XML, or Extensible Markup Language, forms the foundation for structured text creation in Xeditor. This structure is what gives the text semantic meaning. That introduces a degree of complexity, which Xeditor resolves.
Authors can choose between a technical and a visual view. This makes creating XML documents easy and intuitive for any user, cutting down on training time and dramatically reducing the amount of training required.
In order for documents in XML format to be valid, they need to be validated against a set of rules, an XML schema (XSD), or a document type definition (DTD). This set of rules gives the content a semantic structure. The XML content that is generated is then standardized accordingly, machine-readable, and thus ready for automated subsequent processing.
The intelligent authoring support in Xeditor guides users intuitively through this set of rules – without requiring any prior XML experience or technical knowledge. Xeditor supports multiple industry standards, including DITA, S1000D, DocBook, and JATS – and can also be rapidly configured to support any custom schema.
Because of their structure and semantic markup, documents created in Xeditor form the ideal basis for machine learning. Structured data is perfect for storing relationships and highly linked data, which supports ontology management.
AI-based enterprise search solutions such as Mindbreeze InSpire are able to analyze, interpret and learn from this high-quality data in an optimal way. Data and information created in Xeditor can thus be applied to all other enterprise data. This results in a multitude of additional use cases. Whether it’s AI or other emerging digital formats and channels, the potential to leverage structured content is immense and far from exhausted.
Head of Software Development, NWB Verlag