Semantic knowledge modeling

metaphactory delivers an intuitive vocabulary management interface that supports domain experts / SMEs and business users in creating and editing SKOS vocabularies and taxonomies to capture business-relevant terms. This helps model domain-specific knowledge in terms that business users understand and can use for analysis and in answering critical business questions.

Controlled vocabularies created directly in metaphactory or maintained via external tools can be linked to specific classes in the ontology through metaphactory’s ontology editor. This simplifies the communication between stakeholders.

With its data cataloging capabilities, metaphactory makes dataset metadata itself an integral part of the connected graph. Based on open standards (e.g., DCAT, Dublin Core), these capabilities allow ontology engineers and taxonomists to easily create, manage, or import existing dataset metadata and enrich other assets with this additional metadata layer. This adds explicit dataset context information to ontologies and vocabularies.

Exposed in the publishing interface, the dataset context information becomes immediately accessible to end users, domain experts / SMEs. It delivers additional and vital context information for end-user tasks and helps drive traceable and trustful business decisions.

metaphactory supports import of or federated virtual access over multiple data sources and also allows for the integration of public ontologies and vocabularies. Examples of such public ontologies and vocabularies from various verticals include: the HCLSIG/PharmaOntology, the MeSH ontology, the STW thesaurus for economics, CIDOC-CRM, Bibframe, schema.org, ISO15926-14, FIBO, and many more.

These assets can be used as a basis for your own semantic model, can be extended to fit your specific needs, or can be implemented as extensions to your own, proprietary knowledge model.

Knowledge democratization requires that everyone in the organization has access to relevant semantic models and vocabularies. metaphactory does not only support the creation and management of such knowledge models, but it additionally allows for easy and streamlined publishing via API and through a web application. This web application becomes a central publishing interface and resource for end users across the entire organization. SSO integration guarantees compliance with company policies when it comes to user access and management, while metaphactory’s templating engine enables you to define which information you want to publish to which user groups.

Another important aspect here is publishing and sharing within the community or for reuse and analysis in pre-competitive research. Since the knowledge model is built using flexible, open formats, it becomes human- and machine-understandable, and can be made available to partners or the general public for reuse.

metaphactory transforms knowledge modeling into a streamlined, end-to-end experience based on an agile and iterative process. It allows all relevant stakeholders - from ontology engineers and taxonomists to domain experts / SMEs and business users - to equally contribute to the ontology engineering process and collaborate on defining and continuously improving the semantic model(s), while eliminating obstacles such as external expert tools, media-breaks, or synchronization issues.

Additionally, metaphactory delivers enhanced support for managing these assets, such as cataloging, versioning, and metadata editing capabilities. The ontology, vocabulary, and dataset catalogs feature capabilities to import, create, manage metadata for, and search and explore. They improve access to assets across the organization, foster reuse, and help to build governance processes that scale across individual projects in an organization.

Finally, all assets and changes to these assets can be versioned through Git integration. This enables the seamless embedding of knowledge modeling into governance and CI/CD processes.

Through integration with data-driven algorithms, metaphactory supports the enrichment of explicit knowledge mapped to your semantic model with knowledge learned or derived via machine learning, reasoning or other techniques. By enriching your knowledge model with information on decision models, metaphactory enables decision makers to move from repetitive daily decisions to an automated decision intelligence solution - a solution that not only provides deep, contextual analytics but also decision support and, ultimately, continuous intelligence and decision automation.