FAQ  There are certain questions that we get asked time and again. We've put together the most frequent ones for you here. Please do not hesitate to contact us if you should have any additional questions.

What is Knowledge Network?  In Knowledge Network, business topics and objects are linked to one another, thus establishing a layer of semantics over the data and documents.

The objects of Knowledge Network can be for example companies, employees, products, technologies etc. Relations link these objects: Employees are linked by the relation "manages" or "works with on" projects, but are also assigned to departments. Projects are "performed on behalf of" clients and "use" particular technologies. Technologies are grouped in areas of technology via relations to generic or subordinate terms.

In most cases, Knowledge Network contains facts from structured data sources such as product or customer databases. Additionally, documents and know-how storage media are very often integrated into these connections – and so an intelligent directory of all knowledge resources in the company comes into being. Knowledge Networks combine the intelligence of AI representations of knowledge with the pragmatic demands of everyday business routine.

Is Knowledge Network a database?  Knowledge Networks can be understood as databases inasmuch as they save structured information and make it accessible. On top of this, they provide special assistance with knowledge work:

• Knowledge Networks are distinguished by their high flexibility of schema, with the result that even complex information can be recorded at the same time both in simple and finely detailed forms. Changes to the schema are also substantially easier to realize than for the schema of a relational database
• Knowledge Networks are just as suited to the representation of structured facts as to the mapping of themes and their connections. Thus you can bring together data and classifications
• K-Infinity Knowledge Networks provide a wealth of helpful search functions, navigation options and views, with additional ones being easily defined. This substantially reduces the time required for developing the application
• The logic of themes and sub-themes and their links etc. is already built into the schema, just the same as the mechanisms for creating automatic conclusions
• Finally, Knowledge Networks are superbly suited to making documents accessible

How is it different to a search engine?  Search engines compare what the user has entered with a store of documents. A document is returned to the user as a hit, if the exact series of letters, numbers or symbols entered occurs in the text of the document. Advanced products can bring a minimum level of fuzziness into the comparison, for example by using statistical processes – but the basic procedure is still a comparison of chains of symbols. The person searching then has to forecast which words in which spelling are likely to occur in relevant documents; this often leads to a large number of irrelevant hits and – more seriously – to many relevant documents not being found, because they contain a paraphrase of the expression being searched for, or a synonym or a more general expression.

Only semantic technologies can offer greater independence from the formulation of a text. Search engines permit a certain degree of access to volumes of information that are otherwise too great to manage. They operate without any prior knowledge of the context of the search: Who is searching for information and for what purpose? What will be done with the search results?, etc. However, search engines hit their limits when the search is to be anchored in business processes, combined with navigation/exploration or converted into an active Information Push, or when, say, experts as well as documents are to be returned as hits, or structured information is to be incorporated into the search. Comprehensive access to business-critical information is the domain of Knowledge Networks.

Where does the Knowledge Network come from? How much time and effort is involved in setting it up?  A large part of the information that goes to make up a Knowledge Network comes from sources that already exist. Substantial added value is created just through the integration of information already existing in structured form, but brought together for the first time in a Knowledge Network, with the possibility of searching across different sources and different types of information.

On the other hand, the structuring of information according to requirements is intellectual work And additional information or links that have not existed in any data source up to now often have to be incorporated. Therefore manual effort can certainly be involved when setting up a Knowledge Network. This makes the simple options that K-Infinity provides for setting up and maintaining the system so important. Sources typically flowing into a Knowledge Network are customer and product databases, or directories of employees and organizational units. Companies often have internal glossaries or glossaries and taxonomies covering whole industries; the directory structure of a drive can also provide valuable input.

External data sources can either be incorporated in permanent form or dynamically, the lead system can be the Knowledge Network or the database. When it comes to intellectual, manual maintenance we distinguish between central structuring – possible object types and links, and also themes are mostly centrally determined – and local data entry of projects, customer contacts etc. by the individual user. This takes place via extremely simple maintenance templates incorporated in the research interface. Simply describe your situation to us and we'll make a rough framework for the project.