The paradigm of semantic data processing, which has been attracting increasing attention since the early 2000s, draws on the philosophical approach of ontology, which was established by Parmenides around 500 BC. With this approach, reality can be described both abstractly and concretely. The tradition of ontological "modelling" was extended in modern times by mathematical forms of description, such as horn logic. With the logical programming languages developed in the 70s and 90s, such as Prolog and F-Logic, it is possible to describe complex relationships - as the philosophers did - and to use them as a form of artificial intelligence. Thus, new knowledge is created on the basis of complex connections - the so-called semantic AI.

OntoBroker has one of its greatest strengths in connectivity to the outside world. The Java API makes almost all internal structures easily accessible and is well documented. Furthermore, OntoBroker has both a SOAP and a SPARQL server available. An extensive library of connectors as well as a hot-plugin interface for external programs complete the API offering.

Ontologies are mainly known from the Semantic Web. The Semantic Web uses the Web Ontology Language (OWL), which is based on Description Logic (DL). The primary purpose of DL is the modeling of domains, i.e. the description of concepts, roles and instances, and represents a subset of the First-Order Logic. An essential feature of DL is that it follows the Open-World Assumption (OWA). The OWA is based on the assumption that an observer does not have complete knowledge of the world and therefore there are three logical states: true, false and unknown. This approach makes sense for a flexible and open information pool like the Internet. For industrial applications (e.g. SQL), however, the Close-Word Assumption has proven to be the only viable way to have a complete overview of information for non-chaotic processes. For example, an airline must be able to rely on the fact that a passenger has not checked in if a seat has been assigned to him and this seat is empty. This remains open for reasoning with OWL. The approach commonly used to remedy this situation with downstream so-called "closure axioms" (e.g. "man is not woman") would explode the modeling effort for the exemplary unoccupied seat. Logic languages like Prolog, DataLog and especially the ObjectLogic used here are, in contrast to DL, complete programming languages with which you can not only model domains descriptively in their fixed factual contexts but also functionally. This means that, depending on internal or external states, fact relationships can also change, i.e. ontology functions can change the ontology, including the functions. This non-monotonous property of ObjectLogic is an essential prerequisite for implementing semantic AI. Another important criterion of a logic language is its expressivity and thus the economy of its use. HOL allows the formulation of quantities of quantities. Reasoning" over the various quantity levels makes HOL extremely expressive.

OntoBroker is completely implemented in Java and therefore has a very high performance. This is Further ehanced by the high parallelism in the resolution of the logical pathways. In this way, OntoBroker benefits directly from the presence of many cores for complex reasoning. Furthermore, several OntoBroker instances can optimize performance using different load balancing methods.

The installation of OntoBroker is fast and easy. After starting the installation file, the installation process is initiated. In the following, you have to confirm the prompts in the windows that appear. Before installing OntoBroker, you have to check whether your computer meets the system requirements for the recommended configuration. Before installing OntoBroker, close all of the programs and applications on the computer. The installation wizard will guide you through the further installation process. During the installation, you will be asked for the KeyFile which should be stored in the OntoBroker installation folder. NOTE: Keyfiles for different versions can be put into the same directory ONTOPRISE_LICENSE_HOME.

Operating systems: Windows 7 or higher Windows Server 2016 or higher Linux (tested on SUSE, Debian and Ubuntu) Java platforms: Sun/OpenJDK Java 6 and later Hardware: Intel or AMD processors, 64-bit Minimum: 2 core, 2 GHz and better, 4 GB RAM, 500 MB free hard disk space Recommended: Quad core, 2.4 GHz and better, 8 GB RAM, 500 MB free hard disk space Contact us for Edge device configuration.

When installing the keyfile, during the installation process you must make sure that the keyfile has the original name given by semafora and the original extension.

Before installing OntoBroker make sure you have an appropriate Java runtime environment installed (OntoBroker requires Java 1.6). Then: Unzip the OntoBroker distribution into a folder (e.g. /usr/shared/ontoprise/ontobroker), Copy the license key file (ob_prof.key.xml) into the same folder. The setup process is now finished. You should be able to start OntoBroker using the commandline utilities. NOTE: The installer automatically installs the correct runtime dependending on the target machine's bit-version.

Precondition: The Uninstall function deletes the Installation folder of OntoStudio. Make sure that you have copied the KeyFile to another location before starting the Uninstall function; otherwise the KeyFile might be deleted! From the Windows Start menu select: Start -> All Programs -> OntoStudio Version -> Uninstall. Remove legacy OntoStudio with the help of the uninstall wizard. Click on Next. The uninstall wizard guides you through the further uninstall process. Click on Uninstall.All of the OntoStudio components are removed. Click on Accept. Click on OK.The deinstallation starts. Click on Close. The deinstallation is finished and the OntoStudio software is not on your computer anymore. The window closes.

OntoBroker supports multiple ontology languages: ObjectLogic RDF/RDFS OWL RIF OntoBroker provides native support for RDF/RDFS and OWL. This makes OntoBroker applicable for a wide range of semantic applications and scenarios. It is possible to use OntoBroker as a high-performance RDF triple store (or quad store), for typical OWL reasoning tasks (e.g. consistency checks) for conjunctive queries against an OWL ontology, for high performance ObjectLogic reasoning for evaluating and debugging rules. It is possible to use different storage systems with all ontology languages. This means that you can use the persistent storage H2 for storing OWL axioms, RDF triples and ObjectLogic facts and rules. You can use SPARQL (W3C standard for RDF query languages) for executing queries in combination with all other ontology languages (see the "Query Languages" chapter for further details). OntoBroker also provides a powerful Java-based API which can be used to open, modify and store ontologies, convert ontology languages (e.g. from OWL to ObjectLogic) and to execute queries against an ontology. This API was designed to be independent from the ontology language. This makes it easy to access OntoBroker from your own applications and to write applications which can deal with all ontology languages. The ontology language can be set in the OntoConfig.prp configuration file of the OntoBroker server: OntologyLanguage = ObjectLogic or OntologyLanguage = RDF or OntologyLanguage = OWL

OntoBroker RDF is an RDF triple store, query and inferencing engine. It is well integrated into the general OntoBroker suite, allowing close interaction between the other supported knowledge representation formats OWL and ObjectLogic. Staying close to the official Semantic Web standards like RDF, RDF Schema, and SPARQL is one of the primary design goals. However, the implementation on a horn logic-based model imposes some restrictions in standard compliance -- and some unique features too. This section will give a pragmatic overview of OntoBroker RDF, focusing on RDF-related options and features. For more general issues, see the provided locations in the main OntoBroker documentation.

Enter your answer here