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Semantic technologies are often well hidden, see how they work!
Linked Data 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 vocabularies based on SKOS have to be developed. This is the ‘backbone’ for a further extended version of your enterprise knowledge graph which also contains legacy data and data from sources like DBpedia, Geonames 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 metadata 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 glossaries, simple entity-lists or taxonomies), 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.