Kuria v. 1.0.1 Released
Published by {{by}} on {{at}} and updated at {{updated}}.
Abstract:
Kuria is a frontend generator based on Java POJO annotations. The new version 1.0.1 is mainly bug fixing and some new features.
Kuria provides a set of java annotations and a parser to generate bindings for widget classes. These bindings are used to create input masks, tables and trees for the annotated domain model. It is strongly advised to use Kuria inside Eclipse plug-ins or maven projects.
Kuria is completely independent from any Topic Maps technology. But the Ontology-based automatic generation of applications in Onotoa uses Aranuka in conjunction with Kuria.
The new Kuria version 1.0.1 is mainly bug fixing and provide the following new features:
- added weight attribute to field annotations to set order of widgets
- create widgets for annotated super classes in InputMask
- added Annox support (only in non OSGi environments)
You will get the sources and the change log kor Kuria at Google Code.
Authors of this document are
Lutz Maicher
http://www.wifa.uni-leipzig.de/isrm ...
Lutz is project leader of Musica Migrans, Topic Maps Lab Community.. , and Repertoire of the St. Thomas.. .
Subject Matter
Generating an Ontology Specific Editor
by Hannes Niederhausen, Sven Windisch, ...
Semantic technologies like Topic Maps provide a generic way of structured data representation. These technologies can be used to create data stores …
Was presented at SEMAPRO 2010.
Generating an Ontology Specific Editor
by Hannes Niederhausen, Sven Windisch, ...
Semantic technologies like Topic Maps provide a generic way of structured data representation. These technologies can be used to create data stores …
Was presented at SEMAPRO 2010.
Kuria
is a {{project}}.
Kuria provides a set of java annotations and a parser to generate bindings for widget classes. These bindings are used to input masks, tables and ...
Visit homepage of Kuria
As a former information scientist, I am fascinated since 1999 by the capabilities for building Topic Maps-based knowledge systems having the potential to augment human mind. One can model arbitrary knowledge organization systems, deal with semantic heterogeneity, collocate all facts about one subject in one logical place, and with TMQL have semantic retrieval on federated semantic networks. Therefore I expect bright prospects for business concepts building on the exchange of such knowledge snippets via semantic knowledge services.
