...), the scope, complexity and dynamics of change of your domain are the most significant factors of how long your thesaurus project will last. We would be happy if we could give you some first estimations for this task.
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